Composting of high moisture content swine manure with corncob in a pilot-scale aerated static bin system.

PubMed

Zhu, Nengwu

2006-10-01

Pilot composting experiments of swine manure with corncob were conducted to evaluate the performance of the aerated static bin composting system. Effects of temperature control (60 and 70 degrees C) and moisture content (70% and 80%) were monitored on the composting by measuring physical and chemical indexes. The results showed that (1) the composting system could destroy pathogens, converted nitrogen from unstable ammonia to stable organic forms, and reduced the volume of waste; (2) significant difference of NH(4)(+)-N (P(12) = 0.074), and (NO(3)(-) + NO(2)(-))-N (P(12) = 0.085) was found between the temperature control treatments; (3) anaerobic reaction in the treatment with 80% moisture content resulted in significant difference of pH (P(23) = 0.006), total organic matter (P(23) = 0.003), and germination index (P(23) = 0.040) between 70% and 80%. Therefore, the optimum initial moisture content was less than 80% with the composting of swine manure and corncob by using the composting system.

Tracing dynamics of relative volumetric soil moisture content using SAR data

NASA Astrophysics Data System (ADS)

Avetisyan, Daniela; Velizarova, Emiliya; Nedkov, Roumen

2017-09-01

Soil is a dominant factor of the terrestrial geosystems in the dry sub-humid zones, particularly through its effect on biomass production. Due to the climate changes and industrial development, soil resources in these zones are prone to degradation. Mitigation of the negative effects of land degradation requires in-depth knowledge of the ongoing in the geosystems processes and application of innovative end effective methods for their investigation. The recent study aims to evaluate the relative soil moisture content in various soil differences and to trace its dynamics during growing season. In order to achieve this aim, Relative Soil Moisture Index (RSMI) based on Synthetic Aperture Radar (SAR) data was calculated. The index estimates the relative variation of volumetric soil moisture content in a given time period and enables determination of its change in relative values. The generated results show very high level of correlation for the investigated pilot areas which testifies that the RSMI is applicable in different territories.

A Methodology for Soil Moisture Retrieval from Land Surface Temperature, Vegetation Index, Topography and Soil Type

NASA Astrophysics Data System (ADS)

Pradhan, N. R.

2015-12-01

Soil moisture conditions have an impact upon hydrological processes, biological and biogeochemical processes, eco-hydrology, floods and droughts due to changing climate, near-surface atmospheric conditions and the partition of incoming solar and long-wave radiation between sensible and latent heat fluxes. Hence, soil moisture conditions virtually effect on all aspects of engineering / military engineering activities such as operational mobility, detection of landmines and unexploded ordinance, natural material penetration/excavation, peaking factor analysis in dam design etc. Like other natural systems, soil moisture pattern can vary from completely disorganized (disordered, random) to highly organized. To understand this varying soil moisture pattern, this research utilized topographic wetness index from digital elevation models (DEM) along with vegetation index from remotely sensed measurements in red and near-infrared bands, as well as land surface temperature (LST) in the thermal infrared bands. This research developed a methodology to relate a combined index from DEM, LST and vegetation index with the physical soil moisture properties of soil types and the degree of saturation. The advantage in using this relationship is twofold: first it retrieves soil moisture content at the scale of soil data resolution even though the derived indexes are in a coarse resolution, and secondly the derived soil moisture distribution represents both organized and disorganized patterns of actual soil moisture. The derived soil moisture is used in driving the hydrological model simulations of runoff, sediment and nutrients.

Physicochemical, nutritional and infrared spectroscopy evaluation of an optimized soybean/corn flour extrudate

USDA-ARS?s Scientific Manuscript database

A central composite design using RMS successfully described the effect of independent variables (feed moisture, die temperature and soybean proportion) on the specific parameters of product quality (expansion index, water absorption index, water solubility index and total color difference) studied. ...

Calculating crop water requirement satisfaction in the West Africa Sahel with remotely sensed soil moisture

USGS Publications Warehouse

McNally, Amy; Gregory J. Husak,; Molly Brown,; Carroll, Mark L.; Funk, Christopher C.; Soni Yatheendradas,; Kristi Arsenault,; Christa Peters-Lidard,; Verdin, James

2015-01-01

The Soil Moisture Active Passive (SMAP) mission will provide soil moisture data with unprecedented accuracy, resolution, and coverage, enabling models to better track agricultural drought and estimate yields. In turn, this information can be used to shape policy related to food and water from commodity markets to humanitarian relief efforts. New data alone, however, do not translate to improvements in drought and yield forecasts. New tools will be needed to transform SMAP data into agriculturally meaningful products. The objective of this study is to evaluate the possibility and efficiency of replacing the rainfall-derived soil moisture component of a crop water stress index with SMAP data. The approach is demonstrated with 0.1°-resolution, ~10-day microwave soil moisture from the European Space Agency and simulated soil moisture from the Famine Early Warning Systems Network Land Data Assimilation System. Over a West Africa domain, the approach is evaluated by comparing the different soil moisture estimates and their resulting Water Requirement Satisfaction Index values from 2000 to 2010. This study highlights how the ensemble of indices performs during wet versus dry years, over different land-cover types, and the correlation with national-level millet yields. The new approach is a feasible and useful way to quantitatively assess how satellite-derived rainfall and soil moisture track agricultural water deficits. Given the importance of soil moisture in many applications, ranging from agriculture to public health to fire, this study should inspire other modeling communities to reformulate existing tools to take advantage of SMAP data.

A Methodology for Surface Soil Moisture and Vegetation Optical Depth Retrieval Using the Microwave Polarization Difference Index

NASA Technical Reports Server (NTRS)

Owe, Manfred; deJeu, Richard; Walker, Jeffrey; Zukor, Dorothy J. (Technical Monitor)

2001-01-01

A methodology for retrieving surface soil moisture and vegetation optical depth from satellite microwave radiometer data is presented. The procedure is tested with historical 6.6 GHz brightness temperature observations from the Scanning Multichannel Microwave Radiometer over several test sites in Illinois. Results using only nighttime data are presented at this time, due to the greater stability of nighttime surface temperature estimation. The methodology uses a radiative transfer model to solve for surface soil moisture and vegetation optical depth simultaneously using a non-linear iterative optimization procedure. It assumes known constant values for the scattering albedo and roughness. Surface temperature is derived by a procedure using high frequency vertically polarized brightness temperatures. The methodology does not require any field observations of soil moisture or canopy biophysical properties for calibration purposes and is totally independent of wavelength. Results compare well with field observations of soil moisture and satellite-derived vegetation index data from optical sensors.

Role of geospatial technology in identifying natural habitat of malarial vectors in South Andaman, India.

PubMed

Shankar, Shiva; Agrawal, Deepak Kumar

2016-03-01

Malaria is a serious disease which has repeatedly threatened Andaman, an island territory of India. Uncharted dense vegetation and inaccessibility are the salient features of the area and the major areas are covered by remotely sensed data to identify the malaria vector's natural habitat. The present investigation appraises the role of geospatial technologies in identifying the natural habitat of malarial vectors. The base map was prepared from Survey of India's toposheets, the landuse map was prepared from indices techniques like normalised difference vegetation index (NDVI), normalised difference water index (NDWI), modified normalised difference water index (MNDWI), normalised difference pond index (NDPI), and normalized difference turbidity index (NDTI) in conjugation with visual interpretation. The soil moisture content map was reproduced from the soil atlas of Andaman and Nicobar Islands followed by generation of an aspect profile from ASTER-GDEM satellite data. Both the landuse map and aspect profile were validated for accuracy in the field. A weighted overlay analysis of the classes like landuse, soil moisture and aspect profile of the study area resulted in identification of the potential natural habitat map of malaria vector surrounding the areas of Tushnabad, Garacharma, Manglutan, Chouldari, Ferrargunj and Wimberlygunj hamlets. The natural habitat of malaria vector indicated that Tushnabad, Garacharma, Manglutan, Chouldari, Ferrargunj and Wimberlygunj hamlets are within the proximity of 2.5 km from the prime habitat location with more number of malaria positive cases. Also these hamlets are surrounded by dense evergreen forest and the land surface is draped by clay loam and clay soil texture exhibiting high soil moisture content warranting high rates of survival and proliferation of the vector ensuring resurgence of malaria every year. It is thus concluded that application of geospatial technologies plays an important role in identifying the natural habitat of malaria vector.

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

NASA Astrophysics Data System (ADS)

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

2001-08-01

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

Improvment of the Trapezoid Method Using Raw Landsat Image Digital Count Data for Soil Moisture Estimation in the Texas (usa) High Plains

NASA Astrophysics Data System (ADS)

Shafian, S.; Maas, S. J.

2015-12-01

Variations in soil moisture strongly affect surface energy balances, regional runoff, land erosion and vegetation productivity (i.e., potential crop yield). Hence, the estimation of soil moisture is very valuable in the social, economic, humanitarian (food security) and environmental segments of society. Extensive efforts to exploit the potential of remotely sensed observations to help quantify this complex variable are ongoing. This study aims at developing a new index, the Thermal Ground cover Moisture Index (TGMI), for estimating soil moisture content. This index is based on empirical parameterization of the relationship between raw image digital count (DC) data in the thermal infrared spectral band and ground cover (determined from raw image digital count data in the red and near-infrared spectral bands).The index uses satellite-derived information only, and the potential for its operational application is therefore great. This study was conducted in 18 commercial agricultural fields near Lubbock, TX (USA). Soil moisture was measured in these fields over two years and statistically compared to corresponding values of TGMI determined from Landsat image data. Results indicate statistically significant correlations between TGMI and field measurements of soil moisture (R2 = 0.73, RMSE = 0.05, MBE = 0.17 and AAE = 0.049), suggesting that soil moisture can be estimated using this index. It was further demonstrated that maps of TGMI developed from Landsat imagery could be constructed to show the relative spatial distribution of soil moisture across a region.

Predicting moisture content: fuel moisture indicator sticks in the Pacific Northwest.

Treesearch

Owen P. Cramer

1961-01-01

Successful day-to-day planning of presuppression activities requires accurate prediction of burning index. In the Pacific Northwest, forecasts of burning index are prepared by the fire-control man and are based on predictions of windspeed and fuel moisture. Although fuel moisture is affected by a number of weather elements and is consequently difficult to predict, the...

Effect of Water Invasion on Outburst Predictive Index of Low Rank Coals in Dalong Mine

PubMed Central

Jiang, Jingyu; Cheng, Yuanping; Mou, Junhui; Jin, Kan; Cui, Jie

2015-01-01

To improve the coal permeability and outburst prevention, coal seam water injection and a series of outburst prevention measures were tested in outburst coal mines. These methods have become important technologies used for coal and gas outburst prevention and control by increasing the external moisture of coal or decreasing the stress of coal seam and changing the coal pore structure and gas desorption speed. In addition, techniques have had a significant impact on the gas extraction and outburst prevention indicators of coal seams. Globally, low rank coals reservoirs account for nearly half of hidden coal reserves and the most obvious feature of low rank coal is the high natural moisture content. Moisture will restrain the gas desorption and will affect the gas extraction and accuracy of the outburst prediction of coals. To study the influence of injected water on methane desorption dynamic characteristics and the outburst predictive index of coal, coal samples were collected from the Dalong Mine. The methane adsorption/desorption test was conducted on coal samples under conditions of different injected water contents. Selective analysis assessed the variations of the gas desorption quantities and the outburst prediction index (coal cutting desorption index). Adsorption tests indicated that the Langmuir volume of the Dalong coal sample is ~40.26 m3/t, indicating a strong gas adsorption ability. With the increase of injected water content, the gas desorption amount of the coal samples decreased under the same pressure and temperature. Higher moisture content lowered the accumulation desorption quantity after 120 minutes. The gas desorption volumes and moisture content conformed to a logarithmic relationship. After moisture correction, we obtained the long-flame coal outburst prediction (cutting desorption) index critical value. This value can provide a theoretical basis for outburst prediction and prevention of low rank coal mines and similar occurrence conditions of coal seams. PMID:26161959

A MODIS-based begetation index climatology

USDA-ARS?s Scientific Manuscript database

Passive microwave soil moisture algorithms must account for vegetation attenuation of the signal in the retrieval process. One approach to accounting for vegetation is to use vegetation indices such as the Normalized Difference Vegetation Index (NDVI) to estimate the vegetation optical depth. The pa...

Dryland pasture and crop conditions as seen by HCMM. [Washita River watershed

NASA Technical Reports Server (NTRS)

Harlan, J. C. (Principal Investigator); Rosenthal, W. D.; Blanchard, B. J.

1981-01-01

The antecedent precipitation index (API) was related to surface temperatures as measured from the NASA C-130 and HCMM thermal data. Significant results from the aircraft flight in May 1978, include: (1) canopy temperature were measured accurately remotely; (2) pasture surface temperatures were related to pasture and wheat soil moisture conditions; (3) no relationship was developed with that data set between wheat yield and thermal infrared data due to a lack of moisture stress during the measurement period; and (4) lake surface temperatures were useful in normalizing the thermal IR data. Results from HCMM also suggested a relationship between thermal IR data and antecedent precipitation index. While HCMM was adequate in detecting relative soil moisture differences, the overpass timing was infrequent and prevented detailed analysis of the API/thermal relationship.

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.

Soil moisture retrival from Sentinel-1 and Modis synergy

NASA Astrophysics Data System (ADS)

Gao, Qi; Zribi, Mehrez; Escorihuela, Maria Jose; Baghdadi, Nicolas

2017-04-01

This study presents two methodologies retrieving soil moisture from SAR remote sensing data. The study is based on Sentinel-1 data in the VV polarization, over a site in Urgell, Catalunya (Spain). In the two methodologies using change detection techniques, preprocessed radar data are combined with normalized difference vegetation index (NDVI) auxiliary data to estimate the mean soil moisture with a resolution of 1km. By modeling the relationship between the backscatter difference and NDVI, the soil moisture at a specific NDVI value is retrieved. The first algorithm is already developed on West Africa(Zribi et al., 2014) from ERS scatterometer data to estimate soil water status. In this study, it is adapted to Sentinel-1 data and take into account the high repetitiveness of data in optimizing the inversion approach. Another new method is developed based on the backscatter difference between two adjacent days of Sentinel-1 data w.r.t. NDVI, with smaller vegetation change, the backscatter difference is more sensitive to soil moisture. The proposed methodologies have been validated with the ground measurement in two demonstrative fields with RMS error about 0.05 (in volumetric moisture), and the coherence between soil moisture variations and rainfall events is observed. Soil moisture maps at 1km resolution are generated for the study area. The results demonstrate the potential of Sentinel-1 data for the retrieval of soil moisture at 1km or even better resolution.

Stomatal conductance, canopy temperature, and leaf area index estimation using remote sensing and OBIA techniques

Treesearch

S. Panda; D.M. Amatya; G. Hoogenboom

2014-01-01

Remotely sensed images including LANDSAT, SPOT, NAIP orthoimagery, and LiDAR and relevant processing tools can be used to predict plant stomatal conductance (gs), leaf area index (LAI), and canopy temperature, vegetation density, albedo, and soil moisture using vegetation indices like normalized difference vegetation index (NDVI) or soil adjusted...

Using a Simple Parcel Model to Investigate the Haines Index

Treesearch

Mary Ann Jenkins; Steven K. Krueger; Ruiyu Sun

2003-01-01

The Haines Index (Haines 1988) ia fire-weather index based on stability and moisture conditions of the lower atmosphere that rates the potential for large fire growth or extreme fire behavior. The Hained Index is calculated by adding a temperature term a to a moisture term b.

The relationship between species richness and aboveground biomass in a primary Pinus kesiya forest of Yunnan, southwestern China.

PubMed

Li, Shuaifeng; Lang, Xuedong; Liu, Wande; Ou, Guanglong; Xu, Hui; Su, Jianrong

2018-01-01

The relationship between biodiversity and biomass is an essential element of the natural ecosystem functioning. Our research aims at assessing the effects of species richness on the aboveground biomass and the ecological driver of this relationship in a primary Pinus kesiya forest. We sampled 112 plots of the primary P. kesiya forests in Yunnan Province. The general linear model and the structural equation model were used to estimate relative effects of multivariate factors among aboveground biomass, species richness and the other explanatory variables, including climate moisture index, soil nutrient regime and stand age. We found a positive linear regression relationship between the species richness and aboveground biomass using ordinary least squares regressions. The species richness and soil nutrient regime had no direct significant effect on aboveground biomass. However, the climate moisture index and stand age had direct effects on aboveground biomass. The climate moisture index could be a better link to mediate the relationship between species richness and aboveground biomass. The species richness affected aboveground biomass which was mediated by the climate moisture index. Stand age had direct and indirect effects on aboveground biomass through the climate moisture index. Our results revealed that climate moisture index had a positive feedback in the relationship between species richness and aboveground biomass, which played an important role in a link between biodiversity maintenance and ecosystem functioning. Meanwhile, climate moisture index not only affected positively on aboveground biomass, but also indirectly through species richness. The information would be helpful in understanding the biodiversity-aboveground biomass relationship of a primary P. kesiya forest and for forest management.

The relationship between species richness and aboveground biomass in a primary Pinus kesiya forest of Yunnan, southwestern China

PubMed Central

Li, Shuaifeng; Lang, Xuedong; Liu, Wande; Ou, Guanglong; Xu, Hui

2018-01-01

The relationship between biodiversity and biomass is an essential element of the natural ecosystem functioning. Our research aims at assessing the effects of species richness on the aboveground biomass and the ecological driver of this relationship in a primary Pinus kesiya forest. We sampled 112 plots of the primary P. kesiya forests in Yunnan Province. The general linear model and the structural equation model were used to estimate relative effects of multivariate factors among aboveground biomass, species richness and the other explanatory variables, including climate moisture index, soil nutrient regime and stand age. We found a positive linear regression relationship between the species richness and aboveground biomass using ordinary least squares regressions. The species richness and soil nutrient regime had no direct significant effect on aboveground biomass. However, the climate moisture index and stand age had direct effects on aboveground biomass. The climate moisture index could be a better link to mediate the relationship between species richness and aboveground biomass. The species richness affected aboveground biomass which was mediated by the climate moisture index. Stand age had direct and indirect effects on aboveground biomass through the climate moisture index. Our results revealed that climate moisture index had a positive feedback in the relationship between species richness and aboveground biomass, which played an important role in a link between biodiversity maintenance and ecosystem functioning. Meanwhile, climate moisture index not only affected positively on aboveground biomass, but also indirectly through species richness. The information would be helpful in understanding the biodiversity-aboveground biomass relationship of a primary P. kesiya forest and for forest management. PMID:29324901

Effects of heat-moisture treatment reaction conditions on the physicochemical and structural properties of maize starch: moisture and length of heating.

PubMed

Sui, Zhongquan; Yao, Tianming; Zhao, Yue; Ye, Xiaoting; Kong, Xiangli; Ai, Lianzhong

2015-04-15

Changes in the properties of normal maize starch (NMS) and waxy maize starch (WMS) after heat-moisture treatment (HMT) under various reaction conditions were investigated. NMS and WMS were adjusted to moisture levels of 20%, 25% and 30% and heated at 100 °C for 2, 4, 8 and 16 h. The results showed that moisture content was the most important factor in determining pasting properties for NMS, whereas the heating length was more important for WMS. Swelling power decreased in NMS but increased in WMS, and while the solubility index decreased for both samples, the changes were largely determined by moisture content. The gelatinisation temperatures of both samples increased with increasing moisture content but remained unchanged with increasing heating length. The Fourier transform infrared (FT-IR) absorbance ratio was affected to different extents by the moisture levels but remained constant with increasing the heating length. The X-ray intensities increased but relative crystallinity decreased to a greater extent with increasing moisture content. This study showed that the levels of moisture content and length of heating had significant impacts on the structural and physicochemical properties of normal and waxy maize starches but to different extents. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

A Novel Optical Model for Remote Sensing of Near-Surface Soil Moisture

NASA Astrophysics Data System (ADS)

Babaeian, E.; Sadeghi, M.; Jones, S. B.; Tuller, M.

2016-12-01

Common triangle and trapezoid methods that are based on both optical and thermal remote sensing (RS) information have been widely applied in the past to estimate near-surface soil moisture from the soil temperature - vegetation index space (e.g., LST-NDVI). For most cases, this approach assumes a linear relationship between soil moisture and temperature. Though this linearity assumption yields reasonable moisture estimates, it is not always justified as evidenced by laboratory and field measurements. Furthermore, this approach requires optical as well as thermal RS data for definition of the land surface temperature (LST) - vegetation index space, therefore, it is not applicable to satellites that do not provide thermal output such as the ESA Sentinel-2. To overcome these limitations, we propose a novel trapezoid model that only relies on optical NIR and SWIR data. The new model was validated using Sentinel-2 and Landsat-8 data for the semiarid Walnut Gulch (AZ) and sub humid Little Washita (OK) watersheds that vastly differ in land use and surface cover and provide excellent ground-truth moisture information from extensive sensor networks. Preliminary results for 2015-2016 indicate significant potential of the new model with a RMSE smaller than 4% volumetric near-surface moisture content and also confirm the enhanced utility of the high spatially and temporally resolved Sentinel-2 data.

A pavement Moisture Accelerated Distress (MAD) identification system, volume 2

NASA Astrophysics Data System (ADS)

Carpenter, S. H.; Darter, M. I.; Dempsey, B. J.

1981-09-01

A users manual is designed which provides the engineer with a rational method of examining a pavement and determining rehabilitation needs that are related to the causes of the existing distress, particularly moisture related distress. The key elements in this procedure are the MAD Index developed in Volume 1, the Pavement Condition Index (PCI) and the Moisture Distress Index (MDI). Step by step procedures are presented for calculating each parameter. Complete distress identification manuals are included for asphalt surfaced highways and jointed reinforced concrete highways with pictures and descriptions of all major distress types. Descriptions of the role moisture plays in the development of each distress type are included.

Moisture variation inferred from a nebkha profile correlates with vegetation changes in the southwestern Mu Us Desert of China over one century.

PubMed

Li, Jinchang; Zhao, Yanfang; Han, Liuyan; Zhang, Guoming; Liu, Rentao

2017-11-15

We inferred moisture variations from the early 1930s to the early 2010s in the southwestern Mu Us Desert of China using Rb/Sr ratio, chemical index of alteration (CIA), and organic matter (OM) content in a nebkha profile. Our results showed that the variations in moisture may have been the main factor that controlled vegetation recovery or degradation, and we believe that gradual vegetation recovery was notable throughout the study area during the past 80years, despite two notable degradation stages during the mid-1950s and the mid-1980s. The Rb/Sr ratio, CIA, and OM content revealed that moisture levels increased during the study period, though with large interannual variations. During the early stage of nebkha formation, the moisture variations were controlled by unusually low precipitation. Thereafter, the precipitation, pan evaporation and temperature determined together moisture variations, but the key factor determining moisture variations was different during different periods. The moisture variations trend revealed in this study may not be restricted to this region as it was similar with the adjacent Mongolian Plateau. Copyright © 2017 Elsevier B.V. All rights reserved.

Effects of management practices on reflectance of spring wheat canopies. [Williston, North Dakota Agricultural Experiment Station

NASA Technical Reports Server (NTRS)

Daughtry, C. S. T.; Bauer, M. E.; Crecelius, D. W.; Hixson, M. M. (Principal Investigator)

1980-01-01

The effects of available soil moisture, planting date, nitrogen fertilization, and cultivar on reflectance of spring wheat (Triticum aestivum L.) canopies were investigated. Spectral measurements were acquired on eight dates throughout the growing season, along with measurements of crop maturity stage, leaf area index, biomass, plant height, percent soil cover, and soil moisture. Planting date and available soil moisture were the primary agronomic factors which affected reflectance of spring wheat canopies from tillering to maturity. Comparisons of treatments indicated that during the seedling and tillering stages planting date was associated with 36 percent and 85 percent of variation in red and near infrared reflectances, respectively. As the wheat headed and matured, less of the variation in reflectance was associated with planting date and more with available soil moisture. By mid July, soil moisture accounted for 73 percent and 69 percent of the variation in reflectance in red and near infrared bands, respectively. Differences in spectral reflectance among treatments were attributed to changes in leaf area index, biomass, and percent soil cover. Cultivar and N fertilization rate were associated with very little of the variation in the reflectance of these canopies.

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.

Crop moisture estimation over the southern Great Plains with dual polarization 1.66 centimeter passive microwave data from Nimbus 7

NASA Technical Reports Server (NTRS)

Mcfarland, M. J.; Harder, P. H., II; Wilke, G. D.; Huebner, G. L., Jr.

1984-01-01

Moisture content of snow-free, unfrozen soil is inferred using passive microwave brightness temperatures from the scanning multichannel microwave radiometer (SMMR) on Nimbus-7. Investigation is restricted to the two polarizations of the 1.66 cm wavelength sensor. Passive microwave estimates of soil moisture are of two basic categories; those based upon soil emissivity and those based upon the polarization of soil emission. The two methods are compared and contrasted through the investigation of 54 potential functions of polarized brightness temperatures and, in some cases, ground-based temperature measurements. Of these indices, three are selected for the estimated emissivity, the difference between polarized brightness temperatures, and the normalized polarization difference. Each of these indices is about equally effective for monitoring soil moisture. Using an antecedent precipitation index (API) as ground control data, temporal and spatial analyses show that emissivity data consistently give slightly better soil moisture estimates than depolarization data. The difference, however, is not statistically significant. It is concluded that polarization data alone can provide estimates of soil moisture in areas where the emissivity cannot be inferred due to nonavailability of surface temperature data.

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.

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 (...

Soil moisture downscaling using a simple thermal based proxy

NASA Astrophysics Data System (ADS)

Peng, Jian; Loew, Alexander; Niesel, Jonathan

2016-04-01

Microwave remote sensing has been largely applied to retrieve soil moisture (SM) from active and passive sensors. The obvious advantage of microwave sensor is that SM can be obtained regardless of atmospheric conditions. However, existing global SM products only provide observations at coarse spatial resolutions, which often hamper their applications in regional hydrological studies. Therefore, various downscaling methods have been proposed to enhance the spatial resolution of satellite soil moisture products. The aim of this study is to investigate the validity and robustness of a simple Vegetation Temperature Condition Index (VTCI) downscaling scheme over different climates and regions. Both polar orbiting (MODIS) and geostationary (MSG SEVIRI) satellite data are used to improve the spatial resolution of the European Space Agency's Water Cycle Multi-mission Observation Strategy and Climate Change Initiative (ESA CCI) soil moisture, which is a merged product based on both active and passive microwave observations. The results from direct validation against soil moisture in-situ measurements, spatial pattern comparison, as well as seasonal and land use analyses show that the downscaling method can significantly improve the spatial details of CCI soil moisture while maintain the accuracy of CCI soil moisture. The application of the scheme with different satellite platforms and over different regions further demonstrate the robustness and effectiveness of the proposed method. Therefore, the VTCI downscaling method has the potential to facilitate relevant hydrological applications that require high spatial and temporal resolution soil moisture.

Assessing the relative influence of surface soil moisture and ENSO SST on precipitation predictability over the contiguous United States

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

Yoon, Jin-Ho; Leung, Lai-Yung R.

This study assesses the relative influence of soil moisture memory and tropical sea surface temperature (SST) in seasonal rainfall over the contiguous United States. Using observed precipitation, the NINO3.4 index and soil moisture and evapotranspiration simulated by a land surface model for 61 years, analysis was performed using partial correlations to evaluate to what extent land surface and SST anomaly of El Niño and Southern Oscillation (ENSO) can affect seasonal precipitation over different regions and seasons. Results show that antecedent soil moisture is as important as concurrent ENSO condition in controlling rainfall anomalies over the U.S., but they generally dominatemore » in different seasons with SST providing more predictability during winter while soil moisture, through its linkages to evapotranspiration and snow water, has larger influence in spring and early summer. The proposed methodology is applicable to climate model outputs to evaluate the intensity of land-atmosphere coupling and its relative importance.« less

Advances in Remote Sensing of Vegetation Merging NDVI, Soil Moisture, and Chlorophyll Fluorescence

NASA Astrophysics Data System (ADS)

Tucker, Compton

2016-04-01

I will describe an advance in remote sensing of vegetation in the time domain that combines simultaneous measurements of the normalized difference vegetation index, soil moisture, and chlorophyll fluorescence, all from different satellite sensors but acquired for the same areas at the same time step. The different sensor data are MODIS NDVI data from both Terra and Aqua platforms, soil moisture data from SMOS & SMP (aka SMAP but with only the passive radiometer), and chlorophyll fluorescence data from GOME-2. The complementary combination of these data provide important crop yield information for agricultural production estimates at critical phenological times in the growing season, provide a scientific basis to map land degradation, and enable quantitative determination of the end of the growing season in temperate zones.

Can the normalized soil moisture index improve the prediction of soil organic carbon based on hyperspectral remote sensing data?

NASA Astrophysics Data System (ADS)

van Wesemael, Bas; Nocita, Marco

2016-04-01

One of the problems for mapping of soil organic carbon (SOC) at large-scale based on visible - near and short wave infrared (VIS-NIR-SWIR) remote sensing techniques is the spatial variation of topsoil moisture when the images are collected. Soil moisture is certainly an aspect causing biased SOC estimations, due to the problems in discriminating reflectance differences due to either variations in organic matter or soil moisture, or their combination. In addition, the difficult validation procedures make the accurate estimation of soil moisture from optical airborne a major challenge. After all, the first millimeters of the soil surface reflect the signal to the airborne sensor and show a large spatial, vertical and temporal variation in soil moisture. Hence, the difficulty of assessing the soil moisture of this thin layer at the same moment of the flight. The creation of a soil moisture proxy, directly retrievable from the hyperspectral data is a priority to improve the large-scale prediction of SOC. This paper aims to verify if the application of the normalized soil moisture index (NSMI) to Airborne Prima Experiment (APEX) hyperspectral images could improve the prediction of SOC. The study area was located in the loam region of Wallonia, Belgium. About 40 samples were collected from bare fields covered by the flight lines, and analyzed in the laboratory. Soil spectra, corresponding to the sample locations, were extracted from the images. Once the NSMI was calculated for the bare fields' pixels, spatial patterns, presumably related to within field soil moisture variations, were revealed. SOC prediction models, built using raw and pre-treated spectra, were generated from either the full dataset (general model), or pixels belonging to one of the two classes of NSMI values (NSMI models). The best result, with a RMSE after validation of 1.24 g C kg-1, was achieved with a NSMI model, compared to the best general model, characterized by a RMSE of 2.11 g C kg-1. These results confirmed the advantage to controlling the effect of soil moisture on the detection of SOC. The NSMI proved to be a flexible concept, due to the possible use of different SWIR wavelengths, and ease of use, because measurements of soil moisture by other techniques are not needed. However, in the future, it will be important to assess the effectiveness of the NSMI for different soil types, and other hyperspectral sensors.

Remote Sensing of Soil Moisture: A Comparison of Optical and Thermal Methods

NASA Astrophysics Data System (ADS)

Foroughi, H.; Naseri, A. A.; Boroomandnasab, S.; Sadeghi, M.; Jones, S. B.; Tuller, M.; Babaeian, E.

2017-12-01

Recent technological advances in satellite and airborne remote sensing have provided new means for large-scale soil moisture monitoring. Traditional methods for soil moisture retrieval require thermal and optical RS observations. In this study we compared the traditional trapezoid model parameterized based on the land surface temperature - normalized difference vegetation index (LST-NDVI) space with the recently developed optical trapezoid model OPTRAM parameterized based on the shortwave infrared transformed reflectance (STR)-NDVI space for an extensive sugarcane field located in Southwestern Iran. Twelve Landsat-8 satellite images were acquired during the sugarcane growth season (April to October 2016). Reference in situ soil moisture data were obtained at 22 locations at different depths via core sampling and oven-drying. The obtained results indicate that the thermal/optical and optical prediction methods are comparable, both with volumetric moisture content estimation errors of about 0.04 cm3 cm-3. However, the OPTRAM model is more efficient because it does not require thermal data and can be universally parameterized for a specific location, because unlike the LST-soil moisture relationship, the reflectance-soil moisture relationship does not significantly vary with environmental variables (e.g., air temperature, wind speed, etc.).

A GIS-derived integrated moisture index

Treesearch

Louis R. Iverson; Anantha M. Prasad

2003-01-01

A geographic information system (GIS) approach was used in conjunction with forest-plot data to develop an integrated moisture index (IMI) that is being used to stratify and help explain landscape-level phenomena in the four study areas. Several landscape features (a slope-aspect shading index, cumulative flow of water downslope, curvature of the landscape, and water-...

Physicochemical characteristics and pollen spectra of organic and non-organic honey samples of Apis mellifera L.

PubMed

Sereia, Maria Josiane; Alves, Eloi M; Toledo, Vagner A A; Marchini, Luis C; Serine, Elizabete S; Faquinello, Patricia; Almeida, Daniela de; Moreti, Augusta C C C

2011-09-01

The aim of this research was to analyze and compare 17 honey samples, 11 organic and six non-organic Apis mellifera honey. The samples were analyzed concerning moisture, hydroxymethylfurfural, diastase index, water activity, color, total sugar, reducing sugar, sucrose, ash, viscosity, electrical conductivity, pH, acidity, and formol index. With the exception of acidity, reducing sugar and diastase index, the averages of other parameters were different between the two groups. All samples of organic honey presented moisture values between 23.50 and 24.40%. Among the nonorganic honey samples, two presented apparent sucrose amount upper the maximum limit established by the Brazilian Legislation. According to the quantitative analysis of pollen sediments in the honey samples and frequency of pollen types in 17 honey samples, 41.20% were classified as unifioral, and the remainder as polifioral.

Landsat-TM identification of Amblyomma variegatum (Acari: Ixodidae) habitats in Guadeloupe

NASA Technical Reports Server (NTRS)

Hugh-Jones, M.; Barre, N.; Nelson, G.; Wehnes, K.; Warner, J.; Garvin, J.; Garris, G.

1992-01-01

The feasibility of identifying specific habitats of the African bont tick, Amblyomma variegatum, from Landsat-TM images was investigated by comparing remotely sensed images of visible farms in Grande Terre (Guadeloupe) with field observations made in the same period of time (1986-1987). The different tick habitates could be separated using principal component analysis. The analysis clustered the sites by large and small variance of band values, and by vegetation and moisture indexes. It was found that herds in heterogeneous sites with large variances had more ticks than those in homogeneous or low variance sites. Within the heterogeneous sites, those with high vegetation and moisture indexes had more ticks than those with low values.

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

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

Estimating the responses of winter wheat yields to moisture variations in the past 35 years in Jiangsu Province of China

PubMed Central

Ding, Jinfeng; Li, Chunyan

2018-01-01

Jiangsu is an important agricultural province in China. Winter wheat, as the second major grain crop in the province, is greatly affected by moisture variations. The objective of this study was to investigate whether there were significant trends in changes in the moisture conditions during wheat growing seasons over the past decades and how the wheat yields responded to different moisture levels by means of a popular drought index, the Standardized Precipitation Evapotranspiration Index (SPEI). The study started with a trend analysis and quantification of the moisture conditions with the Mann-Kendall test and Sen’s Slope method, respectively. Then, correlation analysis was carried out to determine the relationship between de-trended wheat yields and multi-scalar SPEI. Finally, a multivariate panel regression model was established to reveal the quantitative yield responses to moisture variations. The results showed that the moisture conditions in Jiangsu were generally at a normal level, but this century appeared slightly drier in because of the relatively high temperatures. There was a significant correlation between short time scale SPEI values and wheat yields. Among the three critical stages of wheat development, the SPEI values in the late growth stage (April-June) had a closer linkage to the yields than in the seedling stage (October-November) and the over-wintering stage (December-February). Moreover, the yield responses displayed an asymmetric characteristic, namely, moisture excess led to higher yield losses compared to moisture deficit in this region. The maximum yield increment could be obtained under the moisture level of slight drought according to the 3-month SPEI at the late growth stage, while extreme wetting resulted in the most severe yield losses. The moisture conditions in the first 15 years of the 21st century were more favorable than in the last 20 years of the 20th century for wheat production in Jiangsu. PMID:29329353

Estimating the responses of winter wheat yields to moisture variations in the past 35 years in Jiangsu Province of China.

PubMed

Xu, Xiangying; Gao, Ping; Zhu, Xinkai; Guo, Wenshan; Ding, Jinfeng; Li, Chunyan

2018-01-01

Jiangsu is an important agricultural province in China. Winter wheat, as the second major grain crop in the province, is greatly affected by moisture variations. The objective of this study was to investigate whether there were significant trends in changes in the moisture conditions during wheat growing seasons over the past decades and how the wheat yields responded to different moisture levels by means of a popular drought index, the Standardized Precipitation Evapotranspiration Index (SPEI). The study started with a trend analysis and quantification of the moisture conditions with the Mann-Kendall test and Sen's Slope method, respectively. Then, correlation analysis was carried out to determine the relationship between de-trended wheat yields and multi-scalar SPEI. Finally, a multivariate panel regression model was established to reveal the quantitative yield responses to moisture variations. The results showed that the moisture conditions in Jiangsu were generally at a normal level, but this century appeared slightly drier in because of the relatively high temperatures. There was a significant correlation between short time scale SPEI values and wheat yields. Among the three critical stages of wheat development, the SPEI values in the late growth stage (April-June) had a closer linkage to the yields than in the seedling stage (October-November) and the over-wintering stage (December-February). Moreover, the yield responses displayed an asymmetric characteristic, namely, moisture excess led to higher yield losses compared to moisture deficit in this region. The maximum yield increment could be obtained under the moisture level of slight drought according to the 3-month SPEI at the late growth stage, while extreme wetting resulted in the most severe yield losses. The moisture conditions in the first 15 years of the 21st century were more favorable than in the last 20 years of the 20th century for wheat production in Jiangsu.

Development of an Integrated Moisture Index for predicting species composition

Treesearch

Louis R. Iverson; Charles T. Scott; Martin E. Dale; Anantha Prasad

1996-01-01

A geographic information system (GIS) approach was used to develop an Integrated Moisture Index (IMI), which was used to predict species composition for Ohio forests. Several landscape features (a slope-aspect shading index, cumulative flow of water downslope, curvature of the landscape, and the water-holding capacity of the soil) were derived from elevation and soils...

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.

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.

A New Approach for Validating Satellite Estimates of Soil Moisture Using Large-Scale Precipitation: Comparing AMSR-E Products

NASA Astrophysics Data System (ADS)

Tuttle, S. E.; Salvucci, G.

2012-12-01

Soil moisture influences many hydrological processes in the water and energy cycles, such as runoff generation, groundwater recharge, and evapotranspiration, and thus is important for climate modeling, water resources management, agriculture, and civil engineering. Large-scale estimates of soil moisture are produced almost exclusively from remote sensing, while validation of remotely sensed soil moisture has relied heavily on ground truthing, which is at an inherently smaller scale. Here we present a complementary method to determine the information content in different soil moisture products using only large-scale precipitation data (i.e. without modeling). This study builds on the work of Salvucci [2001], Saleem and Salvucci [2002], and Sun et al. [2011], in which precipitation was conditionally averaged according to soil moisture level, resulting in moisture-outflow curves that estimate the dependence of drainage, runoff, and evapotranspiration on soil moisture (i.e. sigmoidal relations that reflect stressed evapotranspiration for dry soils, roughly constant flux equal to potential evaporation minus capillary rise for moderately dry soils, and rapid drainage for very wet soils). We postulate that high quality satellite estimates of soil moisture, using large-scale precipitation data, will yield similar sigmoidal moisture-outflow curves to those that have been observed at field sites, while poor quality estimates will yield flatter, less informative curves that explain less of the precipitation variability. Following this logic, gridded ¼ degree NLDAS precipitation data were compared to three AMSR-E derived soil moisture products (VUA-NASA, or LPRM [Owe et al., 2001], NSIDC [Njoku et al., 2003], and NSIDC-LSP [Jones & Kimball, 2011]) for a period of nine years (2001-2010) across the contiguous United States. Gaps in the daily soil moisture data were filled using a multiple regression model reliant on past and future soil moisture and precipitation, and soil moisture was then converted to a ranked wetness index, in order to reconcile the wide range and magnitude of the soil moisture products. Generalized linear models were employed to fit a polynomial model to precipitation, given wetness index. Various measures of fit (e.g. log likelihood) were used to judge the amount of information in each soil moisture product, as indicated by the amount of precipitation variability explained by the fitted model. Using these methods, regional patterns appear in soil moisture product performance.

Enhanced agricultural drought monitoring using a soil water anomaly-based drought index in south-west India

NASA Astrophysics Data System (ADS)

Hochstöger, Simon; Pfeil, Isabella; Amarnath, Giriraj; Pani, Peejush; Enenkel, Markus; Wagner, Wolfgang

2017-04-01

In India, agriculture accounts for roughly 17% of the GDP and employs around 50% of the total workforce. Especially in the western part of India, most of the agricultural fields are non-irrigated. Hence, agriculture is highly dependent on the monsoon in these areas. However, the absence of rainfall during the monsoon season increases the occurrence of drought periods, which is the main environmental factor affecting agricultural productivity. Rainfall is often not accessible to plants due to runoff or increased rates of evapotranspiration. Therefore, knowledge of the soil moisture state in the root zone of the soil is of great interest in the field of agricultural drought monitoring and operational decision-support. By introducing soil moisture, retrieved via active or passive microwave remote sensors, the gap between rainfall and the subsequent response of vegetation can be closed. Agricultural droughts are strongly influenced by a lack of water availability in the root zone of the soil, making anomalies of the Advanced Scatterometer (ASCAT) soil water index (SWI), representing the water content in lower soil layers, a suitable measure to estimate the water deficit in the soil. These anomalies describe the difference of the actual soil moisture value to the long-term average calculated for the same period. The objective of the study is to investigate the usability of soil moisture anomalies for developing an indicator that is based on critical thresholds, which finally results in a classification with different drought severity levels. In order to evaluate the performance of the drought index, it is compared to the Integrated Drought Severity Index (IDSI), which is developed at the International Water Management Institute in Colombo, Sri Lanka and to rainfall data from the Indian Meteorological Department (IMD). Overall, first analyses show a high potential of using SWI anomalies for agricultural drought monitoring. Most of the drought events detected by negative SWI anomalies correspond to IDSI drought events and also to reduced precipitation during that time.

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).

Combining SMOS with visible and near/shortwave/thermal infrared satellite data for high resolution soil moisture estimates

NASA Astrophysics Data System (ADS)

Sánchez-Ruiz, Sergio; Piles, María; Sánchez, Nilda; Martínez-Fernández, José; Vall-llossera, Mercè; Camps, Adriano

2014-08-01

Sensors in the range of visible and near-shortwave-thermal infrared regions can be used in combination with passive microwave observations to provide soil moisture maps at much higher spatial resolution than the original resolution of current radiometers. To do so, a new downscaling algorithm ultimately based on the land surface temperature (LST) - Normalized Difference Vegetation Index (NDVI) - Brightness Temperature (TB) relationship is used, in which shortwave infrared indices are used as vegetation descriptors, instead of the more common near infrared ones. The theoretical basis of those indices, calculated as the normalized ratio of the 1240, 1640 and 2130 nm shortwave infrared (SWIR) bands and the 858 nm near infrared (NIR) band indicate that they are able to provide estimates of the vegetation water content. These so-called water indices extracted from MODIS products, have been used together with MODIS LST, and SMOS TB to improve the spatial resolution of ∼40 km SMOS soil moisture estimates. The aim was to retrieve soil moisture maps with the same accuracy as SMOS, but at the same resolution of the MODIS dataset, i.e., 500 m, which were then compared against in situ measurements from the REMEDHUS network in Spain. Results using two years of SMOS and MODIS data showed a similar performance for the four indices, with slightly better results when using the index derived from the first SWIR band. For the areal-average, a coefficient of correlation (R) of ∼0.61 and ∼0.72 for the morning and afternoon orbits, respectively, and a centered root mean square difference (cRMSD) of ∼0.04 m3 m-3 for both orbits was obtained. A twofold improvement of the current versions of this downscaling approach has been achieved by using more frequent and higher spatial resolution water indexes as vegetation descriptors: (1) the spatial resolution of the resulting soil moisture maps can be enhanced from ∼40 km up to 500 m, and (2) more accurate soil moisture maps (in terms of R and cRMSD) can be obtained, especially in periods of high vegetation activity. The results of this study support the use of high resolution LST and SWIR-based vegetation indices to disaggregate SMOS observations down to 500 m soil moisture maps, meeting the needs of fine-scale hydrological applications.

Detection of anomalous crop condition and soil variability mapping using a 26 year Landsat record and the Palmer crop moisture index

NASA Astrophysics Data System (ADS)

Venteris, E. R.; Tagestad, J. D.; Downs, J. L.; Murray, C. J.

2015-07-01

Cost-effective and reliable vegetation monitoring methods are needed for applications ranging from traditional agronomic mapping, to verifying the safety of geologic injection activities. A particular challenge is defining baseline crop conditions and subsequent anomalies from long term imagery records (Landsat) in the face of large spatiotemporal variability. We develop a new method for defining baseline crop response (near peak growth) using the normalized difference vegetation index (NDVI) from 26 years (1986-2011) of Landsat data for 400 km2 surrounding a planned geologic carbon sequestration site near Jacksonville, Illinois. The normal score transform (yNDVI) was applied on a field by field basis to accentuate spatial patterns and level differences due to planting times. We tested crop type and soil moisture (Palmer crop moisture index (CMI)) as predictors of expected crop condition. Spatial patterns in yNDVI were similar between corn and soybeans - the two major crops. Linear regressions between yNDVI and the cumulative CMI (CCMI) exposed complex interactions between crop condition, field location (topography and soils), and annual moisture. Wet toposequence positions (depressions) were negatively correlated to CCMI and dry positions (crests) positively correlated. However, only 21% of the landscape showed a statistically significant (p < 0.05) linear relationship. To map anomalous crop conditions, we defined a tolerance interval based on yNDVI statistics. Tested on an independent image (2013), 63 of 1483 possible fields showed unusual crop condition. While the method is not directly suitable for crop health assessment, the spatial patterns in correlation between yNDVI and CCMI have potential applications for pest damage detection and edaphological soil mapping, especially in the developing world.

[Sap flow characteristics of Quercus liaotungensis in response to sapwood area and soil moisture in the loess hilly region, China].

PubMed

Lyu, Jin Lin; He, Qiu Yue; Yan, Mei Jie; Li, Guo Qing; Du, Sheng

2018-03-01

To examine the characteristics of sap flow in Quercus liaotungensis and their response to environmental factors under different soil moisture conditions, Granier-type thermal dissipation probes were used to measure xylem sap flow of trees with different sapwood area in a natural Q. liaotungensis forest in the loess hilly region. Solar radiation, air temperature, relative air humidity, precipitation, and soil moisture were monitored during the study period. The results showed that sap flux of Q. liaotungensis reached daily peaks earlier than solar radiation and vapor pressure deficit. The diurnal dynamics of sap flux showed a similar pattern to those of the environmental factors. Trees had larger sap flux during the period with higher soil moisture. Under the same soil moisture conditions, trees with larger diameter and sapwood areas had significantly higher sap flux than those with smaller diameter and sapwood areas. Sap flux could be fitted with vapor pressure deficit, solar radiation, and the integrated index of the two factors using exponential saturation function. Differences in the fitted curves and parameters suggested that sap flux tended to reach saturation faster under higher soil moisture. Furthermore, trees in the smaller diameter class were more sensitive to the changes of soil moisture. The ratio of daily sap flux per unit vapor pressure deficit under lower soil moisture condition to that under higher soil moisture condition was linearly correlated to sapwood area. The regressive slope in smaller diameter class was larger than that in bigger diameter class, which further indicated the higher sensitivity of trees with smaller diameter class to soil moisture. These results indicated that wider sapwood of larger diameter class provided a buffer against drought stress.

Evaluation of groundwater droughts in Austria

NASA Astrophysics Data System (ADS)

Haas, Johannes Christoph; Birk, Steffen

2015-04-01

Droughts are abnormally dry periods that affect various aspects of human life on earth, ranging from negative impacts on agriculture or industry, to being the cause for conflict and loss of human life. The changing climate reinforces the importance of investigations into this phenomenon. Various methods to analyze and classify droughts have been developed. These include drought indices such as the Standard Precipitation Index SPI, the Palmer Drought Severity Index PDSI or the Crop Moisture Index CMI. These and other indices consider meteorological parameters and/or their effects on soil moisture. A depletion of soil moisture triggered by low precipitation and high evapotranspiration may also cause reduced groundwater recharge and thus decreasing groundwater levels and reduced groundwater flow to springs, streams, and wetlands. However, the existing indices were generally not designed to address such drought effects on groundwater. Thus, a Standardized Groundwater level Index has recently been proposed by Bloomfied and Marchant (2013). Yet, to our knowledge, this approach has only been applied to consolidated aquifers in the UK. This work analyzes time series of groundwater levels from various, mostly unconsolidated aquifers in Austria in order to characterize the effects of droughts on aquifers in different hydrogeologic and climatic settings as well as under different usage scenarios. In particular, comparisons are made between the water rich Alpine parts of Austria, and the dryer parts situated in the East. The time series of groundwater levels are compared to other data, such as meteorological time series and written weather records about generally accepted phenomena, such as the 2003 European drought and heat wave. Thus, valuable insight is gained into the propagation of meteorological droughts through the soil and the aquifer in different types of hydrogeologic and climatic settings, which provides a prerequisite for the assessment of the aquifers' drought susceptibility in a changing climate. References: Bloomfield, J. P. & Marchant, B. P. Analysis of groundwater drought building on the standardised precipitation index approach Hydrology and Earth System Sciences, 2013, 17, 4769-4787

Multifrequency remote sensing of soil moisture. [Guymon, Oklahoma and Dalhart, Texas

NASA Technical Reports Server (NTRS)

Theis, S. W.; Mcfarland, M. J.; Rosenthal, W. D.; Jones, C. L. (Principal Investigator)

1982-01-01

Multifrequency sensor data collected at Guymon, Oklahoma and Dalhart, Texas using NASA's C-130 aircraft were used to determine which of the all-weather microwave sensors demonstrated the highest correlation to surface soil moisture over optimal bare soil conditions, and to develop and test techniques which use visible/infrared sensors to compensate for the vegetation effect in this sensor's response to soil moisture. The L-band passive microwave radiometer was found to be the most suitable single sensor system to estimate soil moisture over bare fields. In comparison to other active and passive microwave sensors the L-band radiometer (1) was influenced least by ranges in surface roughness; (2) demonstrated the most sensitivity to soil moisture differences in terms of the range of return from the full range of soil moisture; and (3) was less sensitive to errors in measurement in relation to the range of sensor response. L-band emissivity related more strongly to soil moisture when moisture was expressed as percent of field capacity. The perpendicular vegetation index as determined from the visible/infrared sensors was useful as a measure of the vegetation effect on the L-band radiometer response to soil moisture.

A multivariate analysis of biophysical parameters of tallgrass prairie among land management practices and years

USGS Publications Warehouse

Griffith, J.A.; Price, K.P.; Martinko, E.A.

2001-01-01

Six treatments of eastern Kansas tallgrass prairie - native prairie, hayed, mowed, grazed, burned and untreated - were studied to examine the biophysical effects of land management practices on grasslands. On each treatment, measurements of plant biomass, leaf area index, plant cover, leaf moisture and soil moisture were collected. In addition, measurements were taken of the Normalized Difference Vegetation Index (NDVI), which is derived from spectral reflectance measurements. Measurements were taken in mid-June, mid-July and late summer of 1990 and 1991. Multivariate analysis of variance was used to determine whether there were differences in the set of variables among treatments and years. Follow-up tests included univariate t-tests to determine which variables were contributing to any significant difference. Results showed a significant difference (p < 0.0005) among treatments in the composite of parameters during each of the months sampled. In most treatment types, there was a significant difference between years within each month. The univariate tests showed, however, that only some variables, primarily soil moisture, were contributing to this difference. We conclude that biomass and % plant cover show the best potential to serve as long-term indicators of grassland condition as they generally were sensitive to effects of different land management practices but not to yearly change in weather conditions. NDVI was insensitive to precipitation differences between years in July for most treatments, but was not in the native prairie. Choice of sampling time is important for these parameters to serve effectively as indicators.

An examination of the sensitivity of numerically simulated wildfires to low-level atmospheric stability and moisture, and the consequences for the Haines Index

Treesearch

Mary Ann Jenkins

2002-01-01

The Haines Index, an operational fire-weather index introduced in 1988 and based on the observed stability and moisture content of the near-surface atmosphere, has been a useful indicator of the potential for high-risk fires in low wind conditions and flat terrain. The Haines Index is of limited use, however, as a predictor of actual fire behavior. To develop a fire-...

A GIS-derived integrated moisture index to predict forest composition and productivity of Ohio forests (U.S.A.)

Treesearch

Louis R. Iverson; Martin E. Dale; Charles T. Scott; Anantha Prasad; Anantha Prasad

1997-01-01

A geographic information system (GIS) approach was used in conjunction with forest-plot data to develop an integrated moisture index (IMI), which was then used to predict forest productivity (site index) and species composition for forests in Ohio. In this region, typical of eastern hardwoods across the Midwest and southern Appalachians, topographic aspect and position...

Normalization of multidirectional red and NIR reflectances with the SAVI

NASA Technical Reports Server (NTRS)

Huete, A. R.; Hua, G.; Qi, J.; Chehbouni, A.; Van Leeuwen, W. J. D.

1992-01-01

Directional reflectance measurements were made over a semi-desert gramma grassland at various times of the growing season. View angle measurements from +40 to -40 degrees were made at various solar zenith angles and soil moisture conditions. The sensitivity of the Normalized Difference Vegetation Index (NDVI) and the Soil Adjusted Vegetation Index (SAVI) to bidirectional measurements was assessed for purposes of improving remote temporal monitoring of vegetation dynamics. The SAVI view angle response was found to be symmetric about nadir while the NDVI response was strongly anisotropic. This enabled the view angle behavior of the SAVI to be normalized with a cosine function. In contrast to the NDVI, the SAVI was able to minimize soil moisture and shadow influences for all measurement conditions.

Multiscaling of vegetative indexes from remote sensing images obtained at different spatial resolutions

NASA Astrophysics Data System (ADS)

Alonso, Carmelo; Tarquis, Ana M.; Zuñiga, Ignacio; Benito, Rosa M.

2017-04-01

Vegetation indexes, such as Normalized Difference Vegetation Index (NDVI) and enhanced Vegetation index (EVI), can been used to estimate root zone soil moisture through high resolution remote sensing images. These indexes are based in red (R), near infrared (NIR) and blue (B) wavelengths data. In this work we have studied the scaling properties of both vegetation indexes analyzing the information contained in two satellite data: Landsat-7 and Ikonos. Because of the potential capacity for systematic observations at various scales, remote sensing technology extends possible data archives from present time to over several decades back. For this advantage, enormous efforts have been made by researchers and application specialists to delineate vegetation indexes from local scale to global scale by applying remote sensing imagery. To study the influence of the spatial resolution the vegetation indexes map estimated with Ikonos-2 coded in 8 bits, with a resolution of 4m, have been compared through a multifractal analysis with the ones obtained with Lansat-7 8 bits, of 30 m. resolution, on the same area of study. The scaling behaviour of NDVI and EVI presents several differences that will be discussed based on the multifractal parameters extracted from the analysis. REFERENCES Alonso, C., Tarquis, A. M., Benito, R. M. and Zuñiga, I. Correlation scaling properties between soil moisture and vegetation indices. Geophysical Research Abstracts, 11, EGU2009-13932, 2009. Alonso, C., Tarquis, A. M. and Benito, R. M. Comparison of fractal dimensions based on segmented NDVI fields obtained from different remote sensors. Geophysical Research Abstracts, 14, EGU2012-14342, 2012. Escribano Rodriguez, J., Alonso, C., Tarquis, A.M., Benito, R.M. and Hernandez Diaz-Ambrona, C. Comparison of NDVI fields obtained from different remote sensors. Geophysical Research Abstracts,15, EGU2013-14153, 2013. Lovejoy, S., Tarquis, A., Gaonac'h, H. and Schertzer, D. Single and multiscale remote sensing techniques, multifractals and MODIS derived vegetation and soil moisture, Vadose Zone J., 7, 533-546, 2008. Renosh, P. R., Schmitt, F. G., and Loisel, H.: Scaling analysis of ocean surface turbulent heterogeneities from satellite remote sensing: use of 2D structure functions. PLoS ONE, 10, e0126975, 2015. Tarquis, A.M., Platonov, A., Matulka, A., Grau, J., Sekula, E., Diez, M. and Redondo J. M. Application of multifractal analysis to the study of SAR features and oil spills on the ocean surface. Nonlin. Processes Geophys., 21, 439-450, 2014.

The effect of moisture on the release and enrichment of heavy metals during pyrolysis of municipal solid waste.

PubMed

Raclavská, Helena; Corsaro, Agnieszka; Hlavsová, Adéla; Juchelková, Dagmar; Zajonc, Ondřej

2015-03-01

The investigation of the effect of moisture on the release and enrichment of heavy metals during pyrolysis of municipal solid waste is essential. This is important owing to: (i) the increasing amount of metals in the solid product of pyrolysis beyond the normalised level; (ii) the effect of moisture on the overall cost of pyrolysis process; and (iii) the utilisation of pyrolysis products. Seven metals were selected for evaluation: arsenic, cadmium, chromium, mercury, nickel, lead, and vanadium. Pyrolysis experiments were conducted in a steel retort at 650 °C. The municipal solid waste samples with moisture contents of 0, 30, and 65 wt% were investigated. The relative enrichment index and release of heavy metals were evaluated individually for liquid and solid fractions. A consistent trend was observed for the majority of metals investigated. Reductions of relative enrichment index and release, i.e. an increase of volatility, were observed for arsenic, chromium, cadmium, nickel, and vanadium, with an increase of municipal solid waste moisture. Whereas divergent results were obtained for lead and mercury. The effect of moisture on the relative enrichment index and release was greater at 65 wt% moisture than at 30 wt% for lead, and more remarkable at 30 wt% than at 65 wt% for mercury. © The Author(s) 2015.

Treatment with a barrier-strengthening moisturizer prevents relapse of hand-eczema. An open, randomized, prospective, parallel group study.

PubMed

Lodén, Marie; Wirén, Karin; Smerud, Knut; Meland, Nils; Hønnås, Helge; Mørk, Gro; Lützow-Holm, Claus; Funk, Jörgen; Meding, Birgitta

2010-11-01

Hand eczema influences the quality of life. Management strategies include the use of moisturizers. In the present study the time to relapse of eczema during treatment with a barrier-strengthening moisturizer (5% urea) was compared with no treatment (no medical or non-medicated preparations) in 53 randomized patients with successfully treated hand eczema. The median time to relapse was 20 days in the moisturizer group compared with 2 days in the no treatment group (p = 0.04). Eczema relapsed in 90% of the patients within 26 weeks. No difference in severity was noted between the groups at relapse. Dermatology Life Quality Index (DLQI) increased significantly in both groups; from 4.7 to 7.1 in the moisturizer group and from 4.1 to 7.8 in the no treatment group (p < 0.01) at the time of relapse. Hence, the application of moisturizers seems to prolong the disease-free interval in patients with controlled hand eczema. Whether the data is applic-able to moisturizers without barrier-strengthening properties remains to be elucidated.

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.

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.

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.

Microwave remote sensing of soil moisture, volume 1. [Guymon, Oklahoma and Dalhart, Texas

NASA Technical Reports Server (NTRS)

Mcfarland, M. J. (Principal Investigator); Theis, S. W.; Rosenthal, W. D.; Jones, C. L.

1982-01-01

Multifrequency sensor data from NASA's C-130 aircraft were used to determine which of the all weather microwave sensors demonstrated the highest correlation to surface soil moisture over optimal bare soil conditions, and to develop and test techniques which use visible/infrared sensors to compensate for the vegetation effect in this sensor's response to soil moisture. The L-band passive microwave radiometer was found to be the most suitable single sensor system to estimate soil moisture over bare fields. The perpendicular vegetation index (PVI) as determined from the visible/infrared sensors was useful as a measure of the vegetation effect on the L-band radiometer response to soil moisture. A linear equation was developed to estimate percent field capacity as a function of L-band emissivity and the vegetation index. The prediction algorithm improves the estimation of moisture significantly over predictions from L-band emissivity alone.

Effects of extrusion variables on the properties of waxy hulless barley extrudates.

PubMed

Köksel, Hamit; Ryu, Gy-Hyung; Başman, Arzu; Demiralp, Hande; Ng, Perry K W

2004-02-01

The objective of this research was to investigate the extrudability of waxy hulless barley flour under various extrusion conditions. Waxy hulless barley flour was processed in a laboratory-scale corotating twin-screw extruder with different levels of feed moisture content (22.3, 26.8, and 30.7%) and die temperature (130, 150, and 170 degrees C) to develop a snack food with high beta-glucan content. The effects of extrusion condition variables (screw configuration, moisture, and temperature) on the system variables (pressure and specific mechanical energy), the extrudate physical properties (sectional expansion index, bulk density), starch gelatinization, pasting properties (cold peak viscosity, trough viscosity, and final viscosity), and beta-glucan contents were determined. Results were evaluated by using response surface methodology. Increased extrusion temperature and feed moisture content resulted in decreases in exit die pressure and specific mechanical energy values. For extrudates extruded under low shear screw configuration (LS), increased barrel temperature decreased sectional expansion index (SEI) values at both low and high moisture contents. The feed moisture seems to have an inverse relationship with SEI over the range studied. Bulk density was higher at higher moisture contents, for both low and high barrel temperatures, for samples extruded under high shear screw configuration (HS) and LS. Cold peak viscosities (CV) were observed in all samples. The CV increased with the increase in extrusion temperature and feed moisture content. Although beta-glucan contents of the LS extrudates were comparable to that of barley flour sample, HS samples had generally lower beta-glucan contents. The extrusion cooking technique seems to be promising for the production of snack foods with high beta-glucan content, especially using LS conditions.

Studies and Application of Remote Sensing Retrieval Method of Soil Moisture Content in Land Parcel Units in Irrigation Area

NASA Astrophysics Data System (ADS)

Zhu, H.; Zhao, H. L.; Jiang, Y. Z.; Zang, W. B.

2018-05-01

Soil moisture is one of the important hydrological elements. Obtaining soil moisture accurately and effectively is of great significance for water resource management in irrigation area. During the process of soil moisture content retrieval with multiremote sensing data, multi- remote sensing data always brings multi-spatial scale problems which results in inconformity of soil moisture content retrieved by remote sensing in different spatial scale. In addition, agricultural water use management has suitable spatial scale of soil moisture information so as to satisfy the demands of dynamic management of water use and water demand in certain unit. We have proposed to use land parcel unit as the minimum unit to do soil moisture content research in agricultural water using area, according to soil characteristics, vegetation coverage characteristics in underlying layer, and hydrological characteristic into the basis of study unit division. We have proposed division method of land parcel units. Based on multi thermal infrared and near infrared remote sensing data, we calculate the ndvi and tvdi index and make a statistical model between the tvdi index and soil moisture of ground monitoring station. Then we move forward to study soil moisture remote sensing retrieval method on land parcel unit scale. And the method has been applied in Hetao irrigation area. Results show that compared with pixel scale the soil moisture content in land parcel unit scale has displayed stronger correlation with true value. Hence, remote sensing retrieval method of soil moisture content in land parcel unit scale has shown good applicability in Hetao irrigation area. We converted the research unit into the scale of land parcel unit. Using the land parcel units with unified crops and soil attributes as the research units more complies with the characteristics of agricultural water areas, avoids the problems such as decomposition of mixed pixels and excessive dependence on high-resolution data caused by the research units of pixels, and doesn't involve compromises in the spatial scale and simulating precision like the grid simulation. When the application needs are met, the production efficiency of products can also be improved at a certain degree.

Assessment of the capability of remote sensing and GIS techniques for monitoring reclamation success in coal mine degraded lands.

PubMed

Karan, Shivesh Kishore; Samadder, Sukha Ranjan; Maiti, Subodh Kumar

2016-11-01

The objective of the present study is to monitor reclamation activity in mining areas. Monitoring of these reclaimed sites in the vicinity of mining areas and on closed Over Burden (OB) dumps is critical for improving the overall environmental condition, especially in developing countries where area around the mines are densely populated. The present study evaluated the reclamation success in the Block II area of Jharia coal field, India, using Landsat satellite images for the years 2000 and 2015. Four image processing methods (support vector machine, ratio vegetation index, enhanced vegetation index, and normalized difference vegetation index) were used to quantify the change in vegetation cover between the years 2000 and 2015. The study also evaluated the relationship between vegetation health and moisture content of the study area using remote sensing techniques. Statistical linear regression analysis revealed that Normalized Difference Vegetation Index (NDVI) coupled with Normalized Difference Moisture Index (NDMI) is the best method for vegetation monitoring in the study area when compared to other indices. A strong linear relationship (r(2) > 0.86) was found between NDVI and NDMI. An increase of 21% from 213.88 ha in 2000 to 258.9 ha in 2015 was observed in the vegetation cover of the reclaimed sites for an open cast mine, indicating satisfactory reclamation activity. NDVI results indicated that vegetation health also improved over the years. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

School attendance and daily respiratory symptoms in children: influence of moisture damage.

PubMed

Casas, L; Espinosa, A; Pekkanen, J; Asikainen, A; Borràs-Santos, A; Jacobs, J; Krop, E J M; Täubel, M; Hyvärinen, A; Heederik, D; Zock, J-P

2017-03-01

We investigated the effect of weekends and school holidays on the daily frequency and severity of respiratory and other symptoms among children attending schools with (index) or without (reference) moisture damage in Spain, the Netherlands, and Finland. Throughout 1 year, parents of 419 children with a respiratory condition attending index (n=15) or reference (n=10) primary schools completed three symptom diaries. We assessed associations between lower respiratory tract, upper respiratory tract or allergy, and other symptom scores and school day, weekend, or summer holiday using mixed regression models stratified by country and moisture damage. We evaluated interactions between moisture damage and type of day. We combined country-specific estimates (incidence rate ratios [IRRs] and 95% confidence interval [CI]) in meta-analyses. Symptom scores were lower during weekends and holiday. Lower respiratory tract symptoms were statistically significantly less common during holiday with strongest effect in index schools (IRR=0.7; CI=0.6-0.8). Reporting of other symptoms was more reduced during holiday in index (IRR=0.6; CI=0.4-0.9) than in reference (IRR=0.95; CI=0.8-1.2) schools (interaction P<.01). In conclusion, symptoms were less frequent and/or severe during summer holiday and weekends. This pattern was stronger among children attending moisture-damaged schools, suggesting potential improvement in moisture damage-related symptoms during school breaks. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Effects of selected process parameters in extrusion of yam flour (Dioscorea rotundata) on physicochemical properties of the extrudates.

PubMed

Sebio, L; Chang, Y K

2000-04-01

Raw yam (Dioscorea rotundata) flour was cooked and extruded in a Brabender single-screw laboratory scale extruder. Response surface methodology using an incomplete factorial design was applied with various combinations of barrel temperature [100, 125, 150 degrees C], feed moisture content [18, 22, 26%] and screw speed [100, 150, 200 rpm]. Initial viscosity at 30 degrees C, water solubility index, expansion and hardness were determined. The highest values of initial viscosity were at the highest barrel temperatures and the highest moisture contents. At high feed moisture content and high barrel temperatures the yam extrudate flour showed the greatest values of water solubility index. The physical properties of the extruded product showed that at high temperature the lower the moisture content the greater the expansion index. Hardness was influenced directly by moisture content and inversely by extrusion temperature. The extrusion of yam flour led to the production of snacks and pre-gelatinized flours of diverse properties. Also extruded yam flour can be successfully used in the preparation of 'futu' (pre-cooked compact dough), a yam-based food, popular in Western Africa.

Hydrological modelling of the Mara River Basin, Kenya: Application of the Normalised Difference Infrared Index (NDII)

NASA Astrophysics Data System (ADS)

Hulsman, Petra; Savenije, Hubert; Bogaard, Thom

2017-04-01

In hydrology and water resources management, precipitation and discharge are the main time series for hydrological modelling. However, in African river catchments, the quantity and quality of the available precipitation stations and discharge measurements are unfortunately often inadequate for reliable hydrological modelling. To cope with these uncertainties, this study proposes to calibrate on water levels and to constrain the model using the Normalised Difference Infrared Index (NDII) as a proxy for root zone moisture stress. With the NDII, the leaf water content can be monitored. Previous studies related the NDII to the equivalent water thickness (EWT) of leaves, which is used to determine the vegetation water content (VWC). As the water content in the leaves is related to the water content in the root zone, the NDII can also be used as indicator of the soil moisture content in the root zone. In previous studies it was found that the root zone moisture content is exponentially correlated to the NDII during periods of moisture stress. In this study, the semi-distributed rainfall runoff model FLEX-Topo has been applied to the Mara River Basin. In this model seven sub-basins are distinguished and four hydrological response units with each a unique model structure based on the expected dominant flow processes. To calibrate the model, the water levels have been back-calculated from modelled discharges, using cross-section data and the Strickler formula calibrating parameter 'k•s1/2', and compared to measured water levels. In addition, the correlation between the NDII and root zone moisture content has been analysed for this river basin for each sub-catchment and hydrological response unit. Also, the application of the NDII as model constraint or for calibration has been analysed.

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

NASA Astrophysics Data System (ADS)

Laiolo, Paola; Gabellani, Simone; Rudari, Roberto; Boni, Giorgio; Puca, Silvia

2013-04-01

Soil moisture plays a fundamental role in the partitioning of mass and energy fluxes between land surface and atmosphere, thereby influencing climate and weather, and it is important in determining the rainfall-runoff response of catchments; moreover, in hydrological modelling and flood forecasting, a correct definition of moisture conditions is a key factor for accurate predictions. Different sources of information for the estimation of the soil moisture state are currently available: satellite data, point measurements and model predictions. All are affected by intrinsic uncertainty. Among different satellite sensors that can be used for soil moisture estimation three major groups can be distinguished: passive microwave sensors (e.g., SSMI), active sensors (e.g. SAR, Scatterometers), and optical sensors (e.g. Spectroradiometers). The last two families, mainly because of their temporal and spatial resolution seem the most suitable for hydrological applications In this work soil moisture point measurements from 10 sensors in the Italian territory are compared of with the satellite products both from the HSAF project SM-OBS-2, derived from the ASCAT scatterometer, and from ACHAB, an operative energy balance model that assimilate LST data derived from MSG and furnishes daily an evaporative fraction index related to soil moisture content for all the Italian region. Distributed comparison of the ACHAB and SM-OBS-2 on the whole Italian territory are performed too.

Toxicity of airborne dust as an indicator of moisture problems in school buildings.

PubMed

Tirkkonen, Jenni; Täubel, Martin; Leppänen, Hanna; Peltonen, Matti; Lindsley, William; Chen, Bean T; Hyvärinen, Anne; Hirvonen, Maija-Riitta; Huttunen, Kati

2017-02-01

Moisture-damaged indoor environments are thought to increase the toxicity of indoor air particulate matter (PM), indicating that a toxicological assay could be used as a method for recognizing buildings with indoor air problems. We aimed to test if our approach of analyzing the toxicity of actively collected indoor air PM in vitro differentiates moisture-damaged from non-damaged school buildings. We collected active air samples with NIOSH Bioaerosol Cyclone Samplers from moisture-damaged (index) and non-damaged (reference) school buildings (4 + 4). The teachers and pupils of the schools were administered a symptom questionnaire. Five samples of two size fractions [Stage 1 (>1.9 μm) and Stage 2 (1-1.9 μm)] were collected from each school. Mouse RAW264.7 macrophages were exposed to the collected PM for 24 h and subsequently analyzed for changes in cell metabolic activity, production of nitric oxide (NO), tumor necrosis factor (TNF)-α and interleukin (IL)-6. The teachers working in the moisture-damaged schools reported respiratory symptoms such as cough (p = 0.01) and shortness of breath (p = 0.01) more often than teachers from reference schools. Toxicity of the PM sample as such did not differentiate index from reference building,s but the toxicity adjusted for the amount of the particles tended to be higher in moisture-damaged schools. Further development of the method will require identification of other confounding factors in addition to the necessity to adjust for differences in particle counts between samples.

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).

Performing drought indices to identify the relationship between agricultural losses and drought events in Spain.

NASA Astrophysics Data System (ADS)

Peña Gallardo, Marina; Serrano, Sergio Martín Vicente; Portugués Santiago, Beguería; Burguera Miquel, Tomás

2017-04-01

Drought leads to crop failures reducing the productivity. For this reason, the need of appropriate tool for recognize dry periods and evaluate the impact of drought on crop production is important. In this study, we provide an assessment of the relationship between drought episodes and crop failures in Spain as one of the direct consequences of drought is the diminishing of crop yields. First, different drought indices [the Standardized Precipitation and Evapotranspiration Index (SPEI); the Standardized Precipitation Index (SPI); the self-calibrated Palmer Moisture Anomaly Index (Z-Index), the self-calibrated Crop Moisture Index (CMI) and the Standardized Palmer Drought Index (SPDI)] have been calculated at different time scales in order to identify the dry events occurred in Spain and determine the duration and intensity of each event. Second, the drought episodes have been correlated with crop production estimated and final crop production data provided by the Spanish Crop Insurance System for the available period from 1995 to 2014 at the municipal spatial scale, with the purpose of knowing if the characteristics of the drought episodes are reflected on the agricultural losses. The analysis has been carried out in particular for two types of crop, wheat and barley. The results indicate the existence of an agreement between the most important drought events in Spain and the response of the crop productions and the proportion of hectare insurance. Nevertheless, this agreement vary depending on the drought index applied. Authors found a higher competence of the drought indices calculated at different time scales (SPEI, SPI and SPDI) identifying the begging and end of the drought events and the correspondence with the crop failures.

Physical and functional properties of arrowroot starch extrudates.

PubMed

Jyothi, A N; Sheriff, J T; Sajeev, M S

2009-03-01

Arrowroot starch, a commercially underexploited tuber starch but having potential digestive and medicinal properties, has been subjected to extrusion cooking using a single screw food extruder. Different levels of feed moisture (12%, 14%, and 16%) and extrusion temperatures (140, 150, 160, 170, 180, and 190 degrees C) were used for extrusion. The physical properties--bulk density, true density, porosity, and expansion ratio; functional properties such as water absorption index, water solubility index, oil absorption index, pasting, rheological, and textural properties; and in vitro enzyme digestibility of the extrudates were determined. The expansion ratio of the extrudates ranged from 3.22 to 6.09. The water absorption index (6.52 to 8.85 g gel/g dry sample), water solubility index (15.92% to 41.31%), and oil absorption index (0.50 to 1.70 g/g) were higher for the extrudates in comparison to native starch (1.81 g gel/g dry sample, 1.16% and 0.60 g/g, respectively). The rheological properties, storage modulus, and loss modulus of the gelatinized powdered extrudates were significantly lower (P < 0.05) and these behaved like solutions rather than a paste or a gel. Hardness and toughness were more for the samples extruded at higher feed moisture and lower extrusion temperature, whereas snap force and energy were higher at lower feed moisture and temperature. There was a significant decrease in the percentage digestibility of arrowroot starch (30.07% after 30 min of incubation with the enzyme) after extrusion (25.27% to 30.56%). Extrusion cooking of arrowroot starch resulted in products with very good expansion, color, and lower digestibility, which can be exploited for its potential use as a snack food.

Evaluation of Radar Vegetation Indices for Vegetation Water Content Estimation Using Data from a Ground-Based SMAP Simulator

NASA Technical Reports Server (NTRS)

Srivastava, Prashant K.; O'Neill, Peggy; Cosh, Michael; Lang, Roger; Joseph, Alicia

2015-01-01

Vegetation water content (VWC) is an important component of microwave soil moisture retrieval algorithms. This paper aims to estimate VWC using L band active and passive radar/radiometer datasets obtained from a NASA ground-based Soil Moisture Active Passive (SMAP) simulator known as ComRAD (Combined Radar/Radiometer). Several approaches to derive vegetation information from radar and radiometer data such as HH, HV, VV, Microwave Polarization Difference Index (MPDI), HH/VV ratio, HV/(HH+VV), HV/(HH+HV+VV) and Radar Vegetation Index (RVI) are tested for VWC estimation through a generalized linear model (GLM). The overall analysis indicates that HV radar backscattering could be used for VWC content estimation with highest performance followed by HH, VV, MPDI, RVI, and other ratios.

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.

Fabrication of a Quartz-Crystal-Microbalance/Surface-Plasmon-Resonance Hybrid Sensor and Its Use for Detection of Polymer Thin-Film Deposition and Evaluation of Moisture Sorption Phenomena

NASA Astrophysics Data System (ADS)

Shinbo, Kazunari; Ishikawa, Hiroshi; Baba, Akira; Ohdaira, Yasuo; Kato, Keizo; Kaneko, Futao

2012-03-01

We fabricated a hybrid sensor utilizing quartz crystal microbalance (QCM) and surface plasmon resonance (SPR) spectroscopy. We confirmed its effectiveness by observing QCM frequency shifts and SPR wavelength changes for two processes: deposition of various transparent polymer thin films and moisture sorption. For thin-film deposition, the relationship between the QCM frequency and SPR wavelength was found to depend on the refractive index of the film material. For moisture sorption, the direction of SPR wavelength shift depended on the film thickness. This was estimated to be caused by film swelling and decrease in refractive index induced by moisture.

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.

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Downscaling SMAP Soil Moisture Using Geoinformation Data and Geostatistics

NASA Astrophysics Data System (ADS)

Xu, Y.; Wang, L.

2017-12-01

Soil moisture is important for agricultural and hydrological studies. However, ground truth soil moisture data for wide area is difficult to achieve. Microwave remote sensing such as Soil Moisture Active Passive (SMAP) can offer a solution for wide coverage. However, existing global soil moisture products only provide observations at coarse spatial resolutions, which often limit their applications in regional agricultural and hydrological studies. This paper therefore aims to generate fine scale soil moisture information and extend soil moisture spatial availability. A statistical downscaling scheme is presented that incorporates multiple fine scale geoinformation data into the downscaling of coarse scale SMAP data in the absence of ground measurement data. Geoinformation data related to soil moisture patterns including digital elevation model (DEM), land surface temperature (LST), land use and normalized difference vegetation index (NDVI) at a fine scale are used as auxiliary environmental variables for downscaling SMAP data. Generalized additive model (GAM) and regression tree are first conducted to derive statistical relationships between SMAP data and auxiliary geoinformation data at an original coarse scale, and residuals are then downscaled to a finer scale via area-to-point kriging (ATPK) by accounting for the spatial correlation information of the input residuals. The results from standard validation scores as well as the triple collocation (TC) method against soil moisture in-situ measurements show that the downscaling method can significantly improve the spatial details of SMAP soil moisture while maintain the accuracy.

Sensitivity of soil moisture initialization for decadal predictions under different regional climatic conditions in Europe

NASA Astrophysics Data System (ADS)

Khodayar, S.; Sehlinger, A.; Feldmann, H.; Kottmeier, C.

2015-12-01

The impact of soil initialization is investigated through perturbation simulations with the regional climate model COSMO-CLM. The focus of the investigation is to assess the sensitivity of simulated extreme periods, dry and wet, to soil moisture initialization in different climatic regions over Europe and to establish the necessary spin up time within the framework of decadal predictions for these regions. Sensitivity experiments consisted of a reference simulation from 1968 to 1999 and 5 simulations from 1972 to 1983. The Effective Drought Index (EDI) is used to select and quantify drought status in the reference run to establish the simulation time period for the sensitivity experiments. Different soil initialization procedures are investigated. The sensitivity of the decadal predictions to soil moisture initial conditions is investigated through the analysis of water cycle components' (WCC) variability. In an episodic time scale the local effects of soil moisture on the boundary-layer and the propagated effects on the large-scale dynamics are analysed. The results show: (a) COSMO-CLM reproduces the observed features of the drought index. (b) Soil moisture initialization exerts a relevant impact on WCC, e.g., precipitation distribution and intensity. (c) Regional characteristics strongly impact the response of the WCC. Precipitation and evapotranspiration deviations are larger for humid regions. (d) The initial soil conditions (wet/dry), the regional characteristics (humid/dry) and the annual period (wet/dry) play a key role in the time that soil needs to restore quasi-equilibrium and the impact on the atmospheric conditions. Humid areas, and for all regions, a humid initialization, exhibit shorter spin up times, also soil reacts more sensitive when initialised during dry periods. (e) The initial soil perturbation may markedly modify atmospheric pressure field, wind circulation systems and atmospheric water vapour distribution affecting atmospheric stability conditions, thus modifying precipitation intensity and distribution even several years after the initialization.

An Evaluation of Drought Indices in Different Climatic Regions

NASA Astrophysics Data System (ADS)

Shahabfar, A.; Eitzinger, J.

2009-04-01

Drought has become a recurrent phenomenon in Iran in the last few decades. Significant drought conditions were observed during years of late 2000s and the trend continued up to now. The country's agricultural sector and water resources have been under severe constraints from the recurrent droughts. In this study, spatial and temporal dimensions of meteorological droughts in Iran have been investigated from vulnerability concept. The Standardized Precipitation Index (SPI) was developed to detect drought and wet periods at different time scales, an important characteristic that is not accomplished with typical drought indices. More and more users employ the SPI to monitor droughts. Although calculation of the SPI is easier than other drought indices, such as the Palmer Drought Index, it is still relatively complex. Two indices called the China-Z Index (CZI) and Modified China-Z Index (CZI) have been used by many scientists to monitor moisture conditions across their country or their case study area. The calculations of these indices are easier than the SPI. Another indices, the statistical Z-Score and percent of normal (PN), can also be used to monitor droughts. This paper evaluates the SPI, CZI, MCZI, Z-Score and PN on 1-, 3-, 6-, 9- and 12-month time scales using monthly precipitation totals for six climatic regions in Iran from January 2000 to December 2005 as a sever dry period and representing six climatic regions include: mountain, semi mountain, desert, semi-desert, coastal desert and coastal wet. Advantages and disadvantages for the application of each index are compared. Study results indicate that the CZI, MCZI, Z-Score and PN can provide results similar to the SPI for all time scales, and that the calculations of these indices are relatively easy compared with the SPI, possibly offering better tools to monitor moisture conditions. KEY WORDS: drought monitoring, drought indices, soil moisture, climatic regions.

The Effect of Vegetation on Soil Water Infiltration and Retention Capacity by Improving Soil Physiochemical Property in Semi-arid Grassland

NASA Astrophysics Data System (ADS)

A, Y.; Wang, G.

2017-12-01

Water shortage is the main limiting factor for semi-arid grassland development. However, the grassland are gradually degraded represented by species conversion, biomass decrease and ecosystem structure simplification under the influence of human activity. Soil water characteristics such as moisture, infiltration and conductivity are critical variables affecting the interactions between soil parameters and vegetation. In this study, Cover, Height, Shannon-Wiener diversity index, Pielou evenness index and Richness index are served as indexes of vegetation productivity and community structure. And saturated hydraulic conductivity (Ks) and soil moisture content are served as indexes of soil water characters. The interaction between vegetation and soil water is investigated through other soil parameters, such as soil organic matter content at different vertical depths and in different degradation area (e.g., initial, transition and degraded plots). The results show that Ks significantly controlled by soil texture other than soil organic matter content. So the influence of vegetation on Ks through increasing soil organic content (SOM) might be slight. However, soil moisture content (SMC) appeared significantly positive relationship with SOM and silt content and negative relationship with sand content at all depth, significantly. This indicated that capacity of soil water storage was influenced both by soil texture and organic matter. In addition, the highest correlation coefficient of SMC was with SOM at the sub-surficial soil layer (20 40 cm). At the depth of 20 40 cm, the soil water content was relatively steady which slightly influenced by precipitation and evaporation. But it significantly influenced by soil organic matter content which related to vegetation. The correlation coefficient between SOM and SMC at topsoil layer (0 20 cm) was lowest (R2=0.36, p<0.01), which indicated the influence of vegetation on soil water content not only by soil organic matter content but also the other influential factors, such as the root water uptake, precipitation and evaporation.

Natural variability of the Keetch-Byram Drought Index in the Hawaiian Islands

Treesearch

Klaus Dolling; Pao-Shin Chu; Francis Fujioka

2009-01-01

The Hawaiian Islands experience damaging wildfires on a yearly basis. Soil moisture or lack thereof influences the amount and flammability of vegetation. Incorporating daily maximum temperatures and daily rainfall amounts, the Keetch–Byram Drought Index (KBDI) estimates the amount of soil moisture by tracking daily maximum temperatures and rainfall. A previous study...

Assimilating remote sensing observations of leaf area index and soil moisture for wheat yield estimates: An observing system simulation experiment

USDA-ARS?s Scientific Manuscript database

We develop a robust understanding of the effects of assimilating remote sensing observations of leaf area index and soil moisture (in the top 5 cm) on DSSAT-CSM CropSim-Ceres wheat yield estimates. Synthetic observing system simulation experiments compare the abilities of the Ensemble Kalman Filter...

Effects of some extrusion variables on physicochemical characteristics of extruded corn starch-passion fruit pulp (Passiflora edulis) snacks.

PubMed

Cortés, R Nallely Falfán; Guzmán, Iñigo Verdalet; Martínez-Bustos, Fernando

2014-12-01

The aim of this work was to study the effect of the addition of passion fruit pulp (PFP: 0-7%), the variation of barrel temperature in the third zone extruder (BT: 80-140 °C) and feed moisture (FM:16-30%) in a blend of corn starch and passion fruit pulp on different physicochemical characteristics of directly expanded snacks by extrusion technology. Single-screw laboratory extruder and a central, composite, rotatable experimental design were used. Expansion index of extrudates ranged between 1.0 and 1.8. Decreasing of feed moisture (18%), passion fruit pulp concentration (1.42%) and the increasing of barrel temperature (127 °C) resulted in higher expansion index. The increasing of feed moisture and passion fruit pulp concentration resulted in higher penetration force values of extrudates. The passion fruit pulp concentration showed a highly significant effect (p ≤ 0.01) on the L *, a * and b * parameters. Passion fruit pulp has a reasonable source of β-carotene, proteins and dietary fibers that can be added to expanded snacks.

Radiative transfer in shrub savanna sites in Niger: Preliminary results from HAPEX-Sahel. Part 3: Optical dynamics and vegetation index sensitivity to biomass and plant cover

NASA Technical Reports Server (NTRS)

vanLeeuwen, W. J. D.; Huete, A. R.; Duncan, J.; Franklin, J.

1994-01-01

A shrub savannah landscape in Niger was optically characterized utilizing blue, green, red and near-infrared wavelengths. Selected vegetation indices were evaluated for their performance and sensitivity to describe the complex Sahelian soil/vegetation canopies. Bidirectional reflectance factors (BRF) of plants and soils were measured at several view angles, and used as input to various vegetation indices. Both soil and vegetation targets had strong anisotropic reflectance properties, rendering all vegetation index (6) responses to be a direct function of sun and view geometry. Soil background influences were shown to alter the response of most vegetation indices. N-space greenness had the smallest dynamic range in VI response, but the n-space brightness index provided additional useful information. The global environmental monitoring index (GEMI) showed a large 6 dynamic range for bare soils, which was undesirable for a vegetation index. The view angle response of the normalized difference vegetation index (NDVI), atmosphere resistant vegetation index (ARVI) and soil atmosphere resistant vegetation index (SARVI) were asymmetric about nadir for multiple view angles, and were, except for the SARVI, altered seriously by soil moisture and/or soil brightness effects. The soil adjusted vegetation index (SAVI) was least affected by surface soil moisture and was symmetric about nadir for grass vegetation covers. Overall the SAVI, SARVI and the n-space vegetation index performed best under all adverse conditions and were recommended to monitor vegetation growth in the sparsely vegetated Sahelian zone.

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.

Influence of hydrologic modifications on Fraxinus pennsylvanica in the Mississippi River Alluvial Valley, USA

USGS Publications Warehouse

Gee, Hugo K.W.; King, Sammy L.; Keim, Richard F.

2015-01-01

We used tree-ring analysis to examine radial growth response of a common, moderately flood-tolerant species (Fraxinus pennsylvanica Marshall) to hydrologic and climatic variability for > 40 years before and after hydrologic modifications affecting two forest stands in the Mississippi River Alluvial Valley (USA): a stand without levees below dams and a stand within a ring levee. At the stand without levees below dams, spring flood stages decreased and overall growth increased after dam construction, which we attribute to a reduction in flood stress. At the stand within a ring levee, growth responded to the elimination of overbank flooding by shifting from being positively correlated with river stage to not being correlated with river stage. In general, growth in swales was positively correlated with river stage and Palmer Drought Severity Index (an index of soil moisture) for longer periods than flats. Growth decreased after levee construction, but swales were less impacted than flats likely because of differences in elevation and soils provide higher soil moisture. Results of this study indicate that broad-scale hydrologic processes differ in their effects on the flood regime, and the effects on growth of moderately flood-tolerant species such as F. pennsylvanica can be mediated by local-scale factors such as topographic position, which affects soil moisture.

How Does Drought Change With Climate Change

NASA Astrophysics Data System (ADS)

Trenberth, K. E.

2014-12-01

Large disparities among published studies have led to considerable confusion over the question of how drought is changing and how it is expected to change with global warming. As a result the IPCC AR5 assessment has watered down statements, and failed to carry out an adequate assessment of the sources of the discrepancies. Quite aside from the different definitions of drought related to meteorological (absence of precipitation), hydrological (lack of water in lakes and rivers), and agricultural (lack of soil moisture) drought, there are many indices that measure drought. Good homogeneous datasets are essential to assess changes over time, but are often not available. Simpler indices may miss effects of certain physical processes, such as evapotranspiration (ET). The Palmer Drought Severity Index (PDSI) has been much maligned but has considerable merit because it can accommodate different ET formulations (e.g., Thornthwaite vs Penman-Monteith), it can be self calibrating to accommodate different regions, and it carries out a crude moisture balance. This is in contrast to simpler indices, such as the Standardized Precipitation Index, which provides only a measure of moisture supply, or the Standardized Precipitation Evapotranspiration Index, which also includes potential (but not actual) ET. The largest source of drought variations is ENSO: during La Niña more rain falls on land while during El Niño most precipitation is over the Pacific Ocean, exposing more land to drought conditions. It is essential to account for interannual and inter-decadal variability in assessing changes in drought with climate change. Yet drought is one time on land when effects accumulate, with huge consequences for wild fire risk. It is important to ask the right questions in dealing with drought.

Climate Prediction Center - United States Drought Information

Science.gov Websites

• Crop Moisture Indices • Soil Moisture Percentiles (based on NLDAS) • Standardized Runoff Index (based /Minimum • Mean Surface Hydrology (based on NLDAS) • Total Soil Moisture • Total SM Change • MOSAIC Soil Moisture Profile • NOAH Soil Moisture Profile • NOAH Soil T Profile • Evaporation • E-P Â

Benefit of Modeling the Observation Error in a Data Assimilation Framework Using Vegetation Information Obtained From Passive Based Microwave Data

NASA Technical Reports Server (NTRS)

Bolten, John D.; Mladenova, Iliana E.; Crow, Wade; De Jeu, Richard

2016-01-01

A primary operational goal of the United States Department of Agriculture (USDA) is to improve foreign market access for U.S. agricultural products. A large fraction of this crop condition assessment is based on satellite imagery and ground data analysis. The baseline soil moisture estimates that are currently used for this analysis are based on output from the modified Palmer two-layer soil moisture model, updated to assimilate near-real time observations derived from the Soil Moisture Ocean Salinity (SMOS) satellite. The current data assimilation system is based on a 1-D Ensemble Kalman Filter approach, where the observation error is modeled as a function of vegetation density. This allows for offsetting errors in the soil moisture retrievals. The observation error is currently adjusted using Normalized Difference Vegetation Index (NDVI) climatology. In this paper we explore the possibility of utilizing microwave-based vegetation optical depth instead.

Soil moisture and vegetation patterns in northern California forests

Treesearch

James R. Griffin

1967-01-01

Twenty-nine soil-vegetation plots were studied in a broad transect across the southern Cascade Range. Variations in soil moisture patterns during the growing season and in soil moisture tension values are discussed. Plot soil moisture values for 40- and 80-cm. depths in August and September are integrated into a soil drought index. Vegetation patterns are described in...

Soil moisture inferences from thermal infrared measurements of vegetation temperatures

NASA Technical Reports Server (NTRS)

Jackson, R. D. (Principal Investigator)

1981-01-01

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

Spatial pattern and heterogeneity of soil moisture along a transect in a small catchment on the Loess Plateau

NASA Astrophysics Data System (ADS)

Yang, Yang; Dou, Yanxing; Liu, Dong; An, Shaoshan

2017-07-01

Spatial pattern and heterogeneity of soil moisture is important for the hydrological process on the Loess Plateau. This study combined the classical and geospatial statistical techniques to examine the spatial pattern and heterogeneity of soil moisture along a transect scale (e.g. land use types and topographical attributes) on the Loess Plateau. The average values of soil moisture were on the order of farmland > orchard > grassland > abandoned land > shrubland > forestland. Vertical distribution characteristics of soil moisture (0-500 cm) were similar among land use types. Highly significant (p < 0.01) negative correlations were found between soil moisture and elevation (h) except for shrubland (p > 0.05), whereas no significant correlations were found between soil moisture and plan curvature (Kh), stream power index (SPI), compound topographic index (CTI) (p > 0.05), indicating that topographical attributes (mainly h) have a negative effect on the soil moisture spatial heterogeneity. Besides, soil moisture spatial heterogeneity decreased from forestland to grassland and farmland, accompanied by a decline from 15° to 1° alongside upper to lower slope position. This study highlights the importance of land use types and topographical attributes on the soil moisture spatial heterogeneity from a combined analysis of the structural equation model (SEM) and generalized additive models (GAMs), and the relative contribution of land use types to the soil moisture spatial heterogeneity was higher than that of topographical attributes, which provides insights for researches focusing on soil moisture varitions on the Loess Plateau.

Fabrication of Refractive Index Tunable Coating with Moisture-Resistant Function for High-Power Laser Systems Based on Homogeneous Embedding of Surface-Modified Nanoparticles.

PubMed

Yang, Wei; Lei, Xiangyang; Hui, Haohao; Zhang, Qinghua; Deng, Xueran

2018-05-07

Moisture-resistant silicone coatings were prepared on the surface of potassium dihydrogen phosphate (KDP) crystal by means of spin-coating, in which hydrophobic-modified SiO₂ nanoparticles were embedded in a certain proportion. The refractive index of such coating can be tuned arbitrarily in the range of 1.21⁻1.44, which endows the KDP optical component with excellent transmission capability as well as the moisture proof effect. A dual-layer anti-reflective coating system was obtained by covering this silicone coating with a porous SiO₂ coating which is specially treated to enhance the moisture resistance. Transmittance of such a dual-layer coating system could reach 99.60% and 99.62% at 1064 nm and 532 nm, respectively, by precisely matching the refractive index of both layers. Furthermore, the long-term stability of this coating system has been verified at high humidity ambient of 80% RH for 27 weeks.

A Physically-Based Drought Product Using Thermal Remote Sensing of Evapotranspiration

USDA-ARS?s Scientific Manuscript database

Thermal infrared (TIR) remote sensing of land-surface temperature (LST) provides valuable information about the sub-surface moisture status. While empirical indices measuring anomalies in LST and vegetation amount (e.g., as quantified by the Normalized Difference Vegetation Index; NDVI) have demonst...

Analysis of Affecting Factors and Construction of Index System of Rural Domestic Pollution in Guangxi Province

NASA Astrophysics Data System (ADS)

Chen, Hong; Duan, Chunyi

2018-01-01

This paper systematically analysed the influential factors of rural domestic pollution in Guangxi and the current situation and evaluation index of rural domestic pollution, constructed moisture contents indexes system, which included two kinds of indicators in three levels, in a total of 19 indicators of rural domestic pollution. According to the moisture contents indexes system, a combination of quantitative and qualitative methods were adopted to make regionalization of rural domestic pollution in Guangxi more reasonable and provided scientific support for the prevention and control of rural domestic pollution in Guangxi Province.

Temporal dynamics of soil microbial communities under different moisture regimes: high-throughput sequencing and bioinformatics analysis

NASA Astrophysics Data System (ADS)

Semenov, Mikhail; Zhuravleva, Anna; Semenov, Vyacheslav; Yevdokimov, Ilya; Larionova, Alla

2017-04-01

Recent climate scenarios predict not only continued global warming but also an increased frequency and intensity of extreme climatic events such as strong changes in temperature and precipitation regimes. Microorganisms are well known to be more sensitive to changes in environmental conditions than to other soil chemical and physical parameters. In this study, we determined the shifts in soil microbial community structure as well as indicative taxa in soils under three moisture regimes using high-throughput Illumina sequencing and range of bioinformatics approaches for the assessment of sequence data. Incubation experiments were performed in soil-filled (Greyic Phaeozems Albic) rhizoboxes with maize and without plants. Three contrasting moisture regimes were being simulated: 1) optimal wetting (OW), a watering 2-3 times per week to maintain soil moisture of 20-25% by weight; 2) periodic wetting (PW), with alternating periods of wetting and drought; and 3) constant insufficient wetting (IW), while soil moisture of 12% by weight was permanently maintained. Sampled fresh soils were homogenized, and the total DNA of three replicates was extracted using the FastDNA® SPIN kit for Soil. DNA replicates were combined in a pooled sample and the DNA was used for PCR with specific primers for the 16S V3 and V4 regions. In order to compare variability between different samples and replicates within a single sample, some DNA replicates treated separately. The products were purified and submitted to Illumina MiSeq sequencing. Sequence data were evaluated by alpha-diversity (Chao1 and Shannon H' diversity indexes), beta-diversity (UniFrac and Bray-Curtis dissimilarity), heatmap, tagcloud, and plot-bar analyses using the MiSeq Reporter Metagenomics Workflow and R packages (phyloseq, vegan, tagcloud). Shannon index varied in a rather narrow range (4.4-4.9) with the lowest values for microbial communities under PW treatment. Chao1 index varied from 385 to 480, being a more flexible indicator than Shannon index. Chao1 had similar values for OW and IW communities, but alpha-diversity of microbial communities has sharply decreased under PW treatment. There was no visible difference in beta-diversity depending on sampling date and wetting regime, however, it could be possible to distinguish microbial communities in soils with maize and without plants. The presence of maize was acting as scattering agent, making microbial communities more distinguished. In all studied samples, the most dominant phyla were Proteobacteria, Firmicutes, Verrucomicrobia, Actinobacteria, and Acidobacteria. Chthoniobacter, Bacillus, Alicyclobacillus, Rhodoplanes, Cohnella, Kaistobacter, and Solibacter were the most abundant genera. Moreover, these genera were found as the most reactive and variable taxa in microbial community. Thus, DNA high-throughput sequencing revealed no dramatic shifts in bacterial community structure in soils under different moisture regimes. However, this technique allowed us to determine the effect of wetting regime and the presence of plants on soil microbial community which were adaptable to insufficient wetting, but lost diversity under periodic wetting. Furthermore, we detected the indicative taxa which dominate in microbial communities and at the same time strongly react to environmental changes.

Lodgepole pine site index in relation to synoptic measures of climate, soil moisture and soil nutrients.

Treesearch

G. Geoff Wang; Shongming Huang; Robert A. Monserud; Ryan J. Klos

2004-01-01

Lodgepole pine site index was examined in relation to synoptic measures of topography, soil moisture, and soil nutrients in Alberta. Data came from 214 lodgepole pine-dominated stands sampled as a part of the provincial permanent sample plot program. Spatial location (elevation, latitude, and longitude) and natural subregions (NSRs) were topographic variables that...

Effect of sample moisture content on XRD-estimated cellulose crystallinity index and crystallite size

Treesearch

Umesh P. Agarwal; Sally A. Ralph; Carlos Baez; Richard S. Reiner; Steve P. Verrill

2017-01-01

Although X-ray diffraction (XRD) has been the most widely used technique to investigate crystallinity index (CrI) and crystallite size (L200) of cellulose materials, there are not many studies that have taken into account the role of sample moisture on these measurements. The present investigation focuses on a variety of celluloses and cellulose...

Assessing the evolution of soil moisture and vegetation conditions during the 2012 United States flash drought

USGS Publications Warehouse

Otkin, Jason A.; Anderson, Martha C.; Hain, Christopher; Svoboda, Mark; Johnson, David; Mueller, Richard; Tadesse, Tsegaye; Wardlow, Brian D.; Brown, Jesslyn

2016-01-01

This study examines the evolution of several model-based and satellite-derived drought metrics sensitive to soil moisture and vegetation conditions during the extreme flash drought event that impacted major agricultural areas across the central U.S. during 2012. Standardized anomalies from the remote sensing based Evaporative Stress Index (ESI) and Vegetation Drought Response Index (VegDRI) and soil moisture anomalies from the North American Land Data Assimilation System (NLDAS) are compared to the United States Drought Monitor (USDM), surface meteorological conditions, and crop and soil moisture data compiled by the National Agricultural Statistics Service (NASS).Overall, the results show that rapid decreases in the ESI and NLDAS anomalies often preceded drought intensification in the USDM by up to 6 wk depending on the region. Decreases in the ESI tended to occur up to several weeks before deteriorations were observed in the crop condition datasets. The NLDAS soil moisture anomalies were similar to those depicted in the NASS soil moisture datasets; however, some differences were noted in how each model responded to the changing drought conditions. The VegDRI anomalies tracked the evolution of the USDM drought depiction in regions with slow drought development, but lagged the USDM and other drought indicators when conditions were changing rapidly. Comparison to the crop condition datasets revealed that soybean conditions were most similar to ESI anomalies computed over short time periods (2–4 wk), whereas corn conditions were more closely related to longer-range (8–12 wk) ESI anomalies. Crop yield departures were consistent with the drought severity depicted by the ESI and to a lesser extent by the NLDAS and VegDRI datasets.

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.

Integrating effective drought index (EDI) and remote sensing derived parameters for agricultural drought assessment and prediction in Bundelkhand region of India

NASA Astrophysics Data System (ADS)

Padhee, S. K.; Nikam, B. R.; Aggarwal, S. P.; Garg, V.

2014-11-01

Drought is an extreme condition due to moisture deficiency and has adverse effect on society. Agricultural drought occurs when restraining soil moisture produces serious crop stress and affects the crop productivity. The soil moisture regime of rain-fed agriculture and irrigated agriculture behaves differently on both temporal and spatial scale, which means the impact of meteorologically and/or hydrological induced agriculture drought will be different in rain-fed and irrigated areas. However, there is a lack of agricultural drought assessment system in Indian conditions, which considers irrigated and rain-fed agriculture spheres as separate entities. On the other hand recent advancements in the field of earth observation through different satellite based remote sensing have provided researchers a continuous monitoring of soil moisture, land surface temperature and vegetation indices at global scale, which can aid in agricultural drought assessment/monitoring. Keeping this in mind, the present study has been envisaged with the objective to develop agricultural drought assessment and prediction technique by spatially and temporally assimilating effective drought index (EDI) with remote sensing derived parameters. The proposed technique takes in to account the difference in response of rain-fed and irrigated agricultural system towards agricultural drought in the Bundelkhand region (The study area). The key idea was to achieve the goal by utilizing the integrated scenarios from meteorological observations and soil moisture distribution. EDI condition maps were prepared from daily precipitation data recorded by Indian Meteorological Department (IMD), distributed within the study area. With the aid of frequent MODIS products viz. vegetation indices (VIs), and land surface temperature (LST), the coarse resolution soil moisture product from European Space Agency (ESA) were downscaled using linking model based on Triangle method to a finer resolution soil moisture product. EDI and spatially downscaled soil moisture products were later used with MODIS 16 days NDVI product as key elements to assess and predict agricultural drought in irrigated and rain-fed agricultural systems in Bundelkhand region of India. Meteorological drought, soil moisture deficiency and NDVI degradation were inhabited for each and every pixel of the image in GIS environment, for agricultural impact assessment at a 16 day temporal scale for Rabi seasons (October-April) between years 2000 to 2009. Based on the statistical analysis, good correlations were found among the parameters EDI and soil moisture anomaly; NDVI anomaly and soil moisture anomaly lagged to 16 days and these results were exploited for the development of a linear prediction model. The predictive capability of the developed model was validated on the basis of spatial distribution of predicted NDVI which was compared with MODIS NDVI product in the beginning of preceding Rabi season (Oct-Dec of 2010).The predictions of the model were based on future meteorological data (year 2010) and were found to be yielding good results. The developed model have good predictive capability based on future meteorological data (rainfall data) availability, which enhances its utility in analyzing future Agricultural conditions if meteorological data is available.

Impact of the assimilation of satellite soil moisture and LST on the hydrological cycle

NASA Astrophysics Data System (ADS)

Laiolo, Paola; Gabellani, Simone; Delogu, Fabio; Silvestro, Francesco; Rudari, Roberto; Campo, Lorenzo; Boni, Giorgio

2014-05-01

The reliable estimation of hydrological variables (e.g. soil moisture, evapotranspiration, surface temperature) in space and time is of fundamental importance in operational hydrology to improve the forecast of the rainfall-runoff response of catchments and, consequently, flood predictions. Nowadays remote sensing can offer a chance to provide good space-time estimates of several hydrological variables and then improve hydrological model performances especially in environments with scarce ground based data. The aim of this work is to investigate the impacts on the performances of a distributed hydrological model (Continuum) of the assimilation of satellite-derived soil moisture products and Land Surface (LST). In this work three different soil moisture (SM) products, derived by ASCAT sensor, are used. These data are provided by the EUMETSAT's H-SAF (Satellite Application Facility on Support to Operational Hydrology and Water Management) program. The considered soil moisture products are: large scale surface soil moisture (SM OBS 1 - H07), small scale surface soil moisture (SM OBS 2 - H08) and profile index in the roots region (SM DAS 2 - H14). These data are compared with soil moisture estimated by Continuum model on the Orba catchment (800 km2), in the northern part of Italy, for the period July 2012-June 2013. Different assimilation experiments have been performed. The first experiment consists in the assimilation of the SM products by using a simple Nudging technique; the second one is the assimilation of only LST data, derived from MSG satellite, and the third is the assimilation of both SM products and LST. The benefits on the model predictions of discharge, LST and soil moisture dynamics were tested.

Passive microwave soil moisture downscaling using vegetation index and skin surface temperature

USDA-ARS?s Scientific Manuscript database

Soil moisture satellite estimates are available from a variety of passive microwave satellite sensors, but their spatial resolution is frequently too coarse for use by land managers and other decision makers. In this paper, a soil moisture downscaling algorithm based on a regression relationship bet...

Drought monitoring over the Horn of Africa using remotely sensed evapotranspiration, soil moisture and vegetation parameters

NASA Astrophysics Data System (ADS)

Timmermans, J.; Gokmen, M.; Eden, U.; Abou Ali, M.; Vekerdy, Z.; Su, Z.

2012-04-01

The need to good drought monitoring and management for the Horn of Africa has never been greater. This ongoing drought is the largest in the past sixty years and is effecting the life of around 10 million people, according to the United Nations. The impact of drought is most apparent in food security and health. In addition secondary problems arise related to the drought such as large migration; more than 15000 Somalia have fled to neighboring countries to escape the problems caused by the drought. These problems will only grow in the future to larger areas due to increase in extreme weather patterns due to global climate change. Monitoring drought impact and managing the drought effects are therefore of critical importance. The impact of a drought is hard to characterize as drought depends on several parameters, like precipitation, land use, irrigation. Consequently the effects of the drought vary spatially and range from short-term to long-term. For this reason a drought event can be characterized into four categories: meteorological, agricultural, hydrological and socio-economical. In terms of food production the agricultural drought, or short term dryness near the surface layer, is most important. This drought is usually characterized by low soil moisture content in the root zone, decreased evapotranspiration, and changes in vegetation vigor. All of these parameters can be detected with good accuracy from space. The advantage of remote sensing in Drought monitoring is evident. Drought monitoring is usually performed using drought indices, like the Palmer Index (PDSI), Crop Moisture Index (CMI), Standard Precipitation Index (SPI). With the introduction of remote sensing several indices of these have shown great potential for large scale application. These indices however all incorporate precipitation as the main surface parameter neglecting the response of the surface to the dryness. More recently two agricultural drought indices, the EvapoTranspiration Deficit Index (ETDI) and the Soil Moisture Deficit Index (SMDI), have been proposed to investigate this. The ETDI considers the stress ratio caused by the difference between potential and actual evapotranspiration, while SMDI considers the variation in soil moisture availability to the plant. As there is not a single unique accepted definition of drought, investigation into the impact of drought should not be confined to a single drought index; instead several indices need to be used for this purpose. The objective of this research is to investigate the drought in the Horn of Africa using several remote sensing drought indices and vegetation parameters. In this research the drought will be investigated using SPI, ETDI, SMDI, NDVI and SPI. For this purpose ETDI and SMDI will be estimated from remote sensing products for the period from 2002 till 2011that are created in framework of the WACMOS project. The research involves the comparison of the different drought indices and the research into possible synergies to enhance drought monitoring.

Quantifying agricultural drought impacts using soil moisture model and drought indices in South Korea

NASA Astrophysics Data System (ADS)

Nam, W. H.; Bang, N.; Hong, E. M.; Pachepsky, Y. A.; Han, K. H.; Cho, H.; Ok, J.; Hong, S. Y.

2017-12-01

Agricultural drought is defined as a combination of abnormal deficiency of precipitation, increased crop evapotranspiration demands from high-temperature anomalies, and soil moisture deficits during the crop growth period. Soil moisture variability and their spatio-temporal trends is a key component of the hydrological balance, which determines the crop production and drought stresses in the context of agriculture. In 2017, South Korea has identified the extreme drought event, the worst in one hundred years according to the South Korean government. The objective of this study is to quantify agricultural drought impacts using observed and simulated soil moisture, and various drought indices. A soil water balance model is used to simulate the soil water content in the crop root zone under rain-fed (no irrigation) conditions. The model used includes physical process using estimated effective rainfall, infiltration, redistribution in soil water zone, and plant water uptake in the form of actual crop evapotranspiration. Three widely used drought indices, including the Standardized Precipitation Index (SPI), the Standardized Precipitation Evapotranspiration Index (SPEI), and the Self-Calibrated Palmer Drought Severity Index (SC-PDSI) are compared with the observed and simulated soil moisture in the context of agricultural drought impacts. These results demonstrated that the soil moisture model could be an effective tool to provide improved spatial and temporal drought monitoring for drought policy.

Estimating Long Term Surface Soil Moisture in the GCIP Area From Satellite Microwave Observations

NASA Technical Reports Server (NTRS)

Owe, Manfred; deJeu, Vrije; VandeGriend, Adriaan A.

2000-01-01

Soil moisture is an important component of the water and energy balances of the Earth's surface. Furthermore, it has been identified as a parameter of significant potential for improving the accuracy of large-scale land surface-atmosphere interaction models. However, accurate estimates of surface soil moisture are often difficult to make, especially at large spatial scales. Soil moisture is a highly variable land surface parameter, and while point measurements are usually accurate, they are representative only of the immediate site which was sampled. Simple averaging of point values to obtain spatial means often leads to substantial errors. Since remotely sensed observations are already a spatially averaged or areally integrated value, they are ideally suited for measuring land surface parameters, and as such, are a logical input to regional or larger scale land process models. A nine-year database of surface soil moisture is being developed for the Central United States from satellite microwave observations. This region forms much of the GCIP study area, and contains most of the Mississippi, Rio Grande, and Red River drainages. Daytime and nighttime microwave brightness temperatures were observed at a frequency of 6.6 GHz, by the Scanning Multichannel Microwave Radiometer (SMMR), onboard the Nimbus 7 satellite. The life of the SMMR instrument spanned from Nov. 1978 to Aug. 1987. At 6.6 GHz, the instrument provided a spatial resolution of approximately 150 km, and an orbital frequency over any pixel-sized area of about 2 daytime and 2 nighttime passes per week. Ground measurements of surface soil moisture from various locations throughout the study area are used to calibrate the microwave observations. Because ground measurements are usually only single point values, and since the time of satellite coverage does not always coincide with the ground measurements, the soil moisture data were used to calibrate a regional water balance for the top 1, 5, and 10 cm surface layers in order to interpolate daily surface moisture values. Such a climate-based approach is often more appropriate for estimating large-area spatially averaged soil moisture because meteorological data are generally more spatially representative than isolated point measurements of soil moisture. Vegetation radiative transfer characteristics, such as the canopy transmissivity, were estimated from vegetation indices such as the Normalized Difference Vegetation Index (NDVI) and the 37 GHz Microwave Polarization Difference Index (MPDI). Passive microwave remote sensing presents the greatest potential for providing regular spatially representative estimates of surface soil moisture at global scales. Real time estimates should improve weather and climate modelling efforts, while the development of historical data sets will provide necessary information for simulation and validation of long-term climate and global change studies.

A flash flood early warning system based on rainfall thresholds and daily soil moisture indexes

NASA Astrophysics Data System (ADS)

Brigandì, Giuseppina; Tito Aronica, Giuseppe

2015-04-01

Main focus of the paper is to present a flash flood early warning system, developed for Civil Protection Agency for the Sicily Region, for alerting extreme hydrometeorological events by using a methodology based on the combined use of rainfall thresholds and soil moisture indexes. As matter of fact, flash flood warning is a key element to improve the Civil Protection achievements to mitigate damages and safeguard the security of people. It is a rather complicated task, particularly in those catchments with flashy response where even brief anticipations are important and welcomed. In this context, some kind of hydrological precursors can be considered to improve the effectiveness of the emergency actions (i.e. early flood warning). Now, it is well known how soil moisture is an important factor in flood formation, because the runoff generation is strongly influenced by the antecedent soil moisture conditions of the catchment. The basic idea of the work here presented is to use soil moisture indexes derived in a continuous form to define a first alert phase in a flash flood forecasting chain and then define a unique rainfall threshold for a given day for the subsequent alarm phases activation, derived as a function of the soil moisture conditions at the beginning of the day. Daily soil moisture indexes, representative of the moisture condition of the catchment, were derived by using a parsimonious and simply to use approach based on the IHACRES model application in a modified form developed by the authors. It is a simple, spatially-lumped rainfall-streamflow model, based on the SCS-CN method and on the unit hydrograph approach that requires only rainfall, streamflow and air temperature data. It consists of two modules. In the first a non linear loss model, based on the SCS-CN method, was used to transform total rainfall into effective rainfall. In the second, a linear convolution of effective rainfall was performed using a total unit hydrograph with a configuration of one parallel channel and reservoir, thereby corresponding to 'quick' and 'slow' components of runoff. In the non linear model a wetness/soil moisture index, varying from 0 to 1, was derived to define daily soil moisture catchment conditions and then conveniently linked to a corresponding CN value to use as input to derive the corresponding rainfall threshold for a given day. Finally, rainfall thresholds for flash flooding were derived using an Instantaneous Unit Hydrograph based lumped rainfall-runoff model with the SCS-CN routine for net rainfall. Application of the proposed methodology was carried out with reference to a river basin in Sicily, Italy.

Effects of processing moisture on the physical properties and in vitro digestibility of starch and protein in extruded brown rice and pinto bean composite flours.

PubMed

Sumargo, Franklin; Gulati, Paridhi; Weier, Steven A; Clarke, Jennifer; Rose, Devin J

2016-11-15

The influence of pinto bean flour and processing moisture on the physical properties and in vitro digestibility of rice-bean extrudates has been investigated. Brown rice: pinto bean flour (0%, 15%, 30%, and 45% bean flour) were extruded under 5 moisture conditions (17.2%, 18.1%, 18.3%, 19.5%, and 20.1%). Physical properties [bulk density, unit density, radial expansion, axial expansion, overall expansion, specific volume, hardness, color, water solubility index, and water absorption index] and in vitro starch and protein digestibilities were determined. Increasing bean flour and processing moisture increased density and hardness while decreasing expansion. Rapidly digestible starch decreased and resistant starch increased as bean substitution and processing moisture increased. In vitro protein digestibility increased with increasing bean flour or with decreasing processing moisture. Incorporating bean flour into extruded snacks can negatively affect physical attributes (hardness, density, and expansion) while positively affecting in vitro starch (decrease) and protein (increase) digestibilities. Copyright © 2016 Elsevier Ltd. All rights reserved.

[Effect of moisture content on vigor of Cyathula officinalis seeds and its anti-aging mechanism analysis].

PubMed

Wang, Qian; Yang, Mei; Pei, Jin; Wang, Li; Wu, Yi-Yun; Lv, Hui

2016-04-01

Effects of nine different moisture contents on vigor of Cyathula officinalis seeds and its anti-aging mechanism were studied by artificial accelerated aging through high temperature and wet. The research results showedthat seed vigor were generally decreased after artificial aging; in general, seed vigor and its anti-aging ability are relatively stronger within the scope of 6.55%-4.78% moisture content, the increase range of seed conductivity, peroxidase activity, malondialdehyde content,and reduce amplitude of activityof dehydrogenase , superoxide dismutaseare alllower as well. And when the moisture content reduced to 5.77%, all of the germination tests index of the non-aged seeds are the highest, and the activity of peroxidase the lowest,conductivity of leaching solution relatively low, activity of dehydrogenase and superoxide dismutase the highest,and catalase activityrelatively high.Therefore, in the low temperature germplasm preservation of C. officinalis seeds, the seed moisture content should be controlled close to the range of (5.70±1)% to keep higher vigor and anti-aging ability. Copyright© by the Chinese Pharmaceutical Association.

Developing satellite-derived estimates of surface moisture status

NASA Technical Reports Server (NTRS)

Nemani, Ramakhrishna; Pierce, Lars; Running, Steve; Goward, Samuel

1993-01-01

An evaluation is made of the remotely sensed surface temperature (Ts)/normalized difference vegetation index (NDVI) relationship in studies of the influence of biome type on the slope of Ts/NDVI, and of the automation of the process of defining the relationship so that the surface moisture status can be compared with Ts/NDVI at continental scales. The analysis is conducted using the NOAA AVHRR over a 300 x 300 km area in western Montana, as well as biweekly composite AVHRR data. A strong negative relationship is established between NDVI and Ts over all biome types.

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.

Droughts and Excessive Moisture Events in Southern Siberia in the Late XXth - Early XXIst Centuries

NASA Astrophysics Data System (ADS)

Ryazanova, A. A.; Voropay, N. N.

2017-11-01

In recent years much research has been devoted to global and regional climate changes. Special attention was paid to climate extremes, such as droughts and excessive moisture events. In this study the moisture and aridity of Southern Siberia are estimated using web-GIS called “CLIMATE”. The system “CLIMATE” is part of a hardware and software cloud storage complex for data analysis of various climatic data sets, with algorithms for searching, extracting, processing, and visualizing the data. The ECMWF ERA-Interim reanalysis data for Southern Siberia (50-65°N, 60-120°E) from 1979 to 2010 with a grid cell of 0.75×0.75° is used. Some hydrothermal conditions are estimated using the so-called Ped index (Si), which is a normalized indicator of the ratio of air temperature to precipitation. The mountain regions of Eastern Siberia are becoming more and more arid each month during the last 30 years. In Western Siberia, aridity increases in May and decreases in June, in the other months positive and negative trends are found. The greatest differences between the trends of the aridity index (Si), air temperature, and precipitation are observed in July.

Flood and landslide warning based on rainfall thresholds and soil moisture indexes: the HEWS (Hydrohazards Early Warning System) for Sicily

NASA Astrophysics Data System (ADS)

Brigandì, Giuseppina; Tito Aronica, Giuseppe; Bonaccorso, Brunella; Gueli, Roberto; Basile, Giuseppe

2017-09-01

The main focus of the paper is to present a flood and landslide early warning system, named HEWS (Hydrohazards Early Warning System), specifically developed for the Civil Protection Department of Sicily, based on the combined use of rainfall thresholds, soil moisture modelling and quantitative precipitation forecast (QPF). The warning system is referred to 9 different Alert Zones in which Sicily has been divided into and based on a threshold system of three different increasing critical levels: ordinary, moderate and high. In this system, for early flood warning, a Soil Moisture Accounting (SMA) model provides daily soil moisture conditions, which allow to select a specific set of three rainfall thresholds, one for each critical level considered, to be used for issue the alert bulletin. Wetness indexes, representative of the soil moisture conditions of a catchment, are calculated using a simple, spatially-lumped rainfall-streamflow model, based on the SCS-CN method, and on the unit hydrograph approach, that require daily observed and/or predicted rainfall, and temperature data as input. For the calibration of this model daily continuous time series of rainfall, streamflow and air temperature data are used. An event based lumped rainfall-runoff model has been, instead, used for the derivation of the rainfall thresholds for each catchment in Sicily characterised by an area larger than 50 km2. In particular, a Kinematic Instantaneous Unit Hydrograph based lumped rainfall-runoff model with the SCS-CN routine for net rainfall was developed for this purpose. For rainfall-induced shallow landslide warning, empirical rainfall thresholds provided by Gariano et al. (2015) have been included in the system. They were derived on an empirical basis starting from a catalogue of 265 shallow landslides in Sicily in the period 2002-2012. Finally, Delft-FEWS operational forecasting platform has been applied to link input data, SMA model and rainfall threshold models to produce warning on a daily basis for the entire region.

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.

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.

The Value of SMAP Soil Moisture Observations For Agricultural Applications

NASA Astrophysics Data System (ADS)

Mladenova, I. E.; Bolten, J. D.; Crow, W.; Reynolds, C. A.

2017-12-01

Knowledge of the amount of soil moisture (SM) in the root zone (RZ) is critical source of information for crop analysts and agricultural agencies as it controls crop development and crop condition changes and can largely impact end-of-season yield. Foreign Agricultural Services (FAS), a subdivision of U.S. Department of Agriculture (USDA) that is in charge with providing information on current and expected global crop supply and demand estimates, has been relying on RZSM estimates generated by the modified two-layer Palmer model, which has been enhanced to allow the assimilation of satellite-based soil moisture data. Generally the accuracy of model-based soil moisture estimates is dependent on the precision of the forcing data that drives the model and more specifically, the accuracy of the precipitation data. Data assimilation gives the opportunity to correct for such precipitation-related inaccuracies and enhance the quality of the model estimates. Here we demonstrate the value of ingesting passive-based soil moisture observations derived from the Soil Moisture Active Passive (SMAP) mission. In terms of agriculture, general understanding is that the change in soil moisture conditions precede the change in vegetation status, suggesting that soil moisture can be used as an early indicator of expected crop conditions. Therefore, we assess the accuracy of the SMAP enhanced Palmer model by examining the lag rank cross-correlation coefficient between the model generated soil moisture observations and the Normalized Difference Vegetation Index (NDVI).

The SWEX at the area of Eastern Poland: Comparison of soil moisture obtained from ground measurements and SMOS satellite data*

NASA Astrophysics Data System (ADS)

Usowicz, J. B.; Marczewski, W.; Usowicz, B.; Lukowski, M. I.; Lipiec, J.; Slominski, J.

2012-04-01

Soil moisture, together with soil and vegetation characteristics, plays an important role in exchange of water and energy between the land surface and the atmospheric boundary layer. Accurate knowledge of current and future spatial and temporal variation in soil moisture is not well known, nor easy to measure or predict. Knowledge of soil moisture in surface and root zone soil moisture is critical for achieving sustainable land and water management. The importance of SM is so high that this ECV is recommended by GCOS (Global Climate Observing System) to any attempts of evaluating of effects the climate change, and therefore it is one of the goals for observing the Earth by the ESA SMOS Mission (Soil Moisture and Ocean Salinity), globally. SMOS provides its observations by means of the interferometric radiometry method (1.4 GHz) from the orbit. In parallel, ten ground based stations are kept by IA PAN, in area of the Eastern Wall in Poland, in order to validate SMOS data and for other ground based agrophysical purposes. Soil moisture measurements obtained from ground and satellite measurements from SMOS were compared using Bland-Altman method of agreement, concordance correlation coefficient (CCC) and total deviation index (TDI). Observed similar changes in soil moisture, but the values obtained from satellite measurements were lower. Minor differences between the compared data are at higher moisture contents of soil and they grow with decreasing soil moisture. Soil moisture trends are maintained in the individual stations. Such distributions of soil moisture were mainly related to soil type. * The work was financially supported in part by the ESA Programme for European Cooperating States (PECS), No.98084 "SWEX-R, Soil Water and Energy Exchange/Research", AO3275.

Soil-Site Factors Affecting Southern Upland Oak Managment and Growth

Treesearch

John K. Francis

1980-01-01

Soil supplies trees with physical support, moisture, oxygen, and nutrients. Amount of moisture most limits tree growth; and soil and topographic factors such as texture and aspect, which influence available soil moisture. are most useful in predicting growth. Equations that include soil and topographic variables can be used to predict site index. Foresters can also...

Estimating Soil Moisture from Satellite Microwave Observations

NASA Technical Reports Server (NTRS)

Owe, M.; VandeGriend, A. A.; deJeu, R.; deVries, J.; Seyhan, E.

1998-01-01

Cooperative research in microwave remote sensing between the Hydrological Sciences Branch of the NASA Goddard Space Flight Center and the Earth Sciences Faculty of the Vrije Universiteit Amsterdam began with the Botswana Water and Energy Balance Experiment and has continued through a series of highly successful International Research Programs. The collaboration between these two research institutions has resulted in significant scientific achievements, most notably in the area of satellite-based microwave remote sensing of soil moisture. The Botswana Program was the first joint research initiative between these two institutions, and provided a unique data base which included historical data sets of Scanning Multifrequency Microwave Radiometer (SN4NM) data, climate information, and extensive soil moisture measurements over several large experimental sites in southeast Botswana. These data were the basis for the development of new approaches in physically-based inverse modelling of soil moisture from satellite microwave observations. Among the results from this study were quantitative estimates of vegetation transmission properties at microwave frequencies. A single polarization modelling approach which used horizontally polarized microwave observations combined with monthly composites of Normalized Difference Vegetation Index was developed, and yielded good results. After more precise field experimentation with a ground-based radiometer system, a dual-polarization approach was subsequently developed. This new approach realized significant improvements in soil moisture estimation by satellite. Results from the Botswana study were subsequently applied to a desertification monitoring study for the country of Spain within the framework of the European Community science research programs EFEDA and RESMEDES. A dual frequency approach with only microwave data was used for this application. The Microwave Polarization Difference Index (MPDI) was calculated from 37 GHz data and used to derive the one-way canopy transmissivity. Using a simple radiative transfer model, this information was combined with horizontally polarized 6.6 GHz SMMR observations to derive a 9-year time series of soil moisture for all of Spain at a one quarter degree spatial scale. Both day and night SMMR observations were used independently, in order to check the consistency of the results. A first order Fourier Transform was performed on the mean monthly soil moisture values to identify major characteristics of time series such as trend, amplitude, and phase shift.

Water Availability in a Warming World

NASA Astrophysics Data System (ADS)

Aminzade, Jennifer

As climate warms during the 21st century, the resultant changes in water availability are a vital issue for society, perhaps even more important than the magnitude of warming itself. Yet our climate models disagree in their forecasts of water availability, limiting our ability to plan accordingly. This thesis investigates future water availability projections from Coupled Ocean-Atmosphere General Circulation Models (GCMs), primarily using two water availability measures: soil moisture and the Supply Demand Drought Index (SDDI). Chapter One introduces methods of measuring water availability and explores some of the fundamental differences between soil moisture, SDDI and the Palmer Drought Severity Index (PDSI). SDDI and PDSI tend to predict more severe future drought conditions than soil moisture; 21st century projections of SDDI show conditions rivaling North American historic mega-droughts. We compare multiple potential evapotranspiration (EP) methods in New York using input from the GISS Model ER GCM and local station data from Rochester, NY, and find that they compare favorably with local pan evaporation measurements. We calculate SDDI and PDSI values using various EP methods, and show that changes in future projections are largest when using EP methods most sensitive to global warming, not necessarily methods producing EP values with the largest magnitudes. Chapter Two explores the characteristics and biases of the five GCMs and their 20th and 21st century climate projections. We compare atmospheric variables that drive water availability changes globally, zonally, and geographically among models. All models show increases in both dry and wet extremes for SDDI and soil moisture, but increases are largest for extreme drying conditions using SDDI. The percentage of gridboxes that agree on the sign of change of soil moisture and SDDI between models is very low, but does increase in the 21st century. Still, differences between models are smaller than differences between SDDI and soil moisture projections. Chapter Three addresses the three major differences between SDDI and soil moisture calculations that shed light on why their future projections diverge: evaporation approximations, dependence on previous months' conditions, and the inclusion of additional variables such as runoff. We implement various changes in SDDI and a GCM vegetation scheme to test the sensitivity of each measure and to evaluate which alterations increase the similarity between SDDI and soil moisture. In addition to deconstructing the differences between SDDI and soil moisture, we analyze their projections regionally in Chapter Four. In seven regions (the southwest U.S., southern Europe, eastern China, eastern Siberia, Australia, Uruguay and Colombia), we (1) assess the forecasts of future water availability changes, (2) compare the atmospheric dynamical processes that produce rainfall and drought in the real world to the way it occurs in individual GCMs, (3) determine how these processes change as global temperatures increase, and (4) identify the most likely scenarios for future regional water availability. Chapter Five summarizes key findings by chapter, enumerating this dissertation's contributions to the field. It then discusses the limitations of existing models and measures, and suggests potential solutions for overcoming their predictive shortfalls. Finally, the chapter concludes with a proposal for future research to expand upon this dissertation work. This thesis highlights the global and zonal differences between two water availability measures, SDDI and soil moisture and identifies regions where they agree and disagree in 21st century modeled scenarios. It provides an explanation for differing projections in soil moisture and SDDI and proves that it is possible to bring convergence to their future projections, which is also applicable to PDSI. Finally, a detailed analysis of climatic changes from five GCMs made it possible to present the most likely scenarios for 21st century water availability in seven regions.

A simulation study of the recession coefficient for antecedent precipitation index. [soil moisture and water runoff estimation

NASA Technical Reports Server (NTRS)

Choudhury, B. J.; Blanchard, B. J.

1981-01-01

The antecedent precipitation index (API) is a useful indicator of soil moisture conditions for watershed runoff calculations and recent attempts to correlate this index with spaceborne microwave observations have been fairly successful. It is shown that the prognostic equation for soil moisture used in some of the atmospheric general circulation models together with Thornthwaite-Mather parameterization of actual evapotranspiration leads to API equations. The recession coefficient for API is found to depend on climatic factors through potential evapotranspiration and on soil texture through the field capacity and the permanent wilting point. Climatologial data for Wisconsin together with a recently developed model for global isolation are used to simulate the annual trend of the recession coefficient. Good quantitative agreement is shown with the observed trend at Fennimore and Colby watersheds in Wisconsin. It is suggested that API could be a unifying vocabulary for watershed and atmospheric general circulation modelars.

Spatio-temporal footprints of urbanisation in Surat, the Diamond City of India (1990-2009).

PubMed

Sharma, Richa; Ghosh, Aniruddha; Joshi, Pawan Kumar

2013-04-01

Urbanisation is a ubiquitous phenomenon with greater prominence in developing nations. Urban expansion involves land conversions from vegetated moisture-rich to impervious moisture-deficient land surfaces. The urban land transformations alter biophysical parameters in a mode that promotes development of heat islands and degrades environmental health. This study elaborates relationships among various environmental variables using remote sensing dataset to study spatio-temporal footprint of urbanisation in Surat city. Landsat Thematic Mapper satellite data were used in conjugation with geo-spatial techniques to study urbanisation and correlation among various satellite-derived biophysical parameters, [Normalised Difference Vegetation Index, Normalised Difference Built-up Index, Normalised Difference Water Index, Normalised Difference Bareness Index, Modified NDWI and land surface temperature (LST)]. Land use land cover was prepared using hierarchical decision tree classification with an accuracy of 90.4 % (kappa = 0.88) for 1990 and 85 % (kappa = 0.81) for 2009. It was found that the city has expanded over 42.75 km(2) within a decade, and these changes resulted in elevated surface temperatures. For example, transformation from vegetation to built-up has resulted in 5.5 ± 2.6 °C increase in land surface temperature, vegetation to fallow 6.7 ± 3 °C, fallow to built-up is 3.5 ± 2.9 °C and built-up to dense built-up is 5.3 ± 2.8 °C. Directional profiling for LST was done to study spatial patterns of LST in and around Surat city. Emergence of two new LST peaks for 2009 was observed in N-S and NE-SW profiles.

Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices

USGS Publications Warehouse

Ji, Lei; Peters, Albert J.

2003-01-01

The Normalized Difference Vegetation Index (NDVI) derived from the Advanced Very High Resolution Radiometer (AVHRR) has been widely used to monitor moisture-related vegetation condition. The relationship between vegetation vigor and moisture availability, however, is complex and has not been adequately studied with satellite sensor data. To better understand this relationship, an analysis was conducted on time series of monthly NDVI (1989–2000) during the growing season in the north and central U.S. Great Plains. The NDVI was correlated to the Standardized Precipitation Index (SPI), a multiple-time scale meteorological-drought index based on precipitation. The 3-month SPI was found to have the best correlation with the NDVI, indicating lag and cumulative effects of precipitation on vegetation, but the correlation between NDVI and SPI varies significantly between months. The highest correlations occurred during the middle of the growing season, and lower correlations were noted at the beginning and end of the growing season in most of the area. A regression model with seasonal dummy variables reveals that the relationship between the NDVI and SPI is significant in both grasslands and croplands, if this seasonal effect is taken into account. Spatially, the best NDVI–SPI relationship occurred in areas with low soil water-holding capacity. Our most important finding is that NDVI is an effective indicator of vegetation-moisture condition, but seasonal timing should be taken into consideration when monitoring drought with the NDVI.

7 CFR 61.103 - Determination of quality index.

Code of Federal Regulations, 2012 CFR

2012-01-01

... percent of foreign matter, not more than 12.0 percent of moisture, and not more than 1.8 percent of free..., contain foreign matter, moisture, or free fatty acids in the oil in the seed, in excess of the percentages... of 1.0 percent. (3) One-tenth of a unit for each 0.1 percent of moisture in excess of 12.0 percent...

7 CFR 61.103 - Determination of quality index.

Code of Federal Regulations, 2014 CFR

2014-01-01

... percent of foreign matter, not more than 12.0 percent of moisture, and not more than 1.8 percent of free..., contain foreign matter, moisture, or free fatty acids in the oil in the seed, in excess of the percentages... of 1.0 percent. (3) One-tenth of a unit for each 0.1 percent of moisture in excess of 12.0 percent...

7 CFR 61.103 - Determination of quality index.

Code of Federal Regulations, 2013 CFR

2013-01-01

... percent of foreign matter, not more than 12.0 percent of moisture, and not more than 1.8 percent of free..., contain foreign matter, moisture, or free fatty acids in the oil in the seed, in excess of the percentages... of 1.0 percent. (3) One-tenth of a unit for each 0.1 percent of moisture in excess of 12.0 percent...

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.

Investigation of functional properties and color changes of corn extrudates enriched with broccoli or olive paste.

PubMed

Bisharat, Ghassan I; Katsavou, Ioanna D; Panagiotou, Nikolaos M; Krokida, Magdalini K; Maroulis, Zacharias B

2015-12-01

Following the tendency of replacing common food snacks with healthier food products, extruded snacks with corn flour and broccoli (4-10%) or olive paste (4-8%) were investigated in this study. The effect of material characteristics, including feed moisture content (14-19%), and broccoli or olive paste concentration, and extrusion conditions, including screw speed (150-250 r/min), and extrusion temperature (140-180 ℃), on the functional properties (water absorption index, water solubility index, and oil absorption index), as well as color change (ΔE) of the extruded snacks was studied. Regression analysis showed that screw speed did not significantly influence (p > 0.05) the properties. After mathematical modelling it was found that broccoli and olive paste concentration, as well as temperature increment, caused a decrease in water absorption index (minimum of 5.6 and 6.4 g/g sample, respectively) and an increase in water solubility index (maximum of 18.7 and 10.9 g/100 g sample, respectively), while feed moisture presented opposite tendency. Higher extrusion temperature led to an increment of oil absorption index (approximately to 1.2 and 1 mL/g sample) and decrement of color changes. Finally, feed moisture and broccoli concentration lowered oil absorption index and color of corn/broccoli extrudates, while olive paste concentration caused their increment. © The Author(s) 2014.

In-depth Analysis of Land Surface Emissivity using Microwave Polarization Difference Index to Improve Satellite QPE

NASA Astrophysics Data System (ADS)

Zheng, Y.; Kirstetter, P. E.; Hong, Y.; Wen, Y.; Turk, J.; Gourley, J. J.

2015-12-01

One of primary uncertainties in satellite overland quantitative precipitation estimates (QPE) from passive sensors such as radiometers is the impact on the brightness temperatures by the surface land emissivity. The complexity of surface land emissivity is linked to its temporal variations (diurnal and seasonal) and spatial variations (subsurface vertical profiles of soil moisture, vegetation structure and surface temperature) translating into sub-pixel heterogeneity within the satellite field of view (FOV). To better extract the useful signal from hydrometeors, surface land emissivity needs to be determined and filtered from the satellite-measured brightness temperatures. Based on the dielectric properties of surface land cover constitutes, Microwave Polarization Differential index (MPDI) is expected to carry the composite effect of surface land properties on land surface emissivity, with a higher MPDI indicating a lower emissivity. This study analyses the dependence of MPDI to soil moisture, vegetation and surface skin temperature over 9 different land surface types. Such analysis is performed using the normalized difference vegetation index (NDVI) from MODIS, the near surface air temperature from the RAP model and ante-precedent precipitation accumulation from the Multi-Radar Multi-Sensor as surrogates for the vegetation, surface skin temperature and shallow layer soil moisture, respectively. This paper provides 1) evaluations of brightness temperature-based MPDI from the TRMM and GPM Microwave Imagers in both raining and non-raining conditions to test the dependence of MPDI to precipitation; 2) comparisons of MPDI categorized into instantly before, during and immediately after selected precipitation events to examine the impact of modest-to-heavy precipitation on the spatial pattern of MPDI; 3) inspections of relationship between MPDI versus rain fraction and rain rate within the satellite sensors FOV to investigate the behaviors of MPDI in varying precipitation conditions; 4) analysis of discrepancies of MPDI over 10.65, 19.35, 37 and 85.8 GHz to identify the sensitivity of MPDS to microwave wavelengths.

Relative Roles of Soil Moisture, Nutrient Supply, Depth, and Mechanical Impedance in Determining Composition and Structure of Wisconsin Prairies

PubMed Central

Wernerehl, Robert W.; Givnish, Thomas J.

2015-01-01

Ecologists have long classified Midwestern prairies based on compositional variation assumed to reflect local gradients in moisture availability. The best known classification is based on Curtis’ continuum index (CI), calculated using the presence of indicator species thought centered on different portions of an underlying moisture gradient. Direct evidence of the extent to which CI reflects differences in moisture availability has been lacking, however. Many factors that increase moisture availability (e.g., soil depth, silt content) also increase nutrient supply and decrease soil mechanical impedance; the ecological effects of the last have rarely been considered in any ecosystem. Decreased soil mechanical impedance should increase the availability of soil moisture and nutrients by reducing the root costs of retrieving both. Here we assess the relative importance of soil moisture, nutrient supply, and mechanical impedance in determining prairie composition and structure. We used leaf δ13C of C3 plants as a measure of growing-season moisture availability, cation exchange capacity (CEC) x soil depth as a measure of mineral nutrient availability, and penetrometer data as a measure of soil mechanical impedance. Community composition and structure were assessed in 17 remnant prairies in Wisconsin which vary little in annual precipitation. Ordination and regression analyses showed that δ13C increased with CI toward “drier” sites, and decreased with soil depth and % silt content. Variation in δ13C among remnants was 2.0‰, comparable to that along continental gradients from ca. 500–1500 mm annual rainfall. As predicted, LAI and average leaf height increased significantly toward “wetter” sites. CI accounted for 54% of compositional variance but δ13C accounted for only 6.2%, despite the strong relationships of δ13C to CI and CI to composition. Compositional variation reflects soil fertility and mechanical impedance more than moisture availability. This study is the first to quantify the effects of soil mechanical impedance on community ecology. PMID:26368936

Relative Roles of Soil Moisture, Nutrient Supply, Depth, and Mechanical Impedance in Determining Composition and Structure of Wisconsin Prairies.

PubMed

Wernerehl, Robert W; Givnish, Thomas J

2015-01-01

Ecologists have long classified Midwestern prairies based on compositional variation assumed to reflect local gradients in moisture availability. The best known classification is based on Curtis' continuum index (CI), calculated using the presence of indicator species thought centered on different portions of an underlying moisture gradient. Direct evidence of the extent to which CI reflects differences in moisture availability has been lacking, however. Many factors that increase moisture availability (e.g., soil depth, silt content) also increase nutrient supply and decrease soil mechanical impedance; the ecological effects of the last have rarely been considered in any ecosystem. Decreased soil mechanical impedance should increase the availability of soil moisture and nutrients by reducing the root costs of retrieving both. Here we assess the relative importance of soil moisture, nutrient supply, and mechanical impedance in determining prairie composition and structure. We used leaf δ13C of C3 plants as a measure of growing-season moisture availability, cation exchange capacity (CEC) x soil depth as a measure of mineral nutrient availability, and penetrometer data as a measure of soil mechanical impedance. Community composition and structure were assessed in 17 remnant prairies in Wisconsin which vary little in annual precipitation. Ordination and regression analyses showed that δ13C increased with CI toward "drier" sites, and decreased with soil depth and % silt content. Variation in δ13C among remnants was 2.0‰, comparable to that along continental gradients from ca. 500-1500 mm annual rainfall. As predicted, LAI and average leaf height increased significantly toward "wetter" sites. CI accounted for 54% of compositional variance but δ13C accounted for only 6.2%, despite the strong relationships of δ13C to CI and CI to composition. Compositional variation reflects soil fertility and mechanical impedance more than moisture availability. This study is the first to quantify the effects of soil mechanical impedance on community ecology.

Topographic soil wetness index derived from combined Alaska-British Columbia datasets for the Gulf of Alaska region

NASA Astrophysics Data System (ADS)

D'Amore, D. V.; Biles, F. E.

2016-12-01

The flow of water is often highlighted as a priority in land management planning and assessments related to climate change. Improved measurement and modeling of soil moisture is required to develop predictive estimates for plant distributions, soil moisture, and snowpack, which all play important roles in ecosystem planning in the face of climate change. Drainage indexes are commonly derived from GIS tools with digital elevation models. Soil moisture classes derived from these tools are useful digital proxies for ecosystem functions associated with the concentration of water on the landscape. We developed a spatially explicit topographically derived soil wetness index (TWI) across the perhumid coastal temperate rainforest (PCTR) of Alaska and British Columbia. Developing applicable drainage indexes in complex terrain and across broad areas required careful application of the appropriate DEM, caution with artifacts in GIS covers and mapping realistic zones of wetlands with the indicator. The large spatial extent of the model has facilitated the mapping of forest habitat and the development of water table depth mapping in the region. A key element of the TWI is the merging of elevation datasets across the US-Canada border where major rivers transect the international boundary. The unified TWI allows for seemless mapping across the international border and unified ecological applications. A python program combined with the unified DEM allows end users to quickly apply the TWI to all areas of the PCTR. This common platform can facilitate model comparison and improvements to local soil moisture conditions, generation of streamflow, and ecological site conditions. In this presentation we highlight the application of the TWI for mapping risk factors related to forest decline and the development of a regional water table depth map. Improved soil moisture maps are critical for deriving spatial models of changes in soil moisture for both plant growth and streamflow across future climate conditions.

Performance of vegetation indices from Landsat time series in deforestation monitoring

NASA Astrophysics Data System (ADS)

Schultz, Michael; Clevers, Jan G. P. W.; Carter, Sarah; Verbesselt, Jan; Avitabile, Valerio; Quang, Hien Vu; Herold, Martin

2016-10-01

The performance of Landsat time series (LTS) of eight vegetation indices (VIs) was assessed for monitoring deforestation across the tropics. Three sites were selected based on differing remote sensing observation frequencies, deforestation drivers and environmental factors. The LTS of each VI was analysed using the Breaks For Additive Season and Trend (BFAST) Monitor method to identify deforestation. A robust reference database was used to evaluate the performance regarding spatial accuracy, sensitivity to observation frequency and combined use of multiple VIs. The canopy cover sensitive Normalized Difference Fraction Index (NDFI) was the most accurate. Among those tested, wetness related VIs (Normalized Difference Moisture Index (NDMI) and the Tasselled Cap wetness (TCw)) were spatially more accurate than greenness related VIs (Normalized Difference Vegetation Index (NDVI) and Tasselled Cap greenness (TCg)). When VIs were fused on feature level, spatial accuracy was improved and overestimation of change reduced. NDVI and NDFI produced the most robust results when observation frequency varies.

An analysis of soil moisture and vegetation conditions during a period of rapid subseasonal oscillations between drought and pluvials over Texas during 2015

NASA Astrophysics Data System (ADS)

Hunt, E. D.; Otkin, J.; Zhong, Y.

2017-12-01

Flash drought, characterized by the rapid onset of abnormally warm and dry weather conditions that leads to the rapid depletion of soil moisture and rapid deteriorations in vegetation health. Flash recovery, on the other hand, is characterized by a period(s) of intense precipitation where drought conditions are quickly eradicated and may be replaced by saturated soils and flooding. Both flash drought and flash recovery are closely tied to the rapid depletion or recharge of root zone soil moisture; therefore, soil moisture observations are very useful for monitoring their evolution. However, in-situ soil moisture observations tend to be concentrated over small regions and thus other methods are needed to provide a spatially continuous depiction of soil moisture conditions. One option is to use top soil moisture retrievals from the Soil Moisture Active Passive (SMAP) sensor. SMAP provides routine coverage of surface soil moisture (0-5 cm) over most of the globe, including the timespan (2015) and region of interest (Texas) that are the focus of our study. This region had an unusual sequence of flash recovery-flash drought-flash recovery during an six-month period during 2015 that provides a valuable case study of rapid transitions between extreme soil moisture conditions. During this project, SMAP soil moisture retrievals are being used in combination with in-situ soil moisture observations and assimilated into the Land Information System (LIS) to provide information about soil moisture content. LIS also provides greenness vegetation fraction data over large regions. The relationship between soil moisture and vegetation conditions and the response of the vegetation to the rapidly changing conditions are also assessed using the satellite thermal infrared based Evaporative Stress Index (ESI) that depicts anomalies in evapotranspiration, along with other vegetation datasets (leaf area index, greenness fraction) derived using MODIS observations. Preliminary results with the Noah land surface model (inside of LIS) shows that it broadly captured the soil moisture evolution during the 2015 sequence but tended to underestimate the magnitude of soil moisture anomalies. The ESI also showed negative anomalies during the drought. These and other results will be presented at the annual meeting.

Antecedent Wetness Conditions based on ERS scatterometer data in support to rainfall-runoff modeling

NASA Astrophysics Data System (ADS)

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

2009-04-01

Despite of its small volume compared to other components of the hydrologic cycle, the soil moisture is of fundamental importance to many hydrological, meteorological, biological and biogeochemical processes. For storm rainfall-runoff modeling the estimation of the Antecedent Wetness Conditions (AWC) is one of the most important issues to determine the hydrological response. In this context, this study investigates the potential of the scatterometer on board of the ERS satellites for the assessment of soil wetness conditions at two different scales. The satellite soil moisture data set, available from 1992, is downloaded from the ERS/METOP Soil Moisture archive located at http://www.ipf.tuwien.ac.at/radar/index.php?go=ascat. At the local scale, the scatterometer-derived soil wetness index (SWI) data (Wagner, W., Lemoine, G., and Rott, H., 1999. A Method for Estimating Soil Moisture from ERS Scatterometer and Soil Data. Remote Sensing of Environment, 70, 191-207) have been compared with two in-situ soil moisture data sets. At the catchment scale, the reliability of the SWI to estimate the AWC has been tested considering its relationship with the soil potential maximum retention parameter, S, of the Soil Conservation Service-Curve Number (SCS-CN) method for abstraction. The parameter S has been derived by considering several flood events occurred from 1992 to 2005 in different catchments of central Italy. The performance of two Antecedent Precipitation Indices (API) and one Base Flow Index (BFI), usually employed in the hydrological practice for the AWC assessment, have been compared with the SWI. The obtained results show a high accuracy of the SWI for the estimation of wetness conditions both at the local and catchment scale despite of the complex orography of the investigated areas (Brocca, L., Melone, F., Moramarco, T., Morbidelli, R., 2009. Antecedent wetness conditions based on ERS scatterometer data. Journal of Hydrology, 364 (1-2), 73-87). At the local scale, the SWI has been found quite reliable in representing the soil moisture at layer depth of 15 cm with average correlation coefficient equal to 0.81 and a root mean square error of ~ 0.04 m3/m3. In terms of AWC assessment at the catchment scale, the SWI has been found highly correlated with the observed S parameter with correlation coefficient equal to -0.90. Besides, SWI outperformed both API indices, poorly representative of AWC, and BFI. The methodology delineated in this study can be considered as a simple and entirely new approach to validate the remotely sensed soil moisture estimates at the catchment scale, mainly for coarse resolution sensors as scatterometers and radiometers. The obtained results indirectly reveal the usefulness of the SWI both for flood forecasting applications and for prediction in ungauged basins. Moreover, the correlation of in-situ soil moisture measurements with the SWI reveals the potential of scatterometer data, particularly considering the higher spatial resolution provided by the successor of ERS scatterometer, the Advanced Scatterometer, ASCAT, on board of the meteorological operational platforms, METOP.

Impact of rainfall on the moisture content of large woody fuels

Treesearch

Helen H. Mohr; Thomas A. Waldrop

2013-01-01

This unreplicated case study evaluates the impact of rainfall on large woody fuels over time. We know that one rainfall event may decrease the Keetch-Byram Drought Index, but this study shows no real increase in fuel moisture in 1,000- hour fuels after just one rainfall. Several rain events over time are required for the moisture content of large woody fuels to...

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.

A practical approach for deriving all-weather soil moisture content using combined satellite and meteorological data

NASA Astrophysics Data System (ADS)

Leng, Pei; Li, Zhao-Liang; Duan, Si-Bo; Gao, Mao-Fang; Huo, Hong-Yuan

2017-09-01

Soil moisture has long been recognized as one of the essential variables in the water cycle and energy budget between Earth's surface and atmosphere. The present study develops a practical approach for deriving all-weather soil moisture using combined satellite images and gridded meteorological products. In this approach, soil moisture over the Moderate Resolution Imaging Spectroradiometer (MODIS) clear-sky pixels are estimated from the Vegetation Index/Temperature (VIT) trapezoid scheme in which theoretical dry and wet edges were determined pixel to pixel by China Meteorological Administration Land Data Assimilation System (CLDAS) meteorological products, including air temperature, solar radiation, wind speed and specific humidity. For cloudy pixels, soil moisture values are derived by the calculation of surface and aerodynamic resistances from wind speed. The approach is capable of filling the soil moisture gaps over remaining cloudy pixels by traditional optical/thermal infrared methods, allowing for a spatially complete soil moisture map over large areas. Evaluation over agricultural fields indicates that the proposed approach can produce an overall generally reasonable distribution of all-weather soil moisture. An acceptable accuracy between the estimated all-weather soil moisture and in-situ measurements at different depths could be found with an Root Mean Square Error (RMSE) varying from 0.067 m3/m3 to 0.079 m3/m3 and a slight bias ranging from 0.004 m3/m3 to -0.011 m3/m3. The proposed approach reveals significant potential to derive all-weather soil moisture using currently available satellite images and meteorological products at a regional or global scale in future developments.

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.

Runoff generation processes and fraction of young water for streamflow and groundwater in a pre-alpine forested catchment

NASA Astrophysics Data System (ADS)

Zuecco, Giulia; Penna, Daniele; van Meerveld, Ilja; Borga, Marco

2017-04-01

Understanding of runoff generation mechanisms and storage dynamics is needed for sustainable management of water resources, particularly in catchments characterized by marked seasonality in rainfall. However, temporal and spatial variability of hydrological processes can hinder a detailed comprehension of catchment functioning. In this study, we use hydrometric data and stable isotope data from a 2-ha forested catchment in the Italian pre-Alps to i) identify seasonal changes in runoff generation, ii) determine the factors that affect the hysteretic relations between streamflow and soil moisture and between streamflow and shallow groundwater, and iii) estimate the fraction of young water in stream water and shallow groundwater. Streamflow, soil moisture and groundwater levels were measured continuously between August 2012 and December 2015. Soil moisture was measured at 0-30 cm depth by four time domain reflectometers installed at different locations along a riparian-hillslope transect. Depth to water table was measured in two piezometers installed at a depth of 2.0 and 1.8 m in the riparian zone. Water samples for isotopic analysis were taken monthly from bulk precipitation and approximately biweekly from stream water and groundwater. The relations between streamflow (independent variable), soil moisture and depth to water table (dependent variables) were analyzed by computing a hysteresis index that provides information on the direction, the extent and the shape of the loops for 103 rainfall-runoff events. The temporal variability of the hysteresis index was related to event characteristics (mean and maximum rainfall intensity, rainfall amount and total stormflow) and antecedent soil moisture conditions. We observed threshold-like relations between stormflow and the sum of rainfall and the antecedent soil moisture index and an exponential relation between the change in groundwater level and stormflow. Clockwise hysteretic relations were common between streamflow and riparian soil moisture, suggesting quick contributions from shallow soil layers in the riparian zone to streamflow. The relations between streamflow and hillslope soil moisture and between streamflow and depth to water table in the riparian zone varied seasonally, with clockwise loops being typical for large rainfall events in autumn and anti-clockwise hysteresis being more common in spring and summer. This indicates that hillslope soil water and riparian groundwater dynamics and their contribution to stormflow varied seasonally and depended on event size and antecedent moisture conditions. There was a marked seasonal variability in the isotopic composition of precipitation but a much more damped variability in the isotopic signature of stream water and groundwater. A sine curve was fitted to the seasonal variation in isotopic composition of weighted precipitation, stream water and groundwater to estimate the fraction of young water in stream water and groundwater. The fraction of young water in streamflow was about 14% when considering baseflow conditions only (23% using the entire isotopic dataset). This was similar to the fraction of young water in riparian groundwater. Keywords: runoff generation; hysteresis; isotopes; young water fraction; forested catchment.

Projected climatic changes on drought conditions over Spain

NASA Astrophysics Data System (ADS)

García-Valdecasas Ojeda, Matilde; Quishpe-Vásquez, César; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

2017-04-01

In a context of global warming, the evapotranspiration processes will have a strong influence on drought severity. For this reason, the Standardized Precipitation Evapotranspiration Index (SPEI) was computed at different timescales in order to explore the projected drought changes for the main watersheds in Spain. For that, the Weather Research and Forecasting (WRF) model has been used in order to obtain current (1980-2010) and future (2021-2050 and 2071-2100) climate output fields. WRF model was used over a domain that spans the Iberian Peninsula with a spatial resolution of 0.088°, and nested in the coarser 0.44° EURO-CORDEX domain, and driving by the global bias-corrected climate model output data from version 1 of NCAR's Community Earth System Model (CESM1), using two different Representative Concentration Pathway (RCP) scenarios: RCP 4.5 and RCP 8.5. Besides, to examine the behavior of this drought index, a comparison with the Standardized Precipitation Index (SPI), which does not consider the evapotranspiration effects, was also performed. Additionally the relationship between the SPEI index and the soil moisture has also been analyzed. The results of this study suggest an increase in the severity and duration of drought, being larger when the SPEI index is used to define drought events. This fact confirms the relevance of taking into account the evapotranspiration processes to detect future drought events. The results also show a noticeable relationship between the SPEI and the simulated soil moisture content, which is more significant at higher timescales. Keywords: Drought, SPEI, SPI, Climatic change, Projections, WRF. Acknowledgements: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

In vitro starch digestibility and predicted glycemic index of microwaved and conventionally baked pound cake.

PubMed

Sánchez-Pardo, María Elena; Ortiz-Moreno, Alicia; Mora-Escobedo, Rosalva; Necoechea-Mondragón, Hugo

2007-09-01

The present study compares the effect of baking process (microwave vs conventional oven) on starch bioavailability in fresh pound cake crumbs and in crumbs from pound cake stored for 8 days. Proximal chemical analysis, resistant starch (RS), retrograded starch (RS3) and starch hydrolysis index (HI) were evaluated. The empirical formula suggested by Granfeldt was used to determine the predicted glycemic index (pGI). Pound cake, one of Mexico's major bread products, was selected for analysis because the quality defects often associated with microwave baking might be reduced with the use of high-fat, high-moisture, batted dough. Differences in product moisture, RS and RS3 were observed in fresh microwave-baked and conventionally baked pound cake. RS3 increased significantly in conventionally baked products stored for 8 days at room temperature, whereas no significantly changes in RS3 were observed in the microwaved product. HI values for freshly baked and stored microwaved product were 59 and 62%, respectively (P > 0.05), whereas the HI value for the conventionally baked product decreased significantly after 8 days of storage. A pound cake with the desired HI and GI characteristics might be obtained by adjusting the microwave baking process.

Fire danger index efficiency as a function of fuel moisture and fire behavior.

PubMed

Torres, Fillipe Tamiozzo Pereira; Romeiro, Joyce Machado Nunes; Santos, Ana Carolina de Albuquerque; de Oliveira Neto, Ricardo Rodrigues; Lima, Gumercindo Souza; Zanuncio, José Cola

2018-08-01

Assessment of the performance of forest fire hazard indices is important for prevention and management strategies, such as planning prescribed burnings, public notifications and firefighting resource allocation. The objective of this study was to evaluate the performance of fire hazard indices considering fire behavior variables and susceptibility expressed by the moisture of combustible material. Controlled burns were carried out at different times and information related to meteorological conditions, characteristics of combustible material and fire behavior variables were recorded. All variables analyzed (fire behavior and fuel moisture content) can be explained by the prediction indices. The Brazilian EVAP/P showed the best performance, both at predicting moisture content of the fuel material and fire behavior variables, and the Canadian system showed the best performance to predicting the rate of spread. The coherence of the correlations between the indices and the variables analyzed makes the methodology, which can be applied anywhere, important for decision-making in regions with no records or with only unreliable forest fire data. Copyright © 2018 Elsevier B.V. All rights reserved.

Wetting and drying of soil in response to precipitation: Data analysis, modeling, and forecasting

USGS Publications Warehouse

Basak, Aniruddha; Kulkarni, Chinmay; Schmidt, Kevin M.; Mengshoel, Ole

2016-01-01

This paper investigates methods to analyze and forecast soil moisture time series. We extend an existing Antecedent Water Index (AWI) model, which expresses soil moisture as a function of time and rainfall. Unfortunately, the existing AWI model does not forecast effectively for time periods beyond a few hours. To overcome this limitation, we develop a novel AWI-based model. Our model accumulates rainfall over a time interval and can fit a diverse range of wetting and drying curves. In addition, parameters in our model reflect hydrologic redistribution processes of gravity and suction.We validate our models using experimental soil moisture and rainfall time series data collected from steep gradient post-wildfire sites in Southern California, where rapid landscape change was observed in response to small to moderate rain storms. We found that our novel model fits the data for three distinct soil textures, occurring at different depths below the ground surface (5, 15, and 30 cm). Our model also successfully forecasts soil moisture trends, such as drying and wetting rate.

Flavanols, proanthocyanidins and antioxidant activity changes during cocoa (Theobroma cacao L.) roasting as affected by temperature and time of processing.

PubMed

Ioannone, F; Di Mattia, C D; De Gregorio, M; Sergi, M; Serafini, M; Sacchetti, G

2015-05-01

The effect of roasting on the content of flavanols and proanthocyanidins and on the antioxidant activity of cocoa beans was investigated. Cocoa beans were roasted at three temperatures (125, 135 and 145 °C), for different times, to reach moisture contents of about 2 g 100 g(-1). Flavanols and proanthocyanidins were determined, and the antioxidant activity was tested by total phenolic index (TPI), ferric reducing antioxidant power (FRAP) and total radical trapping antioxidant parameter (TRAP) methods. The rates of flavanol and total proanthocyanidin loss increased with roasting temperatures. Moisture content of the roasted beans being equal, high temperature-short time processes minimised proanthocyanidins loss. Moisture content being equal, the average roasting temperature (135 °C) determined the highest TPI and FRAP values and the highest temperature (145 °C) determined the lowest TPI values. Moisture content being equal, low temperature-long time roasting processes maximised the chain-breaking activity, as determined by the TRAP method. Copyright © 2014 Elsevier Ltd. All rights reserved.

Enhanced Soil Moisture Initialization Using Blended Soil Moisture Product and Regional Optimization of LSM-RTM Coupled Land Data Assimilation System.

NASA Astrophysics Data System (ADS)

Nair, A. S.; Indu, J.

2017-12-01

Prediction of soil moisture dynamics is high priority research challenge because of the complex land-atmosphere interaction processes. Soil moisture (SM) plays a decisive role in governing water and energy balance of the terrestrial system. An accurate SM estimate is imperative for hydrological and weather prediction models. Though SM estimates are available from microwave remote sensing and land surface model (LSM) simulations, it is affected by uncertainties from several sources during estimation. Past studies have generally focused on land data assimilation (DA) for improving LSM predictions by assimilating soil moisture from single satellite sensor. This approach is limited by the large time gap between two consequent soil moisture observations due to satellite repeat cycle of more than three days at the equator. To overcome this, in the present study, we have performed DA using ensemble products from the soil moisture operational product system (SMOPS) blended soil moisture retrievals from different satellite sensors into Noah LSM. Before the assimilation period, the Noah LSM is initialized by cycling through seven multiple loops from 2008 to 2010 forcing with Global data assimilation system (GDAS) data over the Indian subcontinent. We assimilated SMOPS into Noah LSM for a period of two years from 2010 to 2011 using Ensemble Kalman Filter within NASA's land information system (LIS) framework. Results show that DA has improved Noah LSM prediction with a high correlation of 0.96 and low root mean square difference of 0.0303 m3/m3 (figure 1a). Further, this study has also investigated the notion of assimilating microwave brightness temperature (Tb) as a proxy for SM estimates owing to the close proximity of Tb and SM. Preliminary sensitivity analysis show a strong need for regional parameterization of radiative transfer models (RTMs) to improve Tb simulation. Towards this goal, we have optimized the forward RTM using swarm optimization technique for direct Tb assimilation. The results indicate an improvement in Tb simulations based on the multi polarization difference index approach with a correlation of 0.81 (figure 1b (e)) and bias of < 5 K with respect to the SMOS Tb.

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

Adjusting Spectral Indices for Spectral Response Function Differences of Very High Spatial Resolution Sensors Simulated from Field Spectra

PubMed Central

Cundill, Sharon L.; van der Werff, Harald M. A.; van der Meijde, Mark

2015-01-01

The use of data from multiple sensors is often required to ensure data coverage and continuity, but differences in the spectral characteristics of sensors result in spectral index values being different. This study investigates spectral response function effects on 48 spectral indices for cultivated grasslands using simulated data of 10 very high spatial resolution sensors, convolved from field reflectance spectra of a grass covered dike (with varying vegetation condition). Index values for 48 indices were calculated for original narrow-band spectra and convolved data sets, and then compared. The indices Difference Vegetation Index (DVI), Global Environmental Monitoring Index (GEMI), Enhanced Vegetation Index (EVI), Modified Soil-Adjusted Vegetation Index (MSAVI2) and Soil-Adjusted Vegetation Index (SAVI), which include the difference between the near-infrared and red bands, have values most similar to those of the original spectra across all 10 sensors (1:1 line mean 1:1R2 > 0.960 and linear trend mean ccR2 > 0.997). Additionally, relationships between the indices’ values and two quality indicators for grass covered dikes were compared to those of the original spectra. For the soil moisture indicator, indices that ratio bands performed better across sensors than those that difference bands, while for the dike cover quality indicator, both the choice of bands and their formulation are important. PMID:25781511

Antecedent wetness conditions based on ERS scatterometer data

NASA Astrophysics Data System (ADS)

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

2009-01-01

SummarySoil moisture is widely recognized as a key parameter in environmental processes mainly for the role of rainfall partitioning into runoff and infiltration. Therefore, for storm rainfall-runoff modeling the estimation of the antecedent wetness conditions ( AWC) is one of the most important aspect. In this context, this study investigates the potential of scatterometer on board of the ERS satellites for the assessment of wetness conditions in three Tiber sub-catchments (Central Italy), of which one includes an experimental area for soil moisture monitoring. The satellite soil moisture data are taken from the ERS/METOP soil moisture archive. First, the scatterometer-derived soil wetness index ( SWI) data are compared with two on-site soil moisture data sets acquired by different methodologies on areas of different extension ranging from 0.01 km 2 to ˜60 km 2. Moreover, the reliability of SWI to estimate the AWC at a catchment scale is investigated considering the relationship between SWI and the soil potential maximum retention parameter, S, of the Soil Conservation Service-Curve Number (SCS-CN) method for abstraction. Several flood events occurred from 1992 to 2005 are selected for this purpose. Specifically, the performance of the SWI for S estimation is compared with two antecedent precipitation indices ( API) and one base flow index ( BFI). The S values obtained through the observed direct runoff volume and rainfall depth are used as benchmark. Results show the great reliability of the SWI for the estimation of wetness conditions both at the plot and catchment scale despite the complex orography of the investigated areas. As far as the comparison with on site soil moisture data set is concerned, the SWI is found quite reliable in representing the soil moisture at layer depth of 15 cm, with a mean correlation coefficient equal to 0.81. The characteristic time length parameter variations, as expected, is depended on soil type, with values in accordance with previous studies. In terms of AWC assessment at catchment scale, based on selected flood events, the SWI is found highly correlated with the observed maximum potential retention of the SCS-CN method with a correlation coefficient R equal to -0.90. Besides, SWI in representing the AWC of the three investigated catchments, outperformed both API indices, poorly representative of AWC, and BFI. Finally, the classical SCS-CN method applied for direct runoff depth estimation, where S is assessed by SWI, provided good performance with a percentage error not exceeding ˜25% for 80% of investigated rainfall-runoff events.

A MODIS-based vegetation index climatology

USDA-ARS?s Scientific Manuscript database

Our motivation here is to provide information for the NASA Soil Moisture Active Passive (SMAP) satellite soil moisture retrieval algorithms (launch in 2014). Vegetation attenuates the signal and the algorithms must correct for this effect. One approach is to use data that describes the canopy water ...

Flow-specific physical properties of coconut flours

NASA Astrophysics Data System (ADS)

Manikantan, Musuvadi R.; Kingsly Ambrose, Rose P.; Alavi, Sajid

2015-10-01

Coconut milk residue and virgin coconut oil cake are important co-products of virgin coconut oil that are used in the animal feed industry. Flour from these products has a number of potential human health benefits and can be used in different food formulations. The objective of this study was to find out the flow-specific physical properties of coconut flours at three moisture levels. Coconut milk residue flour with 4.53 to 8.18% moisture content (w.b.) had bulk density and tapped density of 317.37 to 312.65 and 371.44 to 377.23 kg m-3, respectively; the corresponding values for virgin coconut oil cake flour with 3.85 to 7.98% moisture content (wet basis) were 611.22 to 608.68 and 663.55 to 672.93 kg m-3, respectively. The compressibility index and Hausner ratio increased with moisture. The angle of repose increased with moisture and ranged from 34.12 to 36.20 and 21.07 to 23.82° for coconut milk residue flour and virgin coconut oil cake flour, respectively. The coefficient of static and rolling friction increased with moisture for all test surfaces, with the plywood offering more resistance to flow than other test surfaces. The results of this study will be helpful in designing handling, flow, and processing systems for coconut milk residue and virgin coconut oil cake flours.

[Effect of the harvest season on the composition of raw and fermented cotyledons of 2 varieties of cacao and shell fractions].

PubMed

de Dios Alvarado, J; Villacís, F E; Zamora, G F

1983-06-01

A study was carried out wherein during the period August 1979 to January 1980, samples of raw and fermented cacao were analyzed monthly. These included two varieties: Arriba, taken from a farm in "Quevedo", and the EET-19, grown in "Pichilingüe" by the Instituto Nacional de Investigaciones Agropecuarias (INIAP). Taking the ear of cacao as a basis, the weight of its main parts was determined. The proximal composition was established in the cotyledons, with significant statistical differences in regard to moisture, protein, and ether extract content according to the month of harvest. As to the fermentation process, differences in moisture, ether extract and ash content were detected; differences in the ether extract and ash content were found between the two varieties. The fat extracted from the cotyledons presented different iodine, saponification and acidity index values between the raw and fermented samples, but none were determined between the varieties; as far as the month of harvest is concerned, differences in the acidity index were observed. The percentage composition of the main fatty acids is reported (palmitic, stearic, oleic, and linoleic acids). In order to suggest possible industrial ways of utilizing the cacao shell by-product which is discarded by the shelling machine, the chemical characteristics of five fractions were determined based on the functioning of the shelling machine. The moisture, protein, ether extract, ash, crude fiber, theobromine, and caffeine contents varied among the fractions, and it was dependent on the broken "nibs" content. Differences in the protein, ether extract, and ash content, according to the months of production, were found. Obviously, the high fat content in fractions A (fine dust) and B (fine ground), which varied from 30 to 11 g/100 g, merits its extraction; the remainder meal has a valuable protein and alkaloid content. The chemical characteristics of the fat extracted from the shell of two fractions were similar to the fat extracted from the cotyledons.

Regional moisture balance control of landslide motion: implications for landslide forecasting in a changing climate

USGS Publications Warehouse

Coe, Jeffrey A.

2012-01-01

I correlated 12 years of annual movement of 18 points on a large, continuously moving, deep-seated landslide with a regional moisture balance index (moisture balance drought index, MBDI). I used MBDI values calculated from a combination of historical precipitation and air temperature data from A.D. 1895 to 2010, and downscaled climate projections using the Intergovernmental Panel on Climate Change A2 emissions scenario for 2011–2099. At the landslide, temperature is projected to increase ~0.5 °C/10 yr between 2011 and 2099, while precipitation decreases at a rate of ~2 mm/10 yr. Landslide movement correlated with the MBDI with integration periods of 12 and 48 months. The correlation between movement and MBDI suggests that the MBDI functions as a proxy for groundwater pore pressures and landslide mobility. I used the correlation to forecast decreasing landslide movement between 2011 and 2099, with the head of the landslide expected to stop moving in the mid-21st century. The MBDI, or a similar moisture balance index that accounts for evapotranspiration, has considerable potential as a tool for forecasting the magnitude of ongoing deep-seated landslide movement, and for assessing the onset or likelihood of regional, deep-seated landslide activity.

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.

Third generation snacks manufactured from orange by-products: physicochemical and nutritional characterization.

PubMed

Tovar-Jiménez, Xochitl; Caro-Corrales, José; Gómez-Aldapa, Carlos A; Zazueta-Morales, José; Limón-Valenzuela, Víctor; Castro-Rosas, Javier; Hernández-Ávila, Juan; Aguilar-Palazuelos, Ernesto

2015-10-01

A mixture of orange vesicle flour, commercial nixtamalized corn flour and potato starch was extruded using a Brabender Laboratory single screw extruder (2:1 L/D). The resulting pellets were expanded by microwaves. Expansion index, bulk density, penetration force, carotenoid content, and dietary fiber were measured for this third-generation snack and optimum production conditions were estimated. Response surface methodology was applied using a central composite rotatable experimental design to evaluate the effect of moisture content and extrusion temperature. Temperature mainly affected the expansion index, bulk density and penetration force, while carotenoids content was affected by moisture content. Surface overlap was used to identify optimum processing conditions: temperature: 128-130 °C; moisture content: 22-24 %. Insoluble dietary fiber decreased and soluble dietary fiber increased after extrusion.

A Drought Cyberinfrastructure System for Improving Water Resource Management and Policy Making

NASA Astrophysics Data System (ADS)

AghaKouchak, Amir

2015-04-01

Development of reliable monitoring and prediction indices and tools are fundamental to drought preparedness, management, and response decision making. This presentation provides an overview of the Global Integrated Drought Monitoring and Prediction System (GIDMaPS) which offers near real-time drought information using both remote sensing observations and model simulations. Designed as a cyberinfrastructure system, GIDMaPS provides drought information based on a wide range of model simulations and satellite observations from different space agencies. Numerous indices have been developed for drought monitoring based on various indicator variables (e.g., precipitation, soil moisture, water storage). Defining droughts based on a single variable (e.g., precipitation, soil moisture or runoff) may not be sufficient for reliable risk assessment and decision making. GIDMaPS provides drought information based on multiple indices including Standardized Precipitation Index (SPI), Standardized Soil Moisture Index (SSI) and the Multivariate Standardized Drought Index (MSDI) which combines SPI and SSI probabilistically. In other words, MSDI incorporates the meteorological and agricultural drought conditions for overall characterization of droughts, and better management and distribution of water resources among and across different users. The seasonal prediction component of GIDMaPS is based on a persistence model which requires historical data and near-past observations. The seasonal drought prediction component is designed to provide drought information for water resource management, and short-term decision making. In this presentation, both monitoring and prediction components of GIDMaPS will be discussed, and the results from several major droughts including the 2013 Namibia, 2012-2013 United States, 2011-2012 Horn of Africa, and 2010 Amazon Droughts will be presented. The presentation will highlight how this drought cyberinfrastructure system can be used to improve water resource management in California. Furthermore, the presentation provides an overview of the information farmers need for better decision making and how GIDMaPS can be used to improve decision making and reducing drought impacts. Further Reading Hao Z., AghaKouchak A., Nakhjiri N., Farahmand A., 2014, Global Integrated Drought Monitoring and Prediction System, Scientific Data, 1:140001, 1-10, doi: 10.1038/sdata.2014.1. Momtaz F., Nakhjiri N., AghaKouchak A., 2014, Toward a Drought Cyberinfrastructure System, Eos, Transactions American Geophysical Union, 95(22), 182-183, doi:10.1002/2014EO220002. AghaKouchak A., 2014, A Baseline Probabilistic Drought Forecasting Framework Using Standardized Soil Moisture Index: Application to the 2012 United States Drought, Hydrology and Earth System Sciences, 18, 2485-2492, doi: 10.5194/hess-18-2485-2014.

The 2000 fire season: lightning-caused fires.

Treesearch

Miriam L. Rorig; Sue A. Ferguson

2002-01-01

A large number of lightning-caused fires burned across the western United States during the summer of 2000. In a previous study, the authors determined that a simple index of low-level moisture (85-kPa dewpoint depression) and instability (85–50-kPa temperature difference) from the Spokane, Washington, upper-air soundings was very useful for indicating the likelihood...

An experimental operative system for shallow landslide and flash flood warning based on rainfall thresholds and soil moisture modelling

NASA Astrophysics Data System (ADS)

Brigandı, G.; Aronica, G. T.; Basile, G.; Pasotti, L.; Panebianco, M.

2012-04-01

On November 2011 a thunderstorms became almost exceptional over the North-East part of the Sicily Region (Italy) producing local heavy rainfall, mud-debris flow and flash flooding. The storm was concentrated on the Tyrrhenian sea coast near the city of Barcellona within the Longano catchment. Main focus of the paper is to present an experimental operative system for alerting extreme hydrometeorological events by using a methodology based on the combined use of rainfall thresholds, soil moisture indexes and quantitative precipitation forecasting. As matter of fact, shallow landslide and flash flood warning is a key element to improve the Civil Protection achievements to mitigate damages and safeguard the security of people. It is a rather complicated task, particularly in those catchments with flashy response where even brief anticipations are important and welcomed. It is well known how the triggering of shallow landslides is strongly influenced by the initial soil moisture conditions of catchments. Therefore, the early warning system here applied is based on the combined use of rainfall thresholds, derived both for flash flood and for landslide, and soil moisture conditions; the system is composed of several basic component related to antecedent soil moisture conditions, real-time rainfall monitoring and antecedent rainfall. Soil moisture conditions were estimated using an Antecedent Precipitation Index (API), similar to this widely used for defining soil moisture conditions via Antecedent Moisture conditions index AMC. Rainfall threshold for landslides were derived using historical and statistical analysis. Finally, rainfall thresholds for flash flooding were derived using an Instantaneous Unit Hydrograph based lumped rainfall-runoff model with the SCS-CN routine for net rainfall. After the implementation and calibration of the model, a testing phase was carried out by using real data collected for the November 2001 event in the Longano catchment. Moreover, in order to test the capability of the system to forecast thise event, Quantitative Precipitation Forecasting provided by the SILAM (Sicily Limited Area Model), a meteorological model run by SIAS (Sicilian Agrometeorological Service) with a forecast horizon up to 144 hours, have been used to run the system.

Evaluation of different approaches for identifying optimal sites to predict mean hillslope soil moisture content

NASA Astrophysics Data System (ADS)

Liao, Kaihua; Zhou, Zhiwen; Lai, Xiaoming; Zhu, Qing; Feng, Huihui

2017-04-01

The identification of representative soil moisture sampling sites is important for the validation of remotely sensed mean soil moisture in a certain area and ground-based soil moisture measurements in catchment or hillslope hydrological studies. Numerous approaches have been developed to identify optimal sites for predicting mean soil moisture. Each method has certain advantages and disadvantages, but they have rarely been evaluated and compared. In our study, surface (0-20 cm) soil moisture data from January 2013 to March 2016 (a total of 43 sampling days) were collected at 77 sampling sites on a mixed land-use (tea and bamboo) hillslope in the hilly area of Taihu Lake Basin, China. A total of 10 methods (temporal stability (TS) analyses based on 2 indices, K-means clustering based on 6 kinds of inputs and 2 random sampling strategies) were evaluated for determining optimal sampling sites for mean soil moisture estimation. They were TS analyses based on the smallest index of temporal stability (ITS, a combination of the mean relative difference and standard deviation of relative difference (SDRD)) and based on the smallest SDRD, K-means clustering based on soil properties and terrain indices (EFs), repeated soil moisture measurements (Theta), EFs plus one-time soil moisture data (EFsTheta), and the principal components derived from EFs (EFs-PCA), Theta (Theta-PCA), and EFsTheta (EFsTheta-PCA), and global and stratified random sampling strategies. Results showed that the TS based on the smallest ITS was better (RMSE = 0.023 m3 m-3) than that based on the smallest SDRD (RMSE = 0.034 m3 m-3). The K-means clustering based on EFsTheta (-PCA) was better (RMSE <0.020 m3 m-3) than these based on EFs (-PCA) and Theta (-PCA). The sampling design stratified by the land use was more efficient than the global random method. Forty and 60 sampling sites are needed for stratified sampling and global sampling respectively to make their performances comparable to the best K-means method (EFsTheta-PCA). Overall, TS required only one site, but its accuracy was limited. The best K-means method required <8 sites and yielded high accuracy, but extra soil and terrain information is necessary when using this method. The stratified sampling strategy can only be used if no pre-knowledge about soil moisture variation is available. This information will help in selecting the optimal methods for estimation the area mean soil moisture.

Switchgrass growth and effects on biomass accumulation, moisture content, and nutrient removal

USDA-ARS?s Scientific Manuscript database

Temporal patterns of plant growth, composition, and nutrient removal impact development of models for predicting optimal harvest times of switchgrass (Panicum virgatum L.) for bioenergy. Objectives were to characterize seasonal trends in yield, tissue moisture, ash content, leaf area index (LAI), in...

Methods to Calculate the Heat Index as an Exposure Metric in Environmental Health Research

PubMed Central

Bell, Michelle L.; Peng, Roger D.

2013-01-01

Background: Environmental health research employs a variety of metrics to measure heat exposure, both to directly study the health effects of outdoor temperature and to control for temperature in studies of other environmental exposures, including air pollution. To measure heat exposure, environmental health studies often use heat index, which incorporates both air temperature and moisture. However, the method of calculating heat index varies across environmental studies, which could mean that studies using different algorithms to calculate heat index may not be comparable. Objective and Methods: We investigated 21 separate heat index algorithms found in the literature to determine a) whether different algorithms generate heat index values that are consistent with the theoretical concepts of apparent temperature and b) whether different algorithms generate similar heat index values. Results: Although environmental studies differ in how they calculate heat index values, most studies’ heat index algorithms generate values consistent with apparent temperature. Additionally, most different algorithms generate closely correlated heat index values. However, a few algorithms are potentially problematic, especially in certain weather conditions (e.g., very low relative humidity, cold weather). To aid environmental health researchers, we have created open-source software in R to calculate the heat index using the U.S. National Weather Service’s algorithm. Conclusion: We identified 21 separate heat index algorithms used in environmental research. Our analysis demonstrated that methods to calculate heat index are inconsistent across studies. Careful choice of a heat index algorithm can help ensure reproducible and consistent environmental health research. Citation: Anderson GB, Bell ML, Peng RD. 2013. Methods to calculate the heat index as an exposure metric in environmental health research. Environ Health Perspect 121:1111–1119; http://dx.doi.org/10.1289/ehp.1206273 PMID:23934704

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.

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

PubMed Central

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

2016-01-01

Understanding of effects of soil temperature and soil moisture on soil respiration (Rs) under future warming is critical to reduce uncertainty in predictions of feedbacks to atmospheric CO2 concentrations from grassland soil carbon. Intact cores with roots taken from a full factorial, 5-year alpine meadow warming and grazing experiment in the field were incubated at three different temperatures (i.e. 5, 15 and 25°C) with two soil moistures (i.e. 30 and 60% water holding capacity (WHC)) in our study. Another experiment of glucose-induced respiration (GIR) with 4 h of incubation was conducted to determine substrate limitation. Our results showed that high temperature increased Rs and low soil moisture limited the response of Rs to temperature only at high incubation temperature (i.e. 25°C). Temperature sensitivity (Q10) did not significantly decrease over the incubation period, suggesting that substrate depletion did not limit Rs. Meanwhile, the carbon availability index (CAI) was higher at 5°C compared with 15 and 25°C incubation, but GIR increased with increasing temperature. Therefore, our findings suggest that warming-induced decrease in Rs in the field over time may result from a decrease in soil moisture rather than from soil substrate depletion, because warming increased root biomass in the alpine meadow. PMID:27798671

Dust emission parameterization scheme over the MENA region: Sensitivity analysis to soil moisture and soil texture

NASA Astrophysics Data System (ADS)

Gherboudj, Imen; Beegum, S. Naseema; Marticorena, Beatrice; Ghedira, Hosni

2015-10-01

The mineral dust emissions from arid/semiarid soils were simulated over the MENA (Middle East and North Africa) region using the dust parameterization scheme proposed by Alfaro and Gomes (2001), to quantify the effect of the soil moisture and clay fraction in the emissions. For this purpose, an extensive data set of Soil Moisture and Ocean Salinity soil moisture, European Centre for Medium-Range Weather Forecasting wind speed at 10 m height, Food Agricultural Organization soil texture maps, MODIS (Moderate Resolution Imaging Spectroradiometer) Normalized Difference Vegetation Index, and erodibility of the soil surface were collected for the a period of 3 years, from 2010 to 2013. Though the considered data sets have different temporal and spatial resolution, efforts have been made to make them consistent in time and space. At first, the simulated sandblasting flux over the region were validated qualitatively using MODIS Deep Blue aerosol optical depth and EUMETSAT MSG (Meteosat Seciond Generation) dust product from SEVIRI (Meteosat Spinning Enhanced Visible and Infrared Imager) and quantitatively based on the available ground-based measurements of near-surface particulate mass concentrations (PM10) collected over four stations in the MENA region. Sensitivity analyses were performed to investigate the effect of soil moisture and clay fraction on the emissions flux. The results showed that soil moisture and soil texture have significant roles in the dust emissions over the MENA region, particularly over the Arabian Peninsula. An inversely proportional dependency is observed between the soil moisture and the sandblasting flux, where a steep reduction in flux is observed at low friction velocity and a gradual reduction is observed at high friction velocity. Conversely, a directly proportional dependency is observed between the soil clay fraction and the sandblasting flux where a steep increase in flux is observed at low friction velocity and a gradual increase is observed at high friction velocity. The magnitude of the percentage reduction/increase in the sandblasting flux decreases with the increase of the friction velocity for both soil moisture and soil clay fraction. Furthermore, these variables are interdependent leading to a gradual decrease in the percentage increase in the sandblasting flux for higher soil moisture values.

Impact of vegetation feedback at subseasonal & seasonal timescales on precipitation over North America

NASA Astrophysics Data System (ADS)

Kim, Y.; Wang, G.

2006-05-01

Soil moisture-vegetation-precipitation feedbacks tend to enhance soil moisture memory in some areas of the globe, which contributes to the subseasonal and seasonal climate prediction skill. In this study, the impact of vegetation on precipitation over North America is investigated using a coupled land-atmosphere model CAM3- CLM3. The coupled model has been modified to include a predictive vegetation phenology scheme and validated against the MODIS data. Vegetation phenology is modeled by updating the leaf area index (LAI) daily in response to cumulative and concurrent hydrometeorological conditions. First, driven with the climatological SST, a large group of 5-member ensembles of simulations from the late spring and summer to the end of year are generated with the different initial conditions of soil moisture. The impact of initial soil moisture anomalies on subsequent precipitation is examined with the predictive vegetation phenology scheme disabled/enabled ("SM"/"SM_Veg" ensembles). The simulated climate differences between "SM" and "SM_Veg" ensembles represent the role of vegetation in soil moisture-vegetation- precipitation feedback. Experiments in this study focus on how the response of precipitation to initial soil moisture anomalies depends on their characteristics, including the timing, magnitude, spatial coverage and vertical depth, and further how it is modified by the interactive vegetation. Our results, for example, suggest that the impact of late spring soil moisture anomalies is not evident in subsequent precipitation until early summer when local convective precipitation dominates. With the summer wet soil moisture anomalies, vegetation tends to enhance the positive feedback between soil moisture and precipitation, while vegetation tends to suppress such positive feedback with the late spring anomalies. Second, the impact of vegetation feedback is investigated by driving the model with the inter-annually varying monthly SST (1983-1994). With the predictive vegetation phenology disabled/enabled ("SM"/"SM_Veg" ensembles), the simulated climates are compared with the observation. This will present the role of an interactive or predictive vegetation phenology scheme in subseasonal and seasonal climate prediction. Specifically, the extreme climate events such as drought in 1988 and flood in 1993 over the Midwestern United States will be the focus of results analyses.

Land Capability Potential Index (LCPI) and geodatabase for the Lower Missouri River Valley

USGS Publications Warehouse

Chojnacki, Kimberly A.; Struckhoff, Matthew A.; Jacobson, Robert B.

2012-01-01

The Land Capacity Potential Index (LCPI) is a coarse-scale index intended to delineate broad land-capability classes in the Lower Missouri River valley bottom from the Gavins Point Dam near Yankton, South Dakota to the mouth of the Missouri River near St. Louis, Missouri (river miles 811–0). The LCPI provides a systematic index of wetness potential and soil moisture-retention potential of the valley-bottom lands by combining the interactions among water-surface elevations, land-surface elevations, and the inherent moisture-retention capability of soils. A nine-class wetness index was generated by intersecting a digital elevation model for the valley bottom with sloping water-surface elevation planes derived from eight modeled discharges. The flow-recurrence index was then intersected with eight soil-drainage classes assigned to soils units in the digital Soil Survey Geographic (SSURGO) Database (Soil Survey Staff, 2010) to create a 72-class index of potential flow-recurrence and moisture-retention capability of Missouri River valley-bottom lands. The LCPI integrates the fundamental abiotic factors that determine long-term suitability of land for various uses, particularly those relating to vegetative communities and their associated values. Therefore, the LCPI provides a mechanism allowing planners, land managers, landowners, and other stakeholders to assess land-use capability based on the physical properties of the land, in order to guide future land-management decisions. This report documents data compilation for the LCPI in a revised and expanded, 72-class version for the Lower Missouri River valley bottom, and inclusion of additional soil attributes to allow users flexibility in exploring land capabilities.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

Soil moisture is one of the most important keys for understanding regional and global climate systems. Soil moisture is directly related to agricultural processes as well as hydrological processes because soil moisture highly influences vegetation growth and determines water supply in the agroecosystem. Accurate monitoring of the spatiotemporal pattern of soil moisture is important. Soil moisture has been generally provided through in situ measurements at stations. Although field survey from in situ measurements provides accurate soil moisture with high temporal resolution, it requires high cost and does not provide the spatial distribution of soil moisture over large areas. Microwave satellite (e.g., advanced Microwave Scanning Radiometer on the Earth Observing System (AMSR2), the Advanced Scatterometer (ASCAT), and Soil Moisture Active Passive (SMAP)) -based approaches and numerical models such as Global Land Data Assimilation System (GLDAS) and Modern- Era Retrospective Analysis for Research and Applications (MERRA) provide spatial-temporalspatiotemporally continuous soil moisture products at global scale. However, since those global soil moisture products have coarse spatial resolution ( 25-40 km), their applications for agriculture and water resources at local and regional scales are very limited. Thus, soil moisture downscaling is needed to overcome the limitation of the spatial resolution of soil moisture products. In this study, GLDAS soil moisture data were downscaled up to 1 km spatial resolution through the integration of AMSR2 and ASCAT soil moisture data, Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM), and Moderate Resolution Imaging Spectroradiometer (MODIS) data—Land Surface Temperature, Normalized Difference Vegetation Index, and Land cover—using modified regression trees over East Asia from 2013 to 2015. Modified regression trees were implemented using Cubist, a commercial software tool based on machine learning. An optimization based on pruning of rules derived from the modified regression trees was conducted. Root Mean Square Error (RMSE) and Correlation coefficients (r) were used to optimize the rules, and finally 59 rules from modified regression trees were produced. The results show high validation r (0.79) and low validation RMSE (0.0556m3/m3). The 1 km downscaled soil moisture was evaluated using ground soil moisture data at 14 stations, and both soil moisture data showed similar temporal patterns (average r=0.51 and average RMSE=0.041). The spatial distribution of the 1 km downscaled soil moisture well corresponded with GLDAS soil moisture that caught both extremely dry and wet regions. Correlation between GLDAS and the 1 km downscaled soil moisture during growing season was positive (mean r=0.35) in most regions.

Meteorological satellite data: A tool to describe the health of the world's agriculture

NASA Technical Reports Server (NTRS)

Gray, T. I., Jr.; Mccrary, D. G. (Principal Investigator); Scott, L.

1981-01-01

Local area coverage data acquired aboard the TIROS-N satellite family by the advanced very high resolution radiometer systems was examined to determine the agricultural information current. Albedo differences between channel 2 and channel 1 of the advanced very high resolution radiometer LAC (called EVI) are shown to be closely correlated to the Ashburn vegetative index produced from LANDSAT multispectral scanner data which have been shown to vary in response to "greenness", soil moisture, and crop production. The statistical correlation between the EVI and the Ashburn Vegetative Index (+ or - 1 deg) is 0.86.

Rainfall estimation by inverting SMOS soil moisture estimates: A comparison of different methods over Australia

NASA Astrophysics Data System (ADS)

Brocca, Luca; Pellarin, Thierry; Crow, Wade T.; Ciabatta, Luca; Massari, Christian; Ryu, Dongryeol; Su, Chun-Hsu; Rüdiger, Christoph; Kerr, Yann

2016-10-01

Remote sensing of soil moisture has reached a level of maturity and accuracy for which the retrieved products can be used to improve hydrological and meteorological applications. In this study, the soil moisture product from the Soil Moisture and Ocean Salinity (SMOS) satellite is used for improving satellite rainfall estimates obtained from the Tropical Rainfall Measuring Mission multisatellite precipitation analysis product (TMPA) using three different "bottom up" techniques: SM2RAIN, Soil Moisture Analysis Rainfall Tool, and Antecedent Precipitation Index Modification. The implementation of these techniques aims at improving the well-known "top down" rainfall estimate derived from TMPA products (version 7) available in near real time. Ground observations provided by the Australian Water Availability Project are considered as a separate validation data set. The three algorithms are calibrated against the gauge-corrected TMPA reanalysis product, 3B42, and used for adjusting the TMPA real-time product, 3B42RT, using SMOS soil moisture data. The study area covers the entire Australian continent, and the analysis period ranges from January 2010 to November 2013. Results show that all the SMOS-based rainfall products improve the performance of 3B42RT, even at daily time scale (differently from previous investigations). The major improvements are obtained in terms of estimation of accumulated rainfall with a reduction of the root-mean-square error of more than 25%. Also, in terms of temporal dynamic (correlation) and rainfall detection (categorical scores) the SMOS-based products provide slightly better results with respect to 3B42RT, even though the relative performance between the methods is not always the same. The strengths and weaknesses of each algorithm and the spatial variability of their performances are identified in order to indicate the ways forward for this promising research activity. Results show that the integration of bottom up and top down approaches has the potential to improve the quality of near-real-time rainfall estimates from remote sensing in the near future.

Assessment of soil moisture dynamics on an irrigated maize field using cosmic ray neutron sensing

NASA Astrophysics Data System (ADS)

Scheiffele, Lena Maria; Baroni, Gabriele; Oswald, Sascha E.

2015-04-01

In recent years cosmic ray neutron sensing (CRS) developed as a valuable, indirect and non-invasive method to estimate soil moisture at a scale of tens of hectares, covering the gap between point scale measurements and large scale remote sensing techniques. The method is particularly promising in cropped and irrigated fields where invasive installation of belowground measurement devices could conflict with the agricultural management. However, CRS is affected by all hydrogen pools in the measurement footprint and a fast growing biomass provides some challenges for the interpretation of the signal and application of the method for detecting soil moisture. For this aim, in this study a cosmic ray probe was installed on a field near Braunschweig (Germany) during one maize growing season (2014). The field was irrigated in stripes of 50 m width using sprinkler devices for a total of seven events. Three soil sampling campaigns were conducted throughout the growing season to assess the effect of different hydrogen pools on calibration results. Additionally, leaf area index and biomass measurements were collected to provide the relative contribution of the biomass on the CRS signal. Calibration results obtained with the different soil sampling campaigns showed some discrepancy well correlated with the biomass growth. However, after the calibration function was adjusted to account also for lattice water and soil organic carbon, thus representing an equivalent water content of the soil, the differences decreased. Soil moisture estimated with CRS responded well to precipitation and irrigation events, confirming also the effective footprint of the method (i.e., radius 300 m) and showing occurring water stress for the crop. Thus, the dynamics are in agreement with the soil moisture determined with point scale measurements but they are less affected by the heterogeneous moisture conditions within the field. For this reason, by applying a detailed calibration, CRS proves to be a valuable method for the application on agricultural sites to assess and improve irrigation management.

Effects of collagen and collagen hydrolysate from jellyfish umbrella on histological and immunity changes of mice photoaging.

PubMed

Fan, Jian; Zhuang, Yongliang; Li, Bafang

2013-01-17

Jellyfish collagen (JC) was extracted from jellyfish umbrella and hydrolyzed to prepare jellyfish collagen hydrolysate (JCH). The effects of JC and JCH on UV-induced skin damage of mice were evaluated by the skin moisture, microscopic analyses of skin and immunity indexes. The skin moisture analyses showed that moisture retention ability of UV-induced mice skin was increased by JC and JCH. Further histological analysis showed that JC and JCH could repair the endogenous collagen and elastin protein fibers, and could maintain the natural ratio of type I to type III collagen. The immunity indexes showed that JC and JCH play a role in enhancing immunity of photoaging mice in vivo. JCH showed much higher protective ability than JC. These results suggest that JCH as a potential novel antiphotoaging agent from natural resources.

Modeling Effects of Temperature, Soil, Moisture, Nutrition and Variety As Determinants of Severity of Pythium Damping-Off and Root Disease in Subterranean Clover

PubMed Central

You, Ming P.; Rensing, Kelly; Renton, Michael; Barbetti, Martin J.

2017-01-01

Subterranean clover (Trifolium subterraneum) is a critical pasture legume in Mediterranean regions of southern Australia and elsewhere, including Mediterranean-type climatic regions in Africa, Asia, Australia, Europe, North America, and South America. Pythium damping-off and root disease caused by Pythium irregulare is a significant threat to subterranean clover in Australia and a study was conducted to define how environmental factors (viz. temperature, soil type, moisture and nutrition) as well as variety, influence the extent of damping-off and root disease as well as subterranean clover productivity under challenge by this pathogen. Relationships were statistically modeled using linear and generalized linear models and boosted regression trees. Modeling found complex relationships between explanatory variables and the extent of Pythium damping-off and root rot. Linear modeling identified high-level (4 or 5-way) significant interactions for each dependent variable (dry shoot and root weight, emergence, tap and lateral root disease index). Furthermore, all explanatory variables (temperature, soil, moisture, nutrition, variety) were found significant as part of some interaction within these models. A significant five-way interaction between all explanatory variables was found for both dry shoot and root dry weights, and a four way interaction between temperature, soil, moisture, and nutrition was found for both tap and lateral root disease index. A second approach to modeling using boosted regression trees provided support for and helped clarify the complex nature of the relationships found in linear models. All explanatory variables showed at least 5% relative influence on each of the five dependent variables. All models indicated differences due to soil type, with the sand-based soil having either higher weights, greater emergence, or lower disease indices; while lowest weights and less emergence, as well as higher disease indices, were found for loam soil and low temperature. There was more severe tap and lateral root rot disease in higher moisture situations. PMID:29184544

Understanding the time-lag effect of terrestrial ecosystem response to drought: a regional case study of the 2000s Millennium Drought in Australia

NASA Astrophysics Data System (ADS)

Zhao, M.; A, G.; Velicogna, I.; Kimball, J. S.

2016-12-01

Drought is one of the major drivers of the reduction in terrestrial ecosystem productivity. Ecosystem productivity may not primarily be driven by present moisture conditions. Instead, earlier drought conditions may have the largest impact on vegetation growth. We investigate this time-lag effect in Australia by comparing MODIS NDVI data with multiple drought metrics that are sensitive to water deficits at different soil depths. These metrics include 1) soil moisture (SM) from microwave satellite-retrievals that is sensitive to top-centimeter SM variations; 2) the Palmer drought severity index (PDSI) which is sensitive to atmosphere moisture demand and shallow-depth ( 1 meter) SM changes; 3) the newly developed GRACE drought severity index (GRACE-DSI) that is sensitive to changes in overall terrestrial water storage component of the hydrologic cycle and complements satellite SM observations and the PDSI by providing information about deep groundwater storage changes. We quantify the temporal lags between NDVI and these drought metrics during 2002-2014. We find that the NDVI closely evolves with the GRACE-DSI but lags 1-3 months behind the PDSI and satellite-retrievals of SM in western Australia. This pattern however is reverse in eastern Australia. These contrasting NDVI response patterns indicate that vegetation in western Australia is more sensitive to water storage in relatively deeper soil depths than vegetation in the east. This suggests that, in western Australia, vegetation might experience a protracted recovery period after extreme drought since, usually, moisture recharge in deeper soil depths takes a relatively longer period. We conclude that the time-lag effect in Australia is associated with the relative depth of SM to which vegetation is most sensitive. We suggest that characterizing the relative vegetation moisture sensitive depth at the global scale is important for understanding the nature and pace of terrestrial ecosystem recovery from extreme drought events under the background of global climate change.

Spatial and temporal variability of throughfall and soil moisture in a deciduous forest in the low mountain ranges (Hesse, Germany)

NASA Astrophysics Data System (ADS)

Chifflard, Peter; Weishaupt, Philipp; Reiss, Martin

2017-04-01

Spatial and temporal patterns of throughfall can affect the heterogeneity of ecological, biogeochemical and hydrological processes at a forest floor and further the underlying soil. Previous research suggests different factors controlling the spatial and temporal patterns of throughfall, but most studies focus on coniferous forest, where the vegetation coverage is more or less constant over time. In deciduous forests the leaf area index varies due to the leaf fall in autumn which implicates a specific spatial and temporal variability of throughfall and furthermore of the soil moisture. Therefore, in the present study, the measurements of throughfall and soil moisture in a deciduous forest in the low mountain ranges focused especially on the period of leaf fall. The aims of this study were: 1) to detect the spatial and temporal variability of both the throughfall and the soil moisture, 2) to examine the temporal stability of the spatial patterns of the throughfall and soil moisture and 3) relate the soil moisture patterns to the throughfall patterns and further to the canopy characteristics. The study was carried out in a small catchment on middle Hesse (Germany) which is covered by beech forest. Annual mean air temperature is 9.4°C (48.9˚F) and annual mean precipitation is 650 mm. Base materials for soil genesis is greywacke and clay shale from Devonian deposits. The soil type at the study plot is a shallow cambisol. The study plot covers an area of about 150 m2 where 77 throughfall samplers where installed. The throughfall and the soil moisture (FDR-method, 20 cm depth) was measured immediately after every rainfall event at the 77 measurement points. During the period of October to December 2015 altogether 7 events were investigated. The geostatistical method kriging was used to interpolate between the measurements points to visualize the spatial patterns of each investigated parameter. Time-stability-plots were applied to examine temporal scatters of each investigated parameter. The spearmen and pearson correlation coefficients were applied to detect the relationship between the different investigated parameters. First results show that the spatial variability of throughfall decreases if the total amount of the throughfall increases. The soil moisture shows a similar behavior. It`s spatial variability decreases if higher soil moisture values were measured. Concerning the temporal stability of throughfall it can be shown that it is very high during the leaf-free period, although the rainfall events have different total througfall amounts. The soil moisture patterns consists of a low temporal stability and additionally only during one event a significant correlations between throughfall and soil moisture patterns exists. This implies that other factors than the throughfall patterns control the spatial patterns of soil moisture.

Computer Calculation of Fire Danger

Treesearch

William A. Main

1969-01-01

This paper describes a computer program that calculates National Fire Danger Rating Indexes. fuel moisture, buildup index, and drying factor are also available. The program is written in FORTRAN and is usable on even the smallest compiler.

Seasonal patterns of photosynthetic gas-exchange and leaf reflectance characteristics in male and female riparian cottonwoods of southern Alberta

NASA Astrophysics Data System (ADS)

Letts, M. G.; Phelan, C. A.; Johnson, D. R.; Pearce, D. W.; Rood, S. B.

2007-12-01

Riparian, or streamside, cottonwood trees ( Populus spp.) are dioecious phreatophytes of hydrological and ecological importance in arid and semi-arid ecosystems throughout the northern hemisphere. In southern Alberta, groundwater and soil moisture levels typically decline during the May to September growth season. To understand how narrowleaf cottonwoods ( Populus angustifolia James) respond to this seasonal decrease in moisture availability, we repeatedly measured photosynthetic gas exchange, leaf reflectance, chlorophyll fluorescence and stable carbon isotope composition (δ13C) in four male and four female trees of the Oldman River valley, throughout the 2006 growth season. Maximum light-saturated net photosynthesis rates (Amax), near 16 μmol m-2 s-1, occurred on day of year (DOY) 205, one month after peak soil moisture, but coincident with the maximum quantum efficiency of Photosystem II (Fv/Fm), chlorophyll index (CI) and scaled photochemical reflectance index (sPRI). CI data suggest that the early-season rise in Amax and Fv/Fm was partly due to growth in the chlorophyll pool. Thereafter, Amax fell to near 10 μmol m-2 s-1, largely due to its positive logarithmic relationship with stomatal conductance (gs; r2=0.89), which decreased from 559 to 246 mmol m-2 s-1 from DOY 205 to 237. The normalized difference vegetation index (NDVI), CI, sPRI and quantum yield of electron transfer at Photosystem II (ΦPSII) also declined in response to lower volumetric soil moisture content (θv) and increasing groundwater depth (Zgw). Little change in transpiration rate (E) was observed in response to changing environmental conditions, except on DOY 237, when a combination of unseasonably low vapour pressure deficit (D) and low θv above the deepening capillary fringe caused E to decrease. No significant difference was observed between the mean WUE (Amax/E) of males (2.1 ± 0.2 mmol mol-1) and females (2.5 ± 0.2 mmol mol-1; repeated measures ANOVA, df=6, F=2.39, p=0.16). Leaves of females showed a tendency for lower NDVI than those of males (repeated measures ANOVA, F=4.82, p=0.07). Otherwise, no significant differences were observed between males and females in any gas-exchange, leaf reflectance or fluorescence characteristic (repeated measures ANOVA, α=0.05) and δ13C remained in the -28.8 to -29.3 ‰ range throughout the season, in both sexes.

Soil respiration response to climate change in Pacific Northwest prairies is mediated by a regional Mediterranean climate gradient.

PubMed

Reynolds, Lorien L; Johnson, Bart R; Pfeifer-Meister, Laurel; Bridgham, Scott D

2015-01-01

Soil respiration is expected to increase with rising global temperatures but the degree of response may depend on soil moisture and other local factors. Experimental climate change studies from single sites cannot discern whether an observed response is site-dependent or generalizable. To deconvolve site-specific vs. regional climatic controls, we examined soil respiration for 18 months along a 520 km climate gradient in three Pacific Northwest, USA prairies that represents increasingly severe Mediterranean conditions from north to south. At each site we implemented a fully factorial combination of 2.5-3 °C warming and 20% added precipitation intensity. The response of soil respiration to warming was driven primarily by the latitudinal climate gradient and not site-specific factors. Warming increased respiration at all sites during months when soil moisture was not limiting. However, these gains were offset by reductions in respiration during seasonal transitions and summer drought due to lengthened periods of soil moisture limitation. The degree of this offset varied along the north-south climate gradient such that in 2011 warming increased cumulative annual soil respiration 28.6% in the northern site, 13.5% in the central site, and not at all in the southern site. Precipitation also stimulated soil respiration more frequently in the south, consistent with an increased duration of moisture limitation. The best predictors of soil respiration in nonlinear models were the Normalized Difference Vegetation Index (NDVI), antecedent soil moisture, and temperature but these models provided biased results at high and low soil respiration. NDVI was an effective integrator of climate and site differences in plant productivity in terms of their combined effects on soil respiration. Our results suggest that soil moisture limitation can offset the effect of warming on soil respiration, and that greater growing-season moisture limitation would constrain cumulative annual responses to warming. © 2014 John Wiley & Sons Ltd.

Analysis of absorption and spreading of moisturizer on the microscopic region of the skin surface with near-infrared imaging.

PubMed

Arimoto, H; Yanai, M; Egawa, M

2016-11-01

Near-infrared (NIR) light with high water absorption enables us to visualize the water content distribution appeared in the superficial skin layer. The light penetration depth with the wavelength of 1920 nm is almost 100 μm from the skin surface. Thus, the water distribution in the stratum corneum can be effectively imaged by detecting the wavelength band around 1920 nm. The aim of this article was to measure the time-lapse behavior of the tiny droplet of the moisturizer spreading on the skin surface by imaging in 1920 nm wavelength band for investigating the correlation with the traditional index of the skin condition such as the water content and transepidermal water loss (TEWL). Experiment is performed with three moisturizer products and seven volunteer subjects. The NIR image is acquired by an originally designed imaging scope equipped with the white light of the strong brightness [super continuum (SC) light], the bandpass filter with the center wavelength of 1920 nm, and the NIR image sensor. A tiny droplet of the moisturizer is put on the surface of the skin and the time-lapse images are saved. Each acquired image is analyzed from a view point of the droplet area and elapsed time for absorption into the skin. The water content and TEWL of all subjects are measured by the conventional electrical method for investigating the relationship with the measured droplet dynamics parameters. Elapsed time for moisturizer droplet to be absorbed into the skin, the droplet area just before absorption for three moisturizer products, skin water contents, and TEWL for seven subjects were measured and correlation coefficients for each parameters were calculated. It was found that the skin with higher water contents or lower TEWL absorbed the moisturizer faster and spreads moisturizer wider. Also absorption and spreading speed depend on moisturizer property (moisturizing or fresh) which is originated from the moisturizer constituents. The correlation values between the moisturizer dynamics on the skin surface and the traditional index of the skin property were clarified. It was found that the skin with the high water content or low TEWL absorbs the moisturizer droplet fast. The spreading area depends not only on the skin property but on the constituents of the moisturizers. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Ecological and geographical regularities of changes in the biological activity of automorphic soils on the foothills and adjacent plains of the Central Caucasus region (Kabardino-Balkarian Republic)

NASA Astrophysics Data System (ADS)

Gorobtsova, O. N.; Khezheva, F. V.; Uligova, T. S.; Tembotov, R. Kh.

2015-03-01

The biochemical properties inherent to the main types of automorphic soils developed in different bioclimatic conditions of Elbrus and Terek variants of the vertical zonality within Kabardino-Balkaria were compared. The natural-climatic conditions of these variants noticeably affect the soil cover pattern. The ratio of the oxidase and hydrolase activities is sensitive to the moisture conditions in which these soils are formed. The redox processes are more active in drier conditions, whereas hydrolytic processes are more active under higher moisture. The level of the biological activity of the automorphic soils is estimated using the integral index of the ecological-biological soil status.

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.

A quantitative comparison of Soil Development in four climatic regimes

USGS Publications Warehouse

Harden, J.W.; Taylor, E.M.

1983-01-01

A new quantitative Soil Development Index based on field data has been applied to chronosequences formed under different climatic regimes. The four soil chronosequences, developed primarily on sandy deposits, have some numeric age control and are located in xeric-inland (Merced, Calif.), xeric-coastal (Ventura, Calif.), aridic (Las Cruces, N. Mex.), and udic (Susquehanna Valley, Pa.) soil-moisture regimes. To quantify field properties, points are assigned for developmental increases in soil properties in comparison to the parent material. Currently ten soil-field properties are quantified and normalized for each horizon in a given chronosequence, including two new properties for carbonate-rich soils in addition to the eight properties previously defined. When individual properties or the combined indexes are plotted as a function of numeric age, rates of soil development can be compared in different climates. The results demonstrate that (1) the Soil Development Index can be applied to very different soil types, (2) many field properties develop systematically in different climatic regimes, (3) certain properties appear to have similar rates of development in different climates, and (4) the Profile Index that combines different field properties increases significantly with age and appears to develop at similar rates in different climates. The Soil Development Index can serve as a preliminary guide to soil age where other age control is lacking and can be used to correlate deposits of different geographical and climatic regions. ?? 1983.

Estimation of Soil Moisture from Optical and Thermal Remote Sensing: A Review

PubMed Central

Zhang, Dianjun; Zhou, Guoqing

2016-01-01

As an important parameter in recent and numerous environmental studies, soil moisture (SM) influences the exchange of water and energy at the interface between the land surface and atmosphere. Accurate estimate of the spatio-temporal variations of SM is critical for numerous large-scale terrestrial studies. Although microwave remote sensing provides many algorithms to obtain SM at large scale, such as SMOS and SMAP etc., resulting in many data products, they are almost low resolution and not applicable in small catchment or field scale. Estimations of SM from optical and thermal remote sensing have been studied for many years and significant progress has been made. In contrast to previous reviews, this paper presents a new, comprehensive and systematic review of using optical and thermal remote sensing for estimating SM. The physical basis and status of the estimation methods are analyzed and summarized in detail. The most important and latest advances in soil moisture estimation using temporal information have been shown in this paper. SM estimation from optical and thermal remote sensing mainly depends on the relationship between SM and the surface reflectance or vegetation index. The thermal infrared remote sensing methods uses the relationship between SM and the surface temperature or variations of surface temperature/vegetation index. These approaches often have complex derivation processes and many approximations. Therefore, combinations of optical and thermal infrared remotely sensed data can provide more valuable information for SM estimation. Moreover, the advantages and weaknesses of different approaches are compared and applicable conditions as well as key issues in current soil moisture estimation algorithms are discussed. Finally, key problems and suggested solutions are proposed for future research. PMID:27548168

Estimation of Soil Moisture from Optical and Thermal Remote Sensing: A Review.

PubMed

Zhang, Dianjun; Zhou, Guoqing

2016-08-17

As an important parameter in recent and numerous environmental studies, soil moisture (SM) influences the exchange of water and energy at the interface between the land surface and atmosphere. Accurate estimate of the spatio-temporal variations of SM is critical for numerous large-scale terrestrial studies. Although microwave remote sensing provides many algorithms to obtain SM at large scale, such as SMOS and SMAP etc., resulting in many data products, they are almost low resolution and not applicable in small catchment or field scale. Estimations of SM from optical and thermal remote sensing have been studied for many years and significant progress has been made. In contrast to previous reviews, this paper presents a new, comprehensive and systematic review of using optical and thermal remote sensing for estimating SM. The physical basis and status of the estimation methods are analyzed and summarized in detail. The most important and latest advances in soil moisture estimation using temporal information have been shown in this paper. SM estimation from optical and thermal remote sensing mainly depends on the relationship between SM and the surface reflectance or vegetation index. The thermal infrared remote sensing methods uses the relationship between SM and the surface temperature or variations of surface temperature/vegetation index. These approaches often have complex derivation processes and many approximations. Therefore, combinations of optical and thermal infrared remotely sensed data can provide more valuable information for SM estimation. Moreover, the advantages and weaknesses of different approaches are compared and applicable conditions as well as key issues in current soil moisture estimation algorithms are discussed. Finally, key problems and suggested solutions are proposed for future research.

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...

Correlation between ERMI values and other moisture and mold assessments of homes in the American Healthy Home Survey

EPA Science Inventory

Objective: The objective of this study was to determine the correlation between the Environmental Relative Moldiness Index (ERMI) values in the HUD American Healthy Home Survey (AHHS) homes and either inspector reports or occupant assessments of mold and moisture. Methods: In t...

Multispectral Passive Microwave Correlations with an Antecedent Precipitation Index Using the Nimbus 7 SMMR.

DTIC Science & Technology

1984-08-01

M.D. Smallwood , 1981: An evaluation of the spatial resolution of soil moisture information. NASA CR-166724, Goddard Space Flight Center, Greenbelt, MD...Thesis, Dept of Meteor- ology, Univ. of Okla., Norman , 59 pp. Theis, S.W., 1979: Surface soil moisture estimation with the Electri- cally Scanning

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.

Detection of underground structures using UAV and field spectroscopy for defence and security in Cyprus

NASA Astrophysics Data System (ADS)

Melillos, George; Themistocleous, Kyriacos; Prodromou, Maria; Hadjimitsis, Diofantos G.

2017-10-01

The purpose of this paper is to present the results obtained from unmanned aerial vehicle (UAV) and field spectroscopy campaigns for detecting underground structures. Underground structures can affect their surrounding landscapes in different ways, such as soil moisture content, soil composition and vegetation vigor. The last is often observed on the ground as a crop mark; a phenomenon which can be used as a proxy to denote the presence of underground non-visible structures. A number of vegetation indices such as the Normalized Difference Vegetation Index (NDVI), Simple Ratio (SR), Difference Vegetation Index (DVI) and Soil Adjusted Vegetation Index (SAVI) were utilized for the development of a vegetation index-based procedure aiming at the detection of underground military structures by using existing vegetation indices or other in-band algorithms. The measurements were taken at the following test areas such as: (a) vegetation area covered with the vegetation (barley), in the presence of an underground military structure (b) vegetation area covered with the vegetation (barley), in the absence of an underground military structure.

Remotely sensed vegetation moisture as explanatory variable of Lyme borreliosis incidence

NASA Astrophysics Data System (ADS)

Barrios, J. M.; Verstraeten, W. W.; Maes, P.; Clement, J.; Aerts, J. M.; Farifteh, J.; Lagrou, K.; Van Ranst, M.; Coppin, P.

2012-08-01

The strong correlation between environmental conditions and abundance and spatial spread of the tick Ixodes ricinus is widely documented. I. ricinus is in Europe the main vector of the bacterium Borrelia burgdorferi, the pathogen causing Lyme borreliosis (LB). Humidity in vegetated systems is a major factor in tick ecology and its effects might translate into disease incidence in humans. Time series of two remotely sensed indices with sensitivity to vegetation greenness and moisture were tested as explanatory variables of LB incidence. Wavelet-based multiresolution analysis allowed the examination of these signals at different temporal scales in study sites in Belgium, where increases in LB incidence were reported in recent years. The analysis showed the potential of the tested indices for disease monitoring, the usefulness of analyzing the signal in different time frames and the importance of local characteristics of the study area for the selection of the vegetation index.

Coherent tropical-subtropical Holocene see-saw moisture patterns in the Eastern Hemisphere monsoon systems

NASA Astrophysics Data System (ADS)

Wang, Yongbo; Bekeschus, Benjamin; Handorf, Dörthe; Liu, Xingqi; Dallmeyer, Anne; Herzschuh, Ulrike

2017-08-01

The concept of a Global Monsoon (GM) has been proposed based on modern precipitation observations, but its application over a wide range of temporal scales is still under debate. Here, we present a synthesis of 268 continental paleo-moisture records collected from monsoonal systems in the Eastern Hemisphere, including the East Asian Monsoon (EAsM), the Indian Monsoon (IM), the East African Monsoon (EAfM), and the Australian Monsoon (AuM) covering the last 18,000 years. The overall pattern of late Glacial to Holocene moisture change is consistent with those inferred from ice cores and marine records. With respect to the last 10,000 years (10 ka), i.e. a period that has high spatial coverage, a Fuzzy c-Means clustering analysis of the moisture index records together with ;Xie-Beni; index reveals four clusters of our data set. The paleoclimatic meaning of each cluster is interpreted considering the temporal evolution and spatial distribution patterns. The major trend in the tropical AuM, EAfM, and IM regions is a gradual decrease in moisture conditions since the early Holocene. Moisture changes in the EAsM regions show maximum index values between 8 and 6 ka. However, records located in nearby subtropical areas, i.e. in regions not influenced by the intertropical convergence zone, show an opposite trend compared to the tropical monsoon regions (AuM, EAfM and IM), i.e. a gradual increase. Analyses of modern meteorological data reveal the same spatial patterns as in the paleoclimate records such that, in times of overall monsoon strengthening, lower precipitation rates are observed in the nearby subtropical areas. We explain this pattern as the effect of a strong monsoon circulation suppressing air uplift in nearby subtropical areas, and hence hindering precipitation. By analogy to the modern system, this would mean that during the early Holocene strong monsoon period, the intensified ascending airflows within the monsoon domains led to relatively weaker ascending or even descending airflows in the adjacent subtropical regions, resulting in a precipitation deficit compared to the late Holocene. Our conceptual model therefore integrates regionally contrasting moisture changes into the Global Monsoon hypothesis.

Characterization of energy exchange parameters in the Himalayan foothills Pakistan

NASA Astrophysics Data System (ADS)

Khalid, Bushra; Kumar, Mukul; Cholaw, Bueh; Aziz Khan, Junaid; Hayat Khan, Azmat

2017-04-01

The characterization of energy exchange parameters for spring season (April-May) has been done for Margalla hills national park (MHNP) Islamabad, Pakistan. It is important because Islamabad city lies in the foothills of Himalayas and micro meteorological activity makes the climate of surrounding areas. The activity on Himalaya's foothills (i.e., Margalla hills) regulate weather and also provide fresh water to the lakes and ponds by late afternoon thunder showers. This research is also important from the perspective of rain water harvesting in Islamabad, Pakistan. The objective of this study is to characterize the energy exchange parameters in the foothills of great Himalayas particularly on MHNP. Landsat ETM+ imageries have been used for calculating the land surface temperature (LST), normalized difference vegetation index (NDVI), and normalized difference moisture index (NDMI). SPOT 5 image has been used for land use/land cover classification over MHNP. The turbulent fluxes have been calculated by computing the values acquired from the processing of satellite imageries and real time observation data sets. The comparisons have been made between the land and atmospheric temperature and moisture to see the difference and its impacts on weather of twin cities i.e., Islamabad and Rawalpindi. The energy exchange parameters have been characterized by analyzing the impacts of weather parameters and turbulent fluxes on MHNP and surrounding cities. The potential rain water harvesting sites have been marked in the foothills. Weather and surface conditions become more favorable for the growth of vegetation by the end of April as the spring season reaches at its peak. There is the start of growing season in the month of April whereas the vegetation becomes thick over time during the month of May over Margalla hills however, the energy exchange parameters follow the same pattern in May as in April. The relative humidity remains between 18 - 55 % and the atmospheric temperature variations are between 19 to 35 0C during the studied period. As the atmospheric temperature and RH fluctuate, it effects the soil moisture and land surface temperature. Even if the atmospheric temperature rise or fall, the evergreen vegetation is found throughout the year on Margalla hills maintains/regulates the land surface temperature and soil moisture. The latent heat flux cause an increase in the noon temperature and RH levels. It further increases the moisture level in the atmosphere that is greatly supported by sensible heat flux to drive the moisture to the higher vertical levels and cause late afternoon thunder showers on the foothills and surrounding areas. The thundershowers are usually intense that cause light or heavy hail and changes the atmospheric temperature around 20 degrees Celsius in the evening time.

Impact of DEM and soils on topographic index, as used in TopoSWAT

USDA-ARS?s Scientific Manuscript database

A topographic index (TI), comprised of slope and upstream contributing area, is used in TopoSWAT to help account for variable source runoff and soil moisture. The level of precision in the GIS input data layers can substantially impact the calculations of the topographic index layer and affect the a...

Effects of Collagen and Collagen Hydrolysate from Jellyfish Umbrella on Histological and Immunity Changes of Mice Photoaging

PubMed Central

Fan, Jian; Zhuang, Yongliang; Li, Bafang

2013-01-01

Jellyfish collagen (JC) was extracted from jellyfish umbrella and hydrolyzed to prepare jellyfish collagen hydrolysate (JCH). The effects of JC and JCH on UV-induced skin damage of mice were evaluated by the skin moisture, microscopic analyses of skin and immunity indexes. The skin moisture analyses showed that moisture retention ability of UV-induced mice skin was increased by JC and JCH. Further histological analysis showed that JC and JCH could repair the endogenous collagen and elastin protein fibers, and could maintain the natural ratio of type I to type III collagen. The immunity indexes showed that JC and JCH play a role in enhancing immunity of photoaging mice in vivo. JCH showed much higher protective ability than JC. These results suggest that JCH as a potential novel antiphotoaging agent from natural resources. PMID:23344251

Permafrost as an additional driving factor for the extreme fire event in the boreal Baikal region in 2003

NASA Astrophysics Data System (ADS)

Forkel, M.; Thonicke, K.; Beer, C.; Cramer, W.; Bartalev, S.; Schmullius, C.

2012-04-01

Wildfires are a natural and important element in the functioning of boreal forests. However, in some years, fires with extreme spread and severity occur. Such severe fires degrade the forest, affect human values, emit huge amount of carbon and aerosols and alter the land surface albedo. Usually, wind, slope, and dry conditions have been recognized as factors determining fire spread. In the Baikal region, 127,000 km2 burned in 2003, while the annual average burned area is approx. 8100 km2. In average years, 16% of the burned area occurred in the continuous permafrost zone but in 2003, 33% of these burned areas coincide with the existence of permanently frozen grounds. Permafrost and the associated upper active layer, which thaws during summer and refreezes during winter, is an important supply for soil moisture in boreal ecosystems. This leads to the question if permafrost hydrology is a potential additional driving factor for extreme fire events in boreal forests. Using temperature and precipitation data, we calculated the Nesterov index as indicator for fire weather conditions. Further, we used satellite observations of burned area and surface moisture, a digital elevation model, a land cover and a permafrost map to evaluate drivers for the temporal dynamic and spatial variability of surface moisture conditions and burned area in spring 2003. On the basis of time series decomposition, we separated the effect of drivers for fire activity on different time scales. We next computed cross-correlations to identify potential time lags between weather conditions, surface moisture and fire activity. Finally, we assessed the predictive capability of different combinations of driving variables for surface moisture conditions and burned area using multivariate spatial-temporal regression models. The results from this study demonstrate that permafrost in larch-dominated ecosystems regulates the inter-annual variability of surface moisture and thus increases the inter-annual variability of burned area. The drought conditions in spring 2003 were accelerated by the presence of permafrost because less water was stored in the upper active layer from the dry previous summer 2002 and the permafrost table prevents vegetative water uptake from deeper layers. In contrast, weather conditions (precipitation anomaly, Nesterov index) are weaker predictors for the 2003 fire event. Our analysis advances the understanding of complex interactions between the atmosphere, vegetation and soil on how feedback mechanisms can lead to extreme fire events. These findings emphasize the importance of a mechanistic coupling of soil thermodynamics, hydrology, and fire activity in earth system models for projecting climate change impacts over the next century.

Modelling of the L-band brightness temperatures measured with ELBARA III radiometer on Bubnow wetland

NASA Astrophysics Data System (ADS)

Gluba, Lukasz; Sagan, Joanna; Lukowski, Mateusz; Szlazak, Radoslaw; Usowicz, Boguslaw

2017-04-01

Microwave radiometry has become the main tool for investigating soil moisture (SM) with remote sensing methods. ESA - SMOS (Soil Moisture and Ocean Salinity) satellite operating at L-band provides global distribution of soil moisture. An integral part of SMOS mission are calibration and validation activities involving measurements with ELBARA III which is an L-band microwave passive radiometer. It is done in order to improve soil moisture retrievals - make them more time-effective and accurate. The instrument is located at Bubnow test-site, on the border of cultivated field, fallow, meadow and natural wetland being a part of Polesie National Park (Poland). We obtain both temporal and spatial dependences of brightness temperatures for varied types of land covers with the ELBARA III directed at different azimuths. Soil moisture is retrieved from brightness temperature using L-band Microwave Emission of the Biosphere (L-MEB) model, the same as currently used radiative transfer model for SMOS. Parametrization of L-MEB, as well as input values are still under debate. We discuss the results of SM retrievals basing on data obtained during first year of the radiometer's operation. We analyze temporal dependences of retrieved SM for one-parameter (SM), two-parameter (SM, τ - optical depth) and three-parameter (SM, τ, Hr - roughness parameter) retrievals, as well as spatial dependences for specific dates. Special case of Simplified Roughness Parametrization, combining the roughness parameter and optical depth, is considered. L-MEB processing is supported by the continuous measurements of soil moisture and temperature obtained from nearby agrometeorological station, as well as studies on the soil granulometric composition of the Bubnow test-site area. Furthermore, for better estimation of optical depth, the satellite-derived Normalized Difference Vegetation Index (NDVI) was employed, supported by measured in situ vegetation parameters (such as Leaf Area Index and Vegetation Water Content) obtained during the field campaigns. The values of NDVI around ELBARA III radiometer are provided by Sentinel-2 satellite with approximately 10 m spatial resolution and average 10 days of time interval within studied period of time. The work was partially funded under two ESA projects: 1) "ELBARA_PD (Penetration Depth)" No. 4000107897/13/NL/KML, funded by the Government of Poland through an ESA-PECS contract (Plan for European Cooperating States). 2) "Technical Support for the fabrication and deployment of the radiometer ELBARA-III in Bubnow, Poland" No. 4000113360/15/NL/FF/gp.

Widespread extreme drought events in Iberia and their relationship with North Atlantic moisture flux deficit

NASA Astrophysics Data System (ADS)

Liberato, Margarida L. R.; Montero, Irene; Russo, Ana; Gouveia, Célia; Ramos, Alexandre M.; Trigo, Ricardo M.

2015-04-01

Droughts represent one of the most frequent climatic extreme events on the Iberian Peninsula, often with widespread negative ecological and environmental impacts, resulting in major socio-economic damages such as large decreases in hydroelectricity and agricultural productions or increasing forest fire risk. Unlike other weather driven extreme events, droughts duration could be from few months to several years. Here we employ a recently developed climatic drought index, the Standardized Precipitation Evapotranspiration Index (SPEI; Vicente-Serrano et al. 2010a), based on the simultaneous use of precipitation and temperature fields. This index holds the advantage of combining a multi-scalar character with the capacity to include the effects of temperature variability on drought assessment (Vicente-Serrano et al., 2010a). In this study the SPEI was computed using the Climatic Research Unit (CRU) TS3.21 High Resolution Gridded Data (0.5°) for the period 1901-2012. At this resolution the study region of Iberian Peninsula corresponds to a square of 30x30 grid pixels. The CRU Potential Evapotranspiration (PET) was used, through the Penmann-Monteith equation and the log-logistic probability distribution. This formulation allows a very good fit to the series of differences between precipitation and PET (Vicente-Serrano et al., 2010b), using monthly averages of daily maximum and minimum temperature data and also monthly precipitation records. The parameters were estimated by means of the L-moment method. The application of multi-scalar indices to the high-resolution datasets allows identifying whether the Iberian Peninsula is in hydric stress and also whether drought is installed. Based on the gridded SPEI datasets, spanning from 1901 to 2012, obtained for timescales 6, 12, 18 and 24 months, an objective method is applied for ranking the most extensive extreme drought events that occurred on the Iberian Peninsula. This objective method is based on the evaluation of the drought's magnitude, which is obtained after considering the area affected - defined by SPEI values over a certain threshold (in this case SPEI < -1.28) - as well as its intensity in each grid point. Different rankings are presented for the different timescales considering both the entire Iberian Peninsula and Portugal. Furthermore we used the NCEP/NCAR reanalysis in the 1948-2012 period, namely, the geopotential height, temperature, wind and specific humidity fields at all pressure levels and mean sea level pressure (MSLP) and total column water vapour (TCWV) for the Euro-Atlantic sector (60° W to 40° E, 20° N to 70° N) at full temporal (six hourly) and spatial (2.5° regular horizontal grid) resolutions available as well as the globally gridded monthly precipitation products of the Global Precipitation Climatology Centre (GPCC), to analyse the large-scale conditions associated with the most extreme droughts in Iberia. Results show that during these drought periods there is a clear moisture deficit over the region, with permanent negative anomalies of TCWV. Additionally, in these occasions, the zonal moisture transport is more intense over the northern Atlantic and less intense on the subtropics while the meridional moisture transport is intensified, in accordance with the barotropic structure of HGT anomalies. Vicente-Serrano, S.M., Beguería, S., and López-Moreno, J.I. (2010a). A Multi-scalar drought index sensitive to global warming: The Standardized Precipitation Evapotranspiration Index - SPEI. Journal of Climate, 23, 1696-1718. Vicente-Serrano, S.M., Beguería, S., López-Moreno, J.I., Angulo, M., and El Kenawy, A. (2010b). A new global 0.5° gridded dataset (1901-2006) of a multiscalar drought index: comparison with current drought index datasets based on the Palmer Drought Severity Index. Journal of Hydrometeorology, 11, 1033-1043 Acknowledgements: This work was partially supported by national funds through FCT (Fundação para a Ciência e a Tecnologia, Portugal) under project QSECA (PTDC/AAGGLO/4155/2012).

Vegetation classification and soil moisture calculation using land surface temperature (LST) and vegetation index (VI)

NASA Astrophysics Data System (ADS)

Liu, Liangyun; Zhang, Bing; Xu, Genxing; Zheng, Lanfen; Tong, Qingxi

2002-03-01

In this paper, the temperature-missivity separating (TES) method and normalized difference vegetation index (NDVI) are introduced, and the hyperspectral image data are analyzed using land surface temperature (LST) and NDVI channels which are acquired by Operative Module Imaging Spectral (OMIS) in Beijing Precision Agriculture Demonstration Base in Xiaotangshan town, Beijing in 26 Apr, 2001. Firstly, the 6 kinds of ground targets, which are winter wheat in booting stage and jointing stage, bare soil, water in ponds, sullage in dry ponds, aquatic grass, are well classified using LST and NDVI channels. Secondly, the triangle-like scatter-plot is built and analyzed using LST and NDVI channels, which is convenient to extract the information of vegetation growth and soil's moisture. Compared with the scatter-plot built by red and near-infrared bands, the spectral distance between different classes are larger, and the samples in the same class are more convergent. Finally, we design a logarithm VIT model to extract the surface soil water content (SWC) using LST and NDVI channel, which works well, and the coefficient of determination, R2, between the measured surface SWC and the estimated is 0.634. The mapping of surface SWC in the wheat area are calculated and illustrated, which is important for scientific irrigation and precise agriculture.

Spectro-spatial relationship between UAV derived high resolution DEM and SWIR hyperspectral data: application to an ombrotrophic peatland

NASA Astrophysics Data System (ADS)

Arroyo-Mora, J. Pablo; Kalacska, Margaret; Lucanus, Oliver; Soffer, Raymond; Leblanc, George

2017-10-01

Peatlands cover 3% of the globe and are key ecosystems for climate regulation. To better understand the potential effects of climate change in peatlands, a major challenge is to determine the complex relationship between hydrology, microtopography, vegetation patterns, and gas exchange. Here we study the spectral and spatial relationship of microtopographic features (e.g. hollows and hummocks) and near-surface water through narrow-band spectral indices derived from hyperspectral imagery. We used a very high resolution digital elevation model (2.5 cm horizontal, 2.2 cm vertical resolution) derived from an UAV based Structure from Motion photogrammetry to map hollows and hummocks in the peatland area. We also created a 2 cm spatial resolution orthophoto mosaic to enhance the visual identification of these hollows and hummocks. Furthermore, we collected SWIR airborne hyperspectral (880-2450 nm) imagery at 1 m pixel resolution over four time periods, from April to June 2016 (phenological gradient: vegetation greening). Our results revealed an increase in the water indices values (NDWI1640 and NDWI2130) and a decrease in the moisture stress index (MSI) between April and June. In addition, for the same period the NDWI2130 shows a bimodal distribution indicating potential to quantitatively assess moisture differences between mosses and vascular plants. Our results, using the digital surface model to extract NDWI2130 values, showed significant differences between hollows and hummocks for each time period, with higher moisture values for hollows (i.e. moss dominated). However, for June, the water index for hummocks approximated the values found in hollows. Our study shows the advantages of using fine spatial and spectral scales to detect temporal trends in near surface water in a peatland.

Performance of the Haines Index During August 2000 for Montana

Treesearch

Brian E. Potter; Scott Goodrick

2003-01-01

The Haines Index, introduced by Haines (1988) as the Lower Atmosphere Severity Index, is designed to gauge how readily the lower mid-troposphere (500 to 4500 m AGL) will spur an otherwise fairly predictable fire to become erratic and unmanageable. Based on stability and moisture, the Haines Index (hereafter, HI) takes on integer values from 2 to 6, with 2 being very...

Response of vegetation indices to changes in three measures of leaf water stress

NASA Technical Reports Server (NTRS)

Cohen, Warren B.

1991-01-01

The responses of vegetation indices to changes in water stress were evaluated in two separate laboratory experiments. In one experiment the normalized difference vegetation index (NDVI), the near-IR to red ratio (near-IR/red), the Infrared Index (II), and the Moisture Stress Index (MSI) were more highly correlated to leaf water potential in lodgepole pine branches than were the Leaf Water Content Index (LWCI), the mid-IR ratio (Mid-IR), or any of the single Thematic Mapper (TM) bands. In the other experiment, these six indices and the TM Tasseled Cap brightness, greenness, and wetness indices responded to changes in leaf relative water content (RWC) differently than they responded to changes in leaf water content (WC) of three plant species, and the responses were dependent on how experimental replicates were pooled. With no pooling, the LWCI was the most highly correlated index to both RWC and WC among replications, followed by the II, MSI, and wetness. Only the LWCI was highly correlated to RWC and WC when replications were pooled within species. With among species pooling the LWCI was the only index highly correlated with RWC, while the II, MSI, Mid-IR, and wetness were most highly correlated with WC.

Predicting key malaria transmission factors, biting and entomological inoculation rates, using modelled soil moisture in Kenya.

PubMed

Patz, J A; Strzepek, K; Lele, S; Hedden, M; Greene, S; Noden, B; Hay, S I; Kalkstein, L; Beier, J C

1998-10-01

While malaria transmission varies seasonally, large inter-annual heterogeneity of malaria incidence occurs. Variability in entomological parameters, biting rates and entomological inoculation rates (EIR) have been strongly associated with attack rates in children. The goal of this study was to assess the weather's impact on weekly biting and EIR in the endemic area of Kisian, Kenya. Entomological data collected by the U.S. Army from March 1986 through June 1988 at Kisian, Kenya was analysed with concurrent weather data from nearby Kisumu airport. A soil moisture model of surface-water availability was used to combine multiple weather parameters with landcover and soil features to improve disease prediction. Modelling soil moisture substantially improved prediction of biting rates compared to rainfall; soil moisture lagged two weeks explained up to 45% of An. gambiae biting variability, compared to 8% for raw precipitation. For An. funestus, soil moisture explained 32% variability, peaking after a 4-week lag. The interspecies difference in response to soil moisture was significant (P < 0.00001). A satellite normalized differential vegetation index (NDVI) of the study site yielded a similar correlation (r = 0.42 An. gambiae). Modelled soil moisture accounted for up to 56% variability of An. gambiae EIR, peaking at a lag of six weeks. The relationship between temperature and An. gambiae biting rates was less robust; maximum temperature r2 = -0.20, and minimum temperature r2 = 0.12 after lagging one week. Benefits of hydrological modelling are compared to raw weather parameters and to satellite NDVI. These findings can improve both current malaria risk assessments and those based on El Niño forecasts or global climate change model projections.

Using satellite image data to estimate soil moisture

NASA Astrophysics Data System (ADS)

Chuang, Chi-Hung; Yu, Hwa-Lung

2017-04-01

Soil moisture is considered as an important parameter in various study fields, such as hydrology, phenology, and agriculture. In hydrology, soil moisture is an significant parameter to decide how much rainfall that will infiltrate into permeable layer and become groundwater resource. Although soil moisture is a critical role in many environmental studies, so far the measurement of soil moisture is using ground instrument such as electromagnetic soil moisture sensor. Use of ground instrumentation can directly obtain the information, but the instrument needs maintenance and consume manpower to operation. If we need wide range region information, ground instrumentation probably is not suitable. To measure wide region soil moisture information, we need other method to achieve this purpose. Satellite remote sensing techniques can obtain satellite image on Earth, this can be a way to solve the spatial restriction on instrument measurement. In this study, we used MODIS data to retrieve daily soil moisture pattern estimation, i.e., crop water stress index (cwsi), over the year of 2015. The estimations are compared with the observations at the soil moisture stations from Taiwan Bureau of soil and water conservation. Results show that the satellite remote sensing data can be helpful to the soil moisture estimation. Further analysis can be required to obtain the optimal parameters for soil moisture estimation in Taiwan.

Sensitivity of Global Terrestrial Gross Primary Production to Hydrologic States Simulated by the Community Land Model Using Two Runoff Parameterizations

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

Lei, Huimin; Huang, Maoyi; Leung, Lai-Yung R.

2014-09-01

The terrestrial water and carbon cycles interact strongly at various spatio-temporal scales. To elucidate how hydrologic processes may influence carbon cycle processes, differences in terrestrial carbon cycle simulations induced by structural differences in two runoff generation schemes were investigated using the Community Land Model 4 (CLM4). Simulations were performed with runoff generation using the default TOPMODEL-based and the Variable Infiltration Capacity (VIC) model approaches under the same experimental protocol. The comparisons showed that differences in the simulated gross primary production (GPP) are mainly attributed to differences in the simulated leaf area index (LAI) rather than soil moisture availability. More specifically,more » differences in runoff simulations can influence LAI through changes in soil moisture, soil temperature, and their seasonality that affect the onset of the growing season and the subsequent dynamic feedbacks between terrestrial water, energy, and carbon cycles. As a result of a relative difference of 36% in global mean total runoff between the two models and subsequent changes in soil moisture, soil temperature, and LAI, the simulated global mean GPP differs by 20.4%. However, the relative difference in the global mean net ecosystem exchange between the two models is small (2.1%) due to competing effects on total mean ecosystem respiration and other fluxes, although large regional differences can still be found. Our study highlights the significant interactions among the water, energy, and carbon cycles and the need for reducing uncertainty in the hydrologic parameterization of land surface models to better constrain carbon cycle modeling.« less

Integrated study of biomass index in La Herreria (Sierra de Guadarrama)

NASA Astrophysics Data System (ADS)

Hernandez Díaz-Ambrona, Carlos G.

2016-04-01

Drought severity has many implications for society, including its impacts on the water supply, water pollution, reservoir management and ecosystem. There have been many attempts to characterize its severity, resulting in the numerous drought indices that have been developed (Niemeyer 2008). The'biomass index', based on satellite image derived Normalized Difference Vegetation Index (NDVI) has been used in several countries for pasture and forage crops for some years (Rao, 2010; Escribano-Rodriguez et al., 2014). NDVI generally provides a broad overview of the vegetation condition and spatial vegetation distribution in a region. Vegetative drought is closely related with weather impacts. However, in NDVI, the weather component gets subdued by the strong ecological component. Another vegetation index is Vegetation Condition Index (VCI) that separates the short-term weather-related NDVI fluctuations from the long-term ecosystem changes (Kogan, 1990). Therefore, while NDVI shows seasonal vegetation dynamics, VCI rescales vegetation dynamics between 0 and 100 to reflect relative changes in the vegetation condition from extremely bad to optimal (Kogan et al., 2003). In this work a pasture area at La Herreria (Sierra de Guadarrama, Spain) has been delimited. Then, NDVI historical data are reconstructed based on remote sensing imaging MODIS, with 500x500m2 resolution. From the closest meteorological station (Santolaria-Canales, 2015) records of weekly precipitation, temperature and evapotranspiration from 2001 till 2012 were obtained. Standard Precipitation Index (SPI), Crop Moisture Index (CMI) (Palmer, 1968) and Evapotranspiration-Precipitation Ratio (EPR) are calculated in an attempt to relate them to several vegetation indexes: NDVI, VCI and NDVI Change Ratio to Median (RMNDVI). The results are discussed in the context of pasture index insurance. References Escribano Rodriguez, J.Agustín, Carlos Gregorio Hernández Díaz-Ambrona and Ana María Tarquis Alfonso. Selection of vegetation indices to estimate pasture production in Dehesas. PASTOS, 44(2), 6-18, 2014. Kogan, F. N., 1990. Remote sensing of weather impacts on vegetation in non-homogeneous areas. Int. J. Remote Sensing, 11(8), pp. 1405-1419. Kogan, F. N., Gitelson, A., Edige, Z., Spivak, l., and Lebed, L., 2003. AVHRR-Based Spectral Vegetation Index for Quantitative Assessment of Vegetation State and Productivity: Calibration and Validation. Photogrammetric Engineering & Remote Sensing, 69(8), pp. 899-906. Niemeyer, S., 2008. New drought indices. First Int. Conf. on Drought Management: Scientific and Technological Innovations, Zaragoza, Spain, Joint Research Centre of the European Commission. Palmer, W.C., 1968. Keeping track of crop moisture conditions, nationwide: The new Crop Moisture Index. Weatherwise 21, 156-161. Rao, K.N. 2010. Index based Crop Insurance. Agriculture and Agricultural Science Procedia 1, 193-203. Santolaria-Canales, Edmundo and the GuMNet Consortium Team (2015). GuMNet - Guadarrama Monitoring Network. Installation and set up of a high altitude monitoring network, north of Madrid. Spain. Geophysical Research Abstracts, 17, EGU2015-13989-2 Web: http://www.ucm.es/gumnet/

SoilNet - A Zigbee based soil moisture sensor network

NASA Astrophysics Data System (ADS)

Bogena, H. R.; Weuthen, A.; Rosenbaum, U.; Huisman, J. A.; Vereecken, H.

2007-12-01

Soil moisture plays a key role in partitioning water and energy fluxes, in providing moisture to the atmosphere for precipitation, and controlling the pattern of groundwater recharge. Large-scale soil moisture variability is driven by variation of precipitation and radiation in space and time. At local scales, land cover, soil conditions, and topography act to redistribute soil moisture. Despite the importance of soil moisture, it is not yet measured in an operational way, e.g. for a better prediction of hydrological and surface energy fluxes (e.g. runoff, latent heat) at larger scales and in the framework of the development of early warning systems (e.g. flood forecasting) and the management of irrigation systems. The SoilNet project aims to develop a sensor network for the near real-time monitoring of soil moisture changes at high spatial and temporal resolution on the basis of the new low-cost ZigBee radio network that operates on top of the IEEE 802.15.4 standard. The sensor network consists of soil moisture sensors attached to end devices by cables, router devices and a coordinator device. The end devices are buried in the soil and linked wirelessly with nearby aboveground router devices. This ZigBee wireless sensor network design considers channel errors, delays, packet losses, and power and topology constraints. In order to conserve battery power, a reactive routing protocol is used that determines a new route only when it is required. The sensor network is also able to react to external influences, e.g. such as rainfall occurrences. The SoilNet communicator, routing and end devices have been developed by the Forschungszentrum Juelich and will be marketed through external companies. We will present first results of experiments to verify network stability and the accuracy of the soil moisture sensors. Simultaneously, we have developed a data management and visualisation system. We tested the wireless network on a 100 by 100 meter forest plot equipped with 25 end devices each consisting of 6 vertically arranged soil moisture sensors. The next step will be the instrumentation of two small catchments (~30 ha) with a 30 m spacing of the end devices. juelich.de/icg/icg-4/index.php?index=739

Multisensor fusion remote sensing technology for assessing multitemporal responses in ecohydrological systems

NASA Astrophysics Data System (ADS)

Makkeasorn, Ammarin

This study aims at presenting a systematic soil moisture estimation method for the Choke Canyon Reservoir Watershed (CCRW), a semiarid watershed with an area of over 14,200 km2 in south Texas. With the aid of five corner reflectors, the RADARSAT-1 Synthetic Aperture Radar (SAR) imageries of the study area acquired in April and September 2004 were processed by both radiometric and geometric calibrations at first. New soil moisture estimation models derived by genetic programming (GP) technique were then developed and applied to support the soil moisture distribution analysis. The GP-based nonlinear function derived in the evolutionary process uniquely links a series of crucial topographic and geographic features. Included in this process are slope, aspect, vegetation cover, and soil permeability to compliment the well-calibrated SAR data. Research indicates that the novel application of GP proved useful for generating a highly nonlinear structure in regression regime, which exhibits very strong correlations statistically between the model estimates and the ground truth measurements (volumetric water content) on the basis of the unseen data sets. In an effort to produce the soil moisture distributions over seasons, it eventually leads to characterizing local- to regional-scale soil moisture variability and performing the possible estimation of water storages of the terrestrial hydrosphere. A new evolutionary computational, supervised classification scheme ( Riparian Classification Algorithm, RICAL) was developed and used to identify the change of riparian zones in a semi-arid watershed temporally and spatially. The case study uniquely demonstrates an effort to incorporating both vegetation index and soil moisture estimates based on Landsat 5 TM and RADARSAT-1 imageries while trying to improve the riparian classification in the Choke Canyon Reservoir Watershed (CCRW), South Texas. The estimation of soil moisture based on RADARSAT-1 Synthetic Aperture Radar (SAR) satellite imagery as previously developed was used. Eight commonly used vegetation indices were calculated from the reflectance obtained from Landsat 5 TM satellite images. The vegetation indices were individually used to classify vegetation cover in association with genetic programming algorithm. The soil moisture and vegetation indices were integrated into Landsat TM images based on a pre-pixel channel approach for riparian classification. Two different classification algorithms were used including genetic programming, and a combination of ISODATA and maximum likelihood supervised classification. The white box feature of genetic programming revealed the comparative advantage of all input parameters. The GP algorithm yielded more than 90% accuracy, based on unseen ground data, using vegetation index and Landsat reflectance band 1, 2, 3, and 4. The detection of changes in the buffer zone was proved to be technically feasible with high accuracy. Overall, the development of the RICAL algorithm may lead to the formulation of more effective management strategies for the handling of non-point source pollution control, bird habitat monitoring, and grazing and live stock management in the future. Geo-environmental information amassed in this study includes soil permeability, surface temperature, soil moisture, precipitation, leaf area index (LAI) and normalized difference vegetation index (NDVI). With the aid of a remote sensing-based GIP analysis, only five locations out of more than 800 candidate sites were selected by the spatial analysis, and then confirmed by a field investigation. The methodology developed in this remote sensing-based GIP analysis will significantly advance the state-of-the-art technology in optimum arrangement/distribution of water sensor platforms for maximum sensing coverage and information-extraction capacity. To more efficiently use the limited amount of water or to resourcefully provide adequate time for flood warning, the results have led us to seek advanced techniques for improving streamflow forecasting. The objective of this section of research is to incorporate sea surface temperature (SST), Next Generation Radar (NEXRAD) and meteorological characteristics with historical stream data to forecast the actual streamflow using genetic programming. This study case concerns the forecasting of stream discharge of a complex-terrain, semi-arid watershed. This study elicits microclimatological factors and the resultant stream flow rate in river system given the influence of dynamic basin features such as soil moisture, soil temperature, ambient relative humidity, air temperature, sea surface temperature, and precipitation. Evaluations of the forecasting results are expressed in terms of the percentage error (PE), the root-mean-square error (RMSE), and the square of the Pearson product moment correlation coefficient (r-squared value). The developed models can predict streamflow with very good accuracy with an r-square of 0.84 and PE of 1% for a 30-day prediction. (Abstract shortened by UMI.)

Intercomparison of Soil Moisture, Evaporative Stress, and Vegetation Indices for Estimating Corn and Soybean Yields Over the U.S.

NASA Technical Reports Server (NTRS)

Mladenova, Iliana E.; Bolten, John D.; Crow, Wade T.; Anderson, Martha C.; Hain, C. R.; Johnson, David M.; Mueller, Rick

2017-01-01

This paper presents an intercomparative study of 12 operationally produced large-scale datasets describing soil moisture, evapotranspiration (ET), and or vegetation characteristics within agricultural regions of the contiguous United States (CONUS). These datasets have been developed using a variety of techniques, including, hydrologic modeling, satellite-based retrievals, data assimilation, and survey in-field data collection. The objectives are to assess the relative utility of each dataset for monitoring crop yield variability, to quantitatively assess their capacity for predicting end-of-season corn and soybean yields, and to examine the evolution of the yield-index correlations during the growing season. This analysis is unique both with regards to the number and variety of examined yield predictor datasets and the detailed assessment of the water availability timing on the end-of-season crop production during the growing season. Correlation results indicate that over CONUS, at state-level soil moisture and ET indices can provide better information for forecasting corn and soybean yields than vegetation-based indices such as normalized difference vegetation index. The strength of correlation with corn and soybean yields strongly depends on the interannual variability in yield measured at a given location. In this case study, some of the remotely derived datasets examined provide skill comparable to that of in situ field survey-based data further demonstrating the utility of these remote sensing-based approaches for estimating crop yield.

Land and atmosphere interactions using satellite remote sensing and a coupled mesoscale/land surface model

NASA Astrophysics Data System (ADS)

Hong, Seungbum

Land and atmosphere interactions have long been recognized for playing a key role in climate and weather modeling. However their quantification has been challenging due to the complex nature of the land surface amongst various other reasons. One of the difficult parts in the quantification is the effect of vegetation which are related to land surface processes such soil moisture variation and to atmospheric conditions such as radiation. This study addresses various relational investigations among vegetation properties such as Normalized Difference Vegetation Index (NDVI), Leaf Area Index (LAI), surface temperature (TSK), and vegetation water content (VegWC) derived from satellite sensors such as Moderate Resolution Imaging Spectroradiometer (MODIS) and EOS Advanced Microwave Scanning Radiometer (AMSR-E). The study provides general information about a physiological behavior of vegetation for various environmental conditions. Second, using a coupled mesoscale/land surface model, we examined the effects of vegetation and its relationship with soil moisture on the simulated land-atmospheric interactions through the model sensitivity tests. The Weather Research and Forecasting (WRF) model was selected for this study, and the Noah land surface model (Noah LSM) implemented in the WRF model was used for the model coupled system. This coupled model was tested through two parameterization methods for vegetation fraction using MODIS data and through model initialization of soil moisture from High Resolution Land Data Assimilation System (HRLDAS). Then, this study evaluates the model improvements for each simulation method.

Relations between soil moisture and satellite vegetation indices in the U.S. Corn Belt

USGS Publications Warehouse

Adegoke, Jimmy O.; Carleton, A.M.

2002-01-01

Satellite-derived vegetation indices extracted over locations representative of midwestern U.S. cropland and forest for the period 1990–94 are analyzed to determine the sensitivity of the indices to neutron probe soil moisture measurements of the Illinois Climate Network (ICN). The deseasoned (i.e., departures from multiyear mean annual cycle) soil moisture measurements are shown to be weakly correlated with the deseasoned full resolution (1 km × 1 km) normalized difference vegetation index (NDVI) and fractional vegetation cover (FVC) data over both land cover types. The association, measured by the Pearson-moment-correlation coefficient, is stronger over forest than over cropland during the growing season (April–September). The correlations improve successively when the NDVI and FVC pixel data are aggregated to 3 km × 3 km, 5 km × 5 km, and 7 km × 7 km areas. The improved correlations are partly explained by the reduction in satellite navigation errors as spatial aggregation occurs, as well as the apparent scale dependence of the NDVI–soil moisture association. Similarly, stronger relations are obtained with soil moisture data that are lagged by up to 8 weeks with respect to the vegetation indices, implying that soil moisture may be a useful predictor of warm season satellite-derived vegetation conditions. This study suggests that a “long-term” memory of several weeks is present in the near-surface hydrological characteristics, especially soil water content, of the Midwest Corn Belt. The memory is integrated into the satellite vegetation indices and may be useful for predicting crop yield estimates and surface temperature anomalies.

Consequences of systematic model drift in DYNAMO MJO hindcasts with SP-CAM and CAM5

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

Hannah, Walter M.; Maloney, Eric D.; Pritchard, Michael S.

Hindcast simulations of MJO events during the dynamics of the MJO (DYNAMO) field campaign are conducted with two models, one with conventional parameterization (CAM5) and a comparable model that utilizes superparameterization (SP–CAM). SP–CAM is shown to produce a qualitatively better reproduction of the fluctuations of precipitation and low–level zonal wind associated with the first two DYNAMO MJO events compared to CAM5. Interestingly, skill metrics using the real–time multivariate MJO index (RMM) suggest the opposite conclusion that CAM5 has more skill than SP–CAM. This inconsistency can be explained by a systematic increase of RMM amplitude with lead time, which results frommore » a drift of the large–scale wind field in SP–CAM that projects strongly onto the RMM index. CAM5 hindcasts exhibit a contraction of the moisture distribution, in which extreme wet and dry conditions become less frequent with lead time. SP–CAM hindcasts better reproduce the observed moisture distribution, but also have stronger drift patterns of moisture budget terms, such as an increase in drying by meridional advection in SP–CAM. This advection tendency in SP–CAM appears to be associated with enhanced off–equatorial synoptic eddy activity with lead time. In conclusion, systematic drift moisture tendencies in SP–CAM are of similar magnitude to intraseasonal moisture tendencies, and therefore are important for understanding MJO prediction skill.« less

Utilization of Satellite Data in Land Surface Hydrology: Sensitivity and Assimilation

NASA Technical Reports Server (NTRS)

Lakshmi, Venkataraman; Susskind, Joel

1999-01-01

This paper investigates the sensitivity of potential evapotranspiration to input meteorological variables, viz- surface air temperature and surface vapor pressure. The sensitivity studies have been carried out for a wide range of land surface variables such as wind speed, leaf area index and surface temperatures. Errors in the surface air temperature and surface vapor pressure result in errors of different signs in the computed potential evapotranspiration. This result has implications for use of estimated values from satellite data or analysis of surface air temperature and surface vapor pressure in large scale hydrological modeling. The comparison of cumulative potential evapotranspiration estimates using ground observations and satellite observations over Manhattan, Kansas for a period of several months shows very little difference between the two. The cumulative differences between the ground based and satellite based estimates of potential evapotranspiration amounted to less that 20mm over a 18 month period and a percentage difference of 15%. The use of satellite estimates of surface skin temperature in hydrological modeling to update the soil moisture using a physical adjustment concept is studied in detail including the extent of changes in soil moisture resulting from the assimilation of surface skin temperature. The soil moisture of the surface layer is adjusted by 0.9mm over a 10 day period as a result of a 3K difference between the predicted and the observed surface temperature. This is a considerable amount given the fact that the top layer can hold only 5mm of water.

Composition and abundance of tree regeneration

Treesearch

Todd F. Hutchinson; Elaine Kennedy Sutherland; Charles T. Scott

2003-01-01

The composition and abundance of tree seedlings and saplings in the four study areas in southern Ohio were related to soil moisture via a GIS-derived integrated moisture index and to soil texture and fertility. For seedlings, the total abundance of small stems (less than 30 cm tall) was significantly greater on xeric plots (81,987/ha) than on intermediate (54,531/ha)...

Clinical use of a ceramide-based moisturizer for treating dogs with atopic dermatitis

PubMed Central

Jung, Ji-young; Nam, Eui-hwa; Park, Seol-hee; Han, Seung-hee

2013-01-01

In humans, skin barrier dysfunction is thought to be responsible for enhanced penetration of allergens. Similar to conditions seen in humans, canine atopic dermatitis (CAD) is characterized by derangement of corneocytes and disorganization of intercellular lipids in the stratum corenum (SC) with decreased ceramide levels. This study was designed to evaluate the effects of a moisturizer containing ceramide on dogs with CAD. Dogs (n = 20, 3~8 years old) with mild to moderate clinical signs were recruited and applied a moisturizer containing ceramide for 4 weeks. Transepidermal water loss (TEWL), skin hydration, pruritus index for canine atopic dermatitis (PICAD) scores, and canine atopic dermatitis extent and severity index (CADESI) scores of all dogs were evaluated. Skin samples from five dogs were also examined with transmission electron microscopy (TEM) using ruthenium tetroxide. TEWL, PICAD, and CADESI values decreased (p < 0.05) and skin hydration increased dramatically over time (p < 0.05). Electron micrographs showed that the skin barrier of all five dogs was partially restored (p < 0.05). In conclusion, these results demonstrated that moisturizer containing ceramide was effective for treating skin barrier dysfunction and CAD symptoms. PMID:23814473

Effects of vegetation types on soil moisture estimation from the normalized land surface temperature versus vegetation index space

NASA Astrophysics Data System (ADS)

Zhang, Dianjun; Zhou, Guoqing

2015-12-01

Soil moisture (SM) is a key variable that has been widely used in many environmental studies. Land surface temperature versus vegetation index (LST-VI) space becomes a common way to estimate SM in optical remote sensing applications. Normalized LST-VI space is established by the normalized LST and VI to obtain the comparable SM in Zhang et al. (Validation of a practical normalized soil moisture model with in situ measurements in humid and semiarid regions [J]. International Journal of Remote Sensing, DOI: 10.1080/01431161.2015.1055610). The boundary conditions in the study were set to limit the point A (the driest bare soil) and B (the wettest bare soil) for surface energy closure. However, no limitation was installed for point D (the full vegetation cover). In this paper, many vegetation types are simulated by the land surface model - Noah LSM 3.2 to analyze the effects on soil moisture estimation, such as crop, grass and mixed forest. The locations of point D are changed with vegetation types. The normalized LST of point D for forest is much lower than crop and grass. The location of point D is basically unchanged for crop and grass.

Microbial secondary metabolites in school buildings inspected for moisture damage in Finland, The Netherlands and Spain.

PubMed

Peitzsch, Mirko; Sulyok, Michael; Täubel, Martin; Vishwanath, Vinay; Krop, Esmeralda; Borràs-Santos, Alicia; Hyvärinen, Anne; Nevalainen, Aino; Krska, Rudolf; Larsson, Lennart

2012-08-01

Secondary metabolites produced by fungi and bacteria are among the potential agents that contribute to adverse health effects observed in occupants of buildings affected by moisture damage, dampness and associated microbial growth. However, few attempts have been made to assess the occurrence of these compounds in relation to moisture damage and dampness in buildings. This study conducted in the context of the HITEA project (Health Effects of Indoor Pollutants: Integrating microbial, toxicological and epidemiological approaches) aimed at providing systematic information on the prevalence of microbial secondary metabolites in a large number of school buildings in three European countries, considering both buildings with and without moisture damage and/or dampness observations. In order to address the multitude and diversity of secondary metabolites a large number of more than 180 analytes was targeted in settled dust and surface swab samples using liquid chromatography/mass spectrometry (LC/MS) based methodology. While 42%, 58% and 44% of all samples collected in Spanish, Dutch and Finnish schools, respectively, were positive for at least one of the metabolites analyzed, frequency of detection for the individual microbial secondary metabolites - with the exceptions of emodin, certain enniatins and physcion - was low, typically in the range of and below 10% of positive samples. In total, 30 different fungal and bacterial secondary metabolites were found in the samples. Some differences in the metabolite profiles were observed between countries and between index and reference school buildings. A major finding in this study was that settled dust derived from moisture damaged, damp schools contained larger numbers of microbial secondary metabolites at higher levels compared to respective dust samples from schools not affected by moisture damage and dampness. This observation was true for schools in each of the three countries, but became statistically significant only when combining schools from all countries and thus increasing the sample number in the statistical analyses.

Terrestrial Ecosystems - Topographic Moisture Potential of the Conterminous United States

USGS Publications Warehouse

Cress, Jill J.; Sayre, Roger G.; Comer, Patrick; Warner, Harumi

2009-01-01

As part of an effort to map terrestrial ecosystems, the U.S. Geological Survey has generated topographic moisture potential classes to be used in creating maps depicting standardized, terrestrial ecosystem models for the conterminous United States, using an ecosystems classification developed by NatureServe. A biophysical stratification approach, developed for South America and now being implemented globally, was used to model the ecosystem distributions. Substrate moisture regimes strongly influence the differentiation and distribution of terrestrial ecosystems, and therefore topographic moisture potential is one of the key input layers in this biophysical stratification. The method used to produce these topographic moisture potential classes was based on the derivation of ground moisture potential using a combination of computed topographic characteristics (CTI, slope, and aspect) and mapped National Wetland Inventory (NWI) boundaries. This method does not use climate or soil attributes to calculate relative topographic moisture potential since these characteristics are incorporated into the ecosystem model though other input layers. All of the topographic data used for this assessment were derived from the USGS 30-meter National Elevation Dataset (NED ) including the National Compound Topographic Index (CTI). The CTI index is a topographically derived measure of slope for a raster cell and the contributing area from upstream raster cells, and thus expresses potential for water flow to a point. In other words CTI data are 'a quantification of the position of a site in the local landscape', where the lowest values indicate ridges and the highest values indicate stream channels, lakes and ponds. These CTI values were compared to independent estimates of water accumulation by obtaining geospatial data from a number of sample locations representing two types of NWI boundaries: freshwater emergent wetlands and freshwater forested/shrub wetlands. Where these shorelines (the interface between the NWI wetlands and adjacent land) occurred, the CTI values were extracted and a histogram of their statistical distributions was calculated. Based on an evaluation of these histograms, CTI thresholds were developed to separate periodically saturated or flooded land, mesic uplands (moderately moist), and uplands. After the range of CTI values for these three different substrate moisture regimes was determined, the CTI values were grouped into three initial topographic moisture potential classes. As a final step in the generation of this national data layer, the uplands classification was subdivided into either very dry uplands or dry uplands. Very dry uplands were defined as uplands with relatively steep, south-facing slopes, and identification of this class was based on the slope and aspect datasets derived from the NED. The remaining uplands that did not meet these additional criteria were simply re-classified as dry uplands. The final National Topographic Moisture Potential dataset for the conterminous United States contains four classes: periodically saturated or flooded land (CTI = 18.5), mesic uplands (12 = 24 degrees and 91 degrees =< Aspect =< 314 degrees). This map shows a smoothed and generalized image of the four topographic moisture potential classes. Additional information about this map and any of the data developed for the ecosystems modeling of the conterminous United States is available online at http://rmgsc.cr.usgs.gov/ecosystems/.

Drought monitoring of Tumen river basin wetlands between 1991 and 2016 using Landsat TM/ETM+

NASA Astrophysics Data System (ADS)

Yu, H.; Zhu, W.; Lee, W. K.; Heo, S.

2017-12-01

Wetlands area described as "the kidney of earth" owing to the importance of functions for stabilizing environment, long-term protection of water sources, as well as effectively minimize sediment loss, purify surface water from industrial and agricultural pollutants, and enhancing aquifer recharge. Drought monitoring in wetlands is vital due to the condition of water supply directly affecting the growth of wetland plants and local biodiversity. In this study, Vegetation Temperature Condition Index derived from Normalized Difference Vegetation Index and Land Surface Temperature is used to observe drought status from 1991 to 2016. For doing this, Landsat TM/ETM+ data for six periods are used to analytical processing. On the other hand, soil moisture maps which are acquired from CMA Land Data Assimilation System Version 1.0 for validating reliability of drought monitoring. As a result, the study shows most of area at normal moist level (decreased 25.8%) became slightly drought (increased 29.7%) in Tumen river basin cross-border (China and North Korea) wetland. The correlation between vegetation temperature condition index and soil moisture are 0.69, 0.32 and 0.2 for the layers of 0 5cm, 0 10cm, and 10 20cm, respectively. Although climate change probably contributes to the process of drought by decreasing precipitation and increasing temperature, human activities are shown as main factor that led to the process in this wetland.

Physico-chemical, nutritional and infrared spectroscopy evaluation of an optimized soybean/corn flour extrudate.

PubMed

Guzmán-Ortiz, Fabiola Araceli; Hernández-Sánchez, Humberto; Yee-Madeira, Hernani; San Martín-Martínez, Eduardo; Robles-Ramírez, María Del Carmen; Rojas-López, Marlon; Berríos, Jose De J; Mora-Escobedo, Rosalva

2015-07-01

A central composite design using RMS (Response Surface Methodology) successfully described the effect of independent variables (feed moisture, die temperature and soybean proportion) on the specific parameters of product quality as expansion index (EI), water absorption index (WAI), water solubility index (WSI) and total color difference (ΔE) studied. The regression model indicated that EI, WAI, WSI and ΔE were significant (p < 0.05) with coefficients of determination (R(2)) of 0.7371, 0.7588, 0.7622, 0.8150, respectively. The optimized processing conditions were obtained with 25.8 % feed moisture, 160 °C die temperature and 58 %/42 % soybean/corn proportion. It was not found statistically changes in amino acid profile due to extrusion process. The electrophoretic profile of extruded soybean/corn mix presented low intensity molecular weight bands, compared to the unprocessed sample. The generation of low molecular weight polypeptides was associated to an increased in In vitro protein digestibility (IVPD) of the extrudate. The FTIR spectra of the soybean/corn mix before and after extrusion showed that the α-helix structure remained unchanged after extrusion. However, the band associated with β-sheet structure showed to be split into two bands at 1624 and 1640 cm(-1) . The changes in the β-sheet structures may be also associated to the increased in IVPD in the extruded sample.

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.

Modeling Stand-Scale Patterns in Evapotranspiration and Soil Moisture in a Heterogeneous Plant Canopy: A Coupled Subsurface-Land Surface Approach

NASA Astrophysics Data System (ADS)

Miller, G. R.; Gou, S.; Ferguson, I. M.; Maxwell, R. M.

2011-12-01

Savanna ecosystems present a well-known modeling challenge; understory grasses and overstory woody vegetation combine to form an open, heterogeneous canopy that creates strong spatial differences in soil moisture and evapotranspiration rates. In this analysis, we used ParFlow.CLM to create a stand-scale model of the Tonzi Ranch oak savanna, based on extensive topography, vegetation, soil, and hydrogeology data collected at the site. Measurements included canopy distribution and ground surface elevation from airborne Lidar, depth to groundwater from deep piezometers, soil and rock hydraulic conductivity, and leaf area index. We then compared the results to the site's long-term data records of radiative flux partitioning, obtained using the eddy-covariance method, and soil moisture, collected via a distributed network of capacitance probes. In order to obtain good agreement between the measured and modeled values, we identified several necessary modifications to the current CLM parameterization. These changes included the addition of a "winter grass" type and the alteration of the root structure and water stress functions to accommodate uptake of groundwater by deep roots. Finally, we compared variograms of site parameters and response variables and performed a scaling analysis relating ET and soil moisture variance to sampling size.

The spatial distribution and temporal variation of desert riparian forests and their influencing factors in the downstream Heihe River basin, China

NASA Astrophysics Data System (ADS)

Ding, Jingyi; Zhao, Wenwu; Daryanto, Stefani; Wang, Lixin; Fan, Hao; Feng, Qiang; Wang, Yaping

2017-05-01

Desert riparian forests are the main restored vegetation community in Heihe River basin. They provide critical habitats and a variety of ecosystem services in this arid environment. Since desert riparian forests are also sensitive to disturbance, examining the spatial distribution and temporal variation of these forests and their influencing factors is important to determine the limiting factors of vegetation recovery after long-term restoration. In this study, field experiment and remote sensing data were used to determine the spatial distribution and temporal variation of desert riparian forests and their relationship with the environmental factors. We classified five types of vegetation communities at different distances from the river channel. Community coverage and diversity formed a bimodal pattern, peaking at the distances of 1000 and 3000 m from the river channel. In general, the temporal normalized difference vegetation index (NDVI) trend from 2000 to 2014 was positive at different distances from the river channel, except for the region closest to the river bank (i.e. within 500 m from the river channel), which had been undergoing degradation since 2011. The spatial distribution of desert riparian forests was mainly influenced by the spatial heterogeneity of soil properties (e.g. soil moisture, bulk density and soil particle composition). Meanwhile, while the temporal variation of vegetation was affected by both the spatial heterogeneity of soil properties (e.g. soil moisture and soil particle composition) and to a lesser extent, the temporal variation of water availability (e.g. annual average and variability of groundwater, soil moisture and runoff). Since surface (0-30 cm) and deep (100-200 cm) soil moisture, bulk density and the annual average of soil moisture at 100 cm obtained from the remote sensing data were regarded as major determining factors of community distribution and temporal variation, conservation measures that protect the soil structure and prevent soil moisture depletion (e.g. artificial soil cover and water conveyance channels) were suggested to better protect desert riparian forests under climate change and intensive human disturbance.

Impact of Different Elastomer Formulations on Moisture Permeation through Stoppers Used for Lyophilized Products Stored under Humid Conditions.

PubMed

Sasaki, Hitoshi; Kikuchi, Jun; Maeda, Terutoshi; Kuboniwa, Hitoshi

2010-01-01

The purpose of this study was to evaluate the effect of moisture permeability of different elastomer formulation stoppers, which had different moisture absorption abilities, on the increase of moisture content inside lyophilized vials during long-term storage under humid conditions. Two different elastomer formulation stoppers (high-moisture and low-moisture uptake stoppers) were compared. The increased amount of moisture content inside lyophilized vials fitted with high-moisture stoppers was higher than those fitted with low-moisture stoppers during the early stage of storage. However, this trend was reversed during the later stage of storage. Our data show that the moisture increase inside the lyophilized vials at the early stage was caused by moisture transfer from the stoppers, whereas the later moisture increase was caused by external moisture permeation through the stoppers. Results indicate that the difference in the moisture uptake profile inside the lyophilized vials at each period of storage was caused by the moisture absorption ability and moisture permeation ability of the two elastomer formulation stoppers. In terms of long-term storage stability under humid conditions, our data indicate that external moisture permeating through the stopper into the lyophilized vial during the late stage was the more important factor. In addition, the increase in moisture content at the early stage was controlled by stopper drying time. Furthermore, stopper drying time did not have an effect on moisture permeation at the late stage. Moisture permeation during the storage period appears to be dependent on the different elastomer formulations of the stoppers. The moisture permeation of different elastomer stoppers was an important factor in terms of the increased moisture content inside the lyophilized vials during the late stage of long-term storage under humid conditions. For lyophilized products stored at room temperature, the moisture permeation ability of the stopper is one of the most important factors for long-term storage stability.

Correcting the influence of vegetation on surface soil moisture indices by using hyperspectral artificial 3D-canopy models

NASA Astrophysics Data System (ADS)

Spengler, D.; Kuester, T.; Frick, A.; Scheffler, D.; Kaufmann, H.

2013-10-01

Surface soil moisture content is one of the key variables used for many applications especially in hydrology, meteorology and agriculture. Hyperspectral remote sensing provides effective methodologies for mapping soil moisture content over a broad area by different indices such as NSMI [1,2] and SMGM [3]. Both indices can achieve a high accuracy for non-vegetation influenced soil samples, but their accuracy is limited in case of the presence of vegetation. Since, the increase of the vegetation cover leads to non-linear variations of the indices. In this study a new methodology for moisture indices correcting the influence of vegetation is presented consisting of several processing steps. First, hyperspectral reflectance data are classified in terms of crop type and growth stage. Second, based on these parameters 3D plant models from a database used to simulate typical canopy reflectance considering variations in the canopy structure (e.g. plant density and distribution) and the soil moisture content for actual solar illumination and sensor viewing angles. Third, a vegetation correction function is developed, based on the calculated soil moisture indices and vegetation indices of the simulated canopy reflectance data. Finally this function is applied on hyperspectral image data. The method is tested on two hyperspectral image data sets of the AISA DUAL at the test site Fichtwald in Germany. The results show a significant improvements compared to solely use of NSMI index. Up to a vegetation cover of 75 % the correction function minimise the influences of vegetation cover significantly. If the vegetation is denser the method leads to inadequate quality to predict the soil moisture content. In summary it can be said that applying the method on weakly to moderately overgrown with vegetation locations enables a significant improvement in the quantification of soil moisture and thus greatly expands the scope of NSMI.

Effects of processing, particle size and moisturizing of sorghum-based feeds on pellet quality and broiler production.

PubMed

da Silva, Patrícia Garcia; Oliveira, Luana Martins Schaly; de Oliveira, Nayanne Rodrigues; de Moura Júnior, Fábio Ataides; Silva, Maura Regina Sousa; Cordeiro, Deibity Alves; Minafra, Cibele Silva; Dos Santos, Fabiana Ramos

2018-01-01

This study aimed to assess the effect of pelleted and expanded sorghum-based feeds prepared with different moisture levels and particle size of ingredients on metabolizable energy, ileal digestibility of amino acids and broiler performance. The experiment was performed with 720 male broiler chicks of the Cobb strain, with treatments of six replications, with 15 birds each; they were arranged in a completely randomized design and 2×2×2 factorial scheme (pelleted or expanded feed processing, 0.8% or 1.6% moisture addition in the mixer, and particle size of 650 or 850 microns). Higher pellet quality (pellets, % and pellet durability index [PDI]) was obtained in expanded diets and inclusion of 1.6% moisture. The particle size of 850 microns increased the PDI of final diet. All studied treatments had no significant effect on weight gain and broiler carcass and cut yields. Lower feed conversion occurred for birds fed pelleted feed at 42 d. The highest apparent metabolizable energy (AME) and apparent metabolizable energy corrected to zero nitrogen balance (AMEn) values of feed in the initial rearing phase (10 to 13 days) were observed in birds fed pelleted feed or for feed prepared with 1.6% moisture. The highest ileal digestibility coefficients of amino acids were obtained with the consumption of pelleted feed prepared with a particle size of 650 microns and 1.6% moisture. Pelleted feed prepared with a milling particle size of 650 microns and 1.6% moisture provided increased ileal digestibility of amino acids and AMEn in the starter period. However, the expanded feed improved pellet quality and feed conversion of broilers at 42 days of age. We conclude that factors such as moisture, particle size and processing affect the pellet quality, and therefore should be considered when attempting to optimize broiler performance.

Effects of processing, particle size and moisturizing of sorghum-based feeds on pellet quality and broiler production

PubMed Central

2018-01-01

Objective This study aimed to assess the effect of pelleted and expanded sorghum-based feeds prepared with different moisture levels and particle size of ingredients on metabolizable energy, ileal digestibility of amino acids and broiler performance. Methods The experiment was performed with 720 male broiler chicks of the Cobb strain, with treatments of six replications, with 15 birds each; they were arranged in a completely randomized design and 2×2×2 factorial scheme (pelleted or expanded feed processing, 0.8% or 1.6% moisture addition in the mixer, and particle size of 650 or 850 microns). Results Higher pellet quality (pellets, % and pellet durability index [PDI]) was obtained in expanded diets and inclusion of 1.6% moisture. The particle size of 850 microns increased the PDI of final diet. All studied treatments had no significant effect on weight gain and broiler carcass and cut yields. Lower feed conversion occurred for birds fed pelleted feed at 42 d. The highest apparent metabolizable energy (AME) and apparent metabolizable energy corrected to zero nitrogen balance (AMEn) values of feed in the initial rearing phase (10 to 13 days) were observed in birds fed pelleted feed or for feed prepared with 1.6% moisture. The highest ileal digestibility coefficients of amino acids were obtained with the consumption of pelleted feed prepared with a particle size of 650 microns and 1.6% moisture. Conclusion Pelleted feed prepared with a milling particle size of 650 microns and 1.6% moisture provided increased ileal digestibility of amino acids and AMEn in the starter period. However, the expanded feed improved pellet quality and feed conversion of broilers at 42 days of age. We conclude that factors such as moisture, particle size and processing affect the pellet quality, and therefore should be considered when attempting to optimize broiler performance. PMID:28920405

Multiscale analysis of surface soil moisture dynamics in a mesoscale catchment utilizing an integrated ecohydrological model

NASA Astrophysics Data System (ADS)

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

2012-12-01

Soil moisture is one of the fundamental variables in hydrology, meteorology and agriculture, influencing the partitioning of solar energy into latent and sensible heat flux as well as the partitioning of precipitation into runoff and percolation. Numerous studies have shown that in addition to natural factors (rainfall, soil, topography etc.) agricultural management is one of the key drivers for spatio-temporal patterns of soil moisture in agricultural landscapes. Interactions between plant growth, soil hydrology and soil nitrogen transformation processes are modeled by using a dynamically coupled modeling approach. The process-based ecohydrological model components of the integrated decision support system DANUBIA are used to identify the important processes and feedbacks determining soil moisture patterns in agroecosystems. Integrative validation of plant growth and surface soil moisture dynamics serves as a basis for a spatially distributed modeling analysis of surface soil moisture patterns in the northern part of the Rur catchment (1100 sq km), Western Germany. An extensive three year dataset (2007-2009) of surface soil moisture-, plant- (LAI, organ specific biomass and N) and soil- (texture, N, C) measurements was collected. Plant measurements were carried out biweekly for winter wheat, maize, and sugar beet during the growing season. Soil moisture was measured with three FDR soil moisture stations. Meteorological data was measured with an eddy flux station. The results of the model validation showed a very good agreement between the modeled plant parameters (biomass, green LAI) and the measured parameters with values between 0.84 and 0.98 (Willmotts index of agreement). The modeled surface soil moisture (0 - 20 cm) showed also a very favorable agreement with the measurements for winter wheat and sugar beet with an RMSE between 1.68 and 3.45 Vol.-%. For maize, the RMSE was less favorable particularly in the 1.5 months prior to harvest. The modeled soil moisture remained in contrast to the measurements very responsive to precipitation with high soil moisture after precipitation events. This behavior indicates that the soil properties might have changed due to the formation of a surface crust or seal towards the end of the growing season. Spatial soil moisture patterns were investigated using a grid resolution of 150 meter. Spatial autocorrelation was computed on a daily basis using patterns of soil texture as well as transpiration and precipitation indices as co-variables. Spatial patterns of surface soil moisture are mostly determined by the structure of the soil properties (soil type) during winter, early growing season and after harvest of all crops. Later in the growing season, after establishment of a closed canopy the dependence of the soil moisture patterns on soil texture patterns becomes smaller and diminishes quickly after precipitation events, due to differences of the transpiration rate of the different crops. When changing the spatial scale of the analysis, the highest autocorrelation values can be found on a grid cell size between 450 and 1200 meters. Thus, small scale variability of transpiration induced by the land use pattern almost averages out, leaving the larger scale structure of soil properties to explain the soil moisture patterns.

Analysis of Drought in North Darfur Region of Sudan: Application of the DPSIR Framework on Long Term Data

NASA Astrophysics Data System (ADS)

Mohmmed, Alnail; Zhange, Ke; Makomere, Reuben; Twecan, Dalson; Mohamme, Mustafa

2017-04-01

Darfur region in western Sudan is located in one of the world's most inhospitable environments, adjacent to the Sahara desert, conflicts and drought have severely degraded this fragile area, devastating the environment, livestock and people. Northern Darfur is bedeviled with frequent drought due to insufficient water resources, high summer temperatures, and poor precipitation. Monitoring drought and providing timely seasonal predictions is important for integrated drought risk reduction in the region. This paper evaluates drought conditions in North Darfur by applying meteorological, remote sensing and crop production data, as well as the Driving force-Pressure-State-Impacts-Response (DPSIR) assessment framework. Interviews, group discussions and participant observations were conducted in order to understand the DPSIR framework indicators. The relationship between the Reconnaissance Drought Index (RDI), Vegetation Condition Index (VCI) and Soil Moisture Content Index (SMCI) were evaluated utilizing data from all five North Darfur counties during 10 growing seasons (2004-2013). Our results showed a strong correlation between RDI, VCI, and SMAI. Also, a significant agreement was noticed between Yield Anomaly Index (YAI) and Rainfall Anomaly Index (RAI). Generally, a high correlation coefficient was obtained between the meteorology drought index and remote sensing indices, which demonstrates the effectiveness of the above indices for evaluating agricultural drought in the sub-Saharan area. Keywords: Drought; Vegetation Condition Index; Reconnaissance Drought Index; Soil Moisture Content Index; North Darfur.

North-East monsoon rainfall extremes over the southern peninsular India and their association with El Niño

NASA Astrophysics Data System (ADS)

Singh, Prem; Gnanaseelan, C.; Chowdary, J. S.

2017-12-01

The present study investigates the relationship between extreme north-east (NE) monsoon rainfall (NEMR) over the Indian peninsula region and El Niño forcing. This turns out to be a critical science issue especially after the 2015 Chennai flood. The puzzle being while most El Niños favour good NE monsoon, some don't. In fact some El Niño years witnessed deficit NE monsoon. Therefore two different cases (or classes) of El Niños are considered for analysis based on standardized NEMR index and Niño 3.4 index with case-1 being both Niño-3.4 and NEMR indices greater than +1 and case-2 being Niño-3.4 index greater than +1 and NEMR index less than -1. Composite analysis suggests that SST anomalies in the central and eastern Pacific are strong in both cases but large differences are noted in the spatial distribution of SST over the Indo-western Pacific region. This questions our understanding of NEMR as mirror image of El Niño conditions in the Pacific. It is noted that the favourable excess NEMR in case-1 is due to anomalous moisture transport from Bay of Bengal and equatorial Indian Ocean to southern peninsular India. Strong SST gradient between warm western Indian Ocean (and Bay of Bengal) and cool western Pacific induced strong easterly wind anomalies during NE monsoon season favour moisture transport towards the core NE monsoon region. Further anomalous moisture convergence and convection over the core NE monsoon region supported positive rainfall anomalies in case-1. While in case-2, weak SST gradients over the Indo-western Pacific and absence of local low level convergence over NE monsoon region are mainly responsible for deficit rainfall. The ocean dynamics in the Indian Ocean displayed large differences during case-1 and case-2, suggesting the key role of Rossby wave dynamics in the Indian Ocean on NE monsoon extremes. Apart from the large scale circulation differences the number of cyclonic systems land fall for case-1 and case-2 have also contributed for variations in NE monsoon rainfall extremes during El Niño years. This study indicates that despite having strong warming in the central and eastern Pacific, NE monsoon rainfall variations over the southern peninsular India is mostly determined by SST gradient over the Indo-western Pacific region and number of systems formation in the Bay of Bengal and their land fall. The paper concludes that though the favourable large scale circulation induced by Pacific is important in modulating the NE monsoon rainfall the local air sea interaction plays a key role in modulating or driving rainfall extremes associated with El Niño.

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.

Variations in annual water-energy balance and their correlations with vegetation and soil moisture dynamics: A case study in the Wei River Basin, China

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

Huang, Shengzhi; Huang, Qiang; Leng, Guoyong

It is of importance to investigate watershed water-energy balance variations and to explore their correlations with vegetation and soil moisture dynamics, which helps better understand the interplays between underlying surface dynamics and the terrestrial water cycle. The heuristic segmentation method was adopted to identify change points in the parameter to series in Fu's equation belonging to the Budyko framework in the Wei River Basin (WRB) and its sub-basins aiming to examine the validity of stationary assumptions. Additionally, the cross wavelet analysis was applied to explore the correlations between vegetation and soil moisture dynamics and to variations. Results indicated that (1)more » the omega variations in the WRB are significant, with some change points identified except for the sub-basin above Zhangjiashan, implying that the stationarity of omega series in the WRB is invalid except for the sub-basin above Zhangjiashan; (2) the correlations between soil moisture series and to series are weaker than those between Normalized Difference Vegetation Index (NDVI) series and omega series; (3) vegetation dynamics show significantly negative correlations with omega variations in 1983-2003 with a 4-8 year signal in the whole WRB, and both vegetation and soil moisture dynamics exert strong impacts on the parameter omega changes. This study helps understanding the interactions between underlying land surface dynamics and watershed water-energy balance. (C) 2017 Elsevier B.V. All rights reserved.« less

Interactive initialization of heat flux parameters for numerical models using satellite temperature measurements. [Kansas and Indiana

NASA Technical Reports Server (NTRS)

Carlson, T. N. (Principal Investigator)

1982-01-01

A method for obtaining patterns of moisture availability (and net evaporation) from satellite infrared measurements employs Carlson's boundary layer model and a variety of image processing routines executed by a minicomputer. To test the method with regard to regional scale moisture analyses, two case studies were chosen because of the availability of HCMM data and because of the presence of a large horizontal gradient in antecedent precipitation and crp moisture index. Results show some correlation in both cases between antecedent precipitation and derived moisture availability. Apparently, regional-scale moisture availability patterns can be determined with some degree of fidelity but the values themselves may be useful only in the relative sense and significant to within plus or minus one category of dryness over a range of 4 or 5 categories between absolutely dry and field saturation. Preliminary results suggest that the derived moisture values correlate best with longer-term precipitation totals, suggesting that the infrared temperatures respond more sensitively to a relatively deep substrate layer.

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.

Retrieval of canopy moisture content for dynamic fire risk assessment using simulated MODIS bands

NASA Astrophysics Data System (ADS)

Maffei, Carmine; Leone, Antonio P.; Meoli, Giuseppe; Calabrò, Gaetano; Menenti, Massimo

2007-10-01

Forest fires are one of the major environmental hazards in Mediterranean Europe. Biomass burning reduces carbon fixation in terrestrial vegetation, while soil erosion increases in burned areas. For these reasons, more sophisticated prevention tools are needed by local authorities to forecast fire danger, allowing a sound allocation of intervention resources. Various factors contribute to the quantification of fire hazard, and among them vegetation moisture is the one that dictates vegetation susceptibility to fire ignition and propagation. Many authors have demonstrated the role of remote sensing in the assessment of vegetation equivalent water thickness (EWT), which is defined as the weight of liquid water per unit of leaf surface. However, fire models rely on the fuel moisture content (FMC) as a measure of vegetation moisture. FMC is defined as the ratio of the weight of the liquid water in a leaf over the weight of dry matter, and its retrieval from remote sensing measurements might be problematic, since it is calculated from two biophysical properties that independently affect vegetation reflectance spectrum. The aim of this research is to evaluate the potential of the Moderate Resolution Imaging Spectrometer (MODIS) in retrieving both EWT and FMC from top of the canopy reflectance. The PROSPECT radiative transfer code was used to simulate leaf reflectance and transmittance as a function of leaf properties, and the SAILH model was adopted to simulate the top of the canopy reflectance. A number of moisture spectral indexes have been calculated, based on MODIS bands, and their performance in predicting EWT and FMC has been evaluated. Results showed that traditional moisture spectral indexes can accurately predict EWT but not FMC. However, it has been found that it is possible to take advantage of the multiple MODIS short-wave infrared (SWIR) channels to improve the retrieval accuracy of FMC (r2 = 0.73). The effects of canopy structural properties on MODIS estimates of FMC have been evaluated, and it has been found that the limiting factor is leaf area index (LAI). The best results are recorded for LAI>2 (r2 = 0.83), while acceptable results (r2 = 0.58) can still be achieved for lower vegetation cover density.

Unified Science Information Model for SoilSCAPE using the Mercury Metadata Search System

NASA Astrophysics Data System (ADS)

Devarakonda, Ranjeet; Lu, Kefa; Palanisamy, Giri; Cook, Robert; Santhana Vannan, Suresh; Moghaddam, Mahta Clewley, Dan; Silva, Agnelo; Akbar, Ruzbeh

2013-12-01

SoilSCAPE (Soil moisture Sensing Controller And oPtimal Estimator) introduces a new concept for a smart wireless sensor web technology for optimal measurements of surface-to-depth profiles of soil moisture using in-situ sensors. The objective is to enable a guided and adaptive sampling strategy for the in-situ sensor network to meet the measurement validation objectives of spaceborne soil moisture sensors such as the Soil Moisture Active Passive (SMAP) mission. This work is being carried out at the University of Michigan, the Massachusetts Institute of Technology, University of Southern California, and Oak Ridge National Laboratory. At Oak Ridge National Laboratory we are using Mercury metadata search system [1] for building a Unified Information System for the SoilSCAPE project. This unified portal primarily comprises three key pieces: Distributed Search/Discovery; Data Collections and Integration; and Data Dissemination. Mercury, a Federally funded software for metadata harvesting, indexing, and searching would be used for this module. Soil moisture data sources identified as part of this activity such as SoilSCAPE and FLUXNET (in-situ sensors), AirMOSS (airborne retrieval), SMAP (spaceborne retrieval), and are being indexed and maintained by Mercury. Mercury would be the central repository of data sources for cal/val for soil moisture studies and would provide a mechanism to identify additional data sources. Relevant metadata from existing inventories such as ORNL DAAC, USGS Clearinghouse, ARM, NASA ECHO, GCMD etc. would be brought in to this soil-moisture data search/discovery module. The SoilSCAPE [2] metadata records will also be published in broader metadata repositories such as GCMD, data.gov. Mercury can be configured to provide a single portal to soil moisture information contained in disparate data management systems located anywhere on the Internet. Mercury is able to extract, metadata systematically from HTML pages or XML files using a variety of methods including OAI-PMH [3]. The Mercury search interface then allows users to perform simple, fielded, spatial and temporal searches across a central harmonized index of metadata. Mercury supports various metadata standards including FGDC, ISO-19115, DIF, Dublin-Core, Darwin-Core, and EML. This poster describes in detail how Mercury implements the Unified Science Information Model for Soil moisture data. References: [1]Devarakonda R., et al. Mercury: reusable metadata management, data discovery and access system. Earth Science Informatics (2010), 3(1): 87-94. [2]Devarakonda R., et al. Daymet: Single Pixel Data Extraction Tool. http://daymet.ornl.gov/singlepixel.html (2012). Last Accesses 10-01-2013 [3]Devarakonda R., et al. Data sharing and retrieval using OAI-PMH. Earth Science Informatics (2011), 4(1): 1-5.

Physical evaluation of a maize-based extruded snack with curry powder.

PubMed

Christofides, Vassilis; Ainsworth, Paul; Ibanoğlu, Senol; Gomes, Frances

2004-02-01

Response surface methodology was used to analyze the effect of screw speed (200-280 rpm), feed moisture (13.0-17.0%, wet basis), and curry powder (6.0-9.0%) on the bulk density, lateral expansion, and firmness of maize-based extruded snack with curry powder. Regression equations describing the effect of each variable on the responses were obtained. Responses were most affected by changes in feed moisture followed by screw speed and curry powder (p < 0.05). Lateral expansion increased linearly as the amount of curry powder added was increased whereas a quadratic increase was obtained in lateral expansion with decreasing feed moisture. The firmness of samples was increased with an increase in feed moisture. The bulk density of samples was increased with increasing feed moisture and screw speeds. Radial expansion was found to be a better index to measure the physical properties of the extruded product indicated by a higher correlation coefficient.

Case studies using GOES infrared data and a planetary boundary layer model to infer regional scale variations in soil moisture. M.S. Thesis

NASA Technical Reports Server (NTRS)

Rose, F. G.

1983-01-01

Modeled temperature data from a one-dimensional, time-dependent, initial value, planetary boundary layer model for 16 separate model runs with varying initial values of moisture availability are applied, by the use of a regression equation, to longwave infrared GOES satellite data to infer moisture availability over a regional area in the central U.S. This was done for several days during the summers of 1978 and 1980 where a large gradient in the antecedent precipitation index (API) represented the boundary between a drought area and a region of near normal precipitation. Correlations between satellite derived moisture availability and API were found to exist. Errors from the presence of clouds, water vapor and other spatial inhomogeneities made the use of the measurement for anything except the relative degree of moisture availability dubious.

Impact of realistic soil moisture initialization on the representation of extreme events in the western Mediterranean

NASA Astrophysics Data System (ADS)

Helgert, Sebastian; Khodayar, Samiro

2017-04-01

In a warmer Mediterranean climate an increase in the intensity and frequency of extreme events like floods, droughts and extreme heat is expected. The ability to predict such events is still a great challenge and exhibits many uncertainties in the weather forecast and climate predictions. Thereby the missing knowledge about soil moisture-atmosphere interactions and their representation in models is identified as one of the main sources of uncertainty. In this context the soil moisture(SM) plays an important role in the partitioning of sensible and latent heat fluxes on the surface and consequently influences the boundary-layer stability and the precipitation formation. The aim of this research work is to assess the influence of soil moisture-atmosphere interactions on the initiation and development of extreme events in the western Mediterranean (WMED). In this respect the impact of realistic SM initialization on the model representation of extreme events is investigated. High-resolution simulations of different regions in the WMED, including various climate zones from moderate to arid climate, are conducted with the atmospheric COSMO (Consortium for Small-scale Modeling) model in the numerical weather prediction and climate mode. A multiscale temporal and spatial approach is used (days to years, 7km to 2.8km grid spacing). Observational data provided by the framework of the HYdrological cycle in the Mediterranean EXperiment (HyMeX) as well as satellite data such as precipitation from CMORPH (CPC MORPHing technique), evapotranspiration from Land Surface Analysis Satellite Applications Facility (LSA-SAF) and atmospheric moisture from MODIS (Moderate Resolution Imaging Spectroradiometer) are used for process understanding and model validation. To select extreme dry and wet periods the Effective Drought Index (EDI) is calculated. In these periods sensitivity studies of extreme SM initialization scenarios are performed to prove a possible impact of soil moisture on precipitation in the WMED. For the realistic SM initialization different state-of-art high-resolution SM products (25km up to 1km grid spacing) of the Soil Moisture Ocean Salinity mission (SMOS) are examined. A CDF-matching method is applied to reduce the bias between model and SMOS-satellite observation. Moreover, techniques to estimate the initial soil moisture profile from satellite data are tested.

A multi-model analysis of moisture changes during the last glacial maximum

NASA Astrophysics Data System (ADS)

Liu, Shanshan; Jiang, Dabang; Lang, Xianmei

2018-07-01

This study investigates terrestrial moisture changes and associated mechanisms during the last glacial maximum (LGM; approximately 21,000 calendar years ago) using multi-model simulations from the Paleoclimate Modelling Intercomparison Project phase 3 (PMIP3). Considering that terrestrial moisture is not determined solely by precipitation, an aridity index (AI) is employed for measuring the terrestrial moisture by combining the effects of both precipitation and potential evapotranspiration (PET), where the latter represents atmospheric water demand and is greatly decreased mainly by the intense cooling during the LGM. Compared to the preindustrial period, the magnitude of global mean terrestrial moisture change is small, as the wetness brought by decreased PET counteracts the dryness induced by decreased precipitation. Regionally, the moisture changes depend on the different combinations of changes in precipitation and PET: (i) drying occurs where precipitation deceases and PET hardly changes, such as the northern tropical Americas and Southeast Asia; (ii) wetting is found in regions with precipitation increases and PET decreases (e.g., northwestern Africa and the central Andes), and their contributions are comparable; (iii) in particular, wetting can also occur in regions of decreased precipitation if a sufficient decrease in PET also occurs (i.e., southeastern North America and the northern and southern parts of eastern Asia), with the latter wetting effect reversing the former drying effect. The multi-model median field is consistent with available paleo-records in southern North America, the northern tropical Americas, the Andes, northwestern Africa, the southern Iberian Peninsula, southwestern Africa, the central part of eastern Asia, and Java but disagrees with proxies in Australia, central Brazil, southeastern Africa, the northern Iberian Peninsula, and the southern part of eastern Asia.

The Global Integrated Drought Monitoring and Prediction System (GIDMaPS): Overview and Capabilities

NASA Astrophysics Data System (ADS)

AghaKouchak, A.; Hao, Z.; Farahmand, A.; Nakhjiri, N.

2013-12-01

Development of reliable monitoring and prediction indices and tools are fundamental to drought preparedness and management. Motivated by the Global Drought Information Systems (GDIS) activities, this paper presents the Global Integrated Drought Monitoring and Prediction System (GIDMaPS) which provides near real-time drought information using both remote sensing observations and model simulations. The monthly data from the NASA Modern-Era Retrospective analysis for Research and Applications (MERRA-Land), North American Land Data Assimilation System (NLDAS), and remotely sensed precipitation data are used as input to GIDMaPS. Numerous indices have been developed for drought monitoring based on various indicator variables (e.g., precipitation, soil moisture, water storage). Defining droughts based on a single variable (e.g., precipitation, soil moisture or runoff) may not be sufficient for reliable risk assessment and decision making. GIDMaPS provides drought information based on multiple indices including Standardized Precipitation Index (SPI), Standardized Soil Moisture Index (SSI) and the Multivariate Standardized Drought Index (MSDI) which combines SPI and SSI probabilistically. In other words, MSDI incorporates the meteorological and agricultural drought conditions for overall characterization of droughts. The seasonal prediction component of GIDMaPS is based on a persistence model which requires historical data and near-past observations. The seasonal drought prediction component is based on two input data sets (MERRA and NLDAS) and three drought indicators (SPI, SSI and MSDI). The drought prediction model provides the empirical probability of drought for different severity levels. In this presentation, both monitoring and prediction components of GIDMaPS will be discussed, and the results from several major droughts including the 2013 Namibia, 2012-2013 United States, 2011-2012 Horn of Africa, and 2010 Amazon Droughts will be presented. The results indicate that GIDMaPS advances our drought monitoring and prediction capabilities through integration of multiple data and indicators.

Influence of pin and hammer mill on grinding characteristics, thermal and antioxidant properties of coriander powder.

PubMed

Barnwal, P; Singh, K K; Sharma, Alka; Choudhary, A K; Saxena, S N

2015-12-01

In present study, influence of grinding (hammer and pin mills) and moisture content (range: 6.4-13.6 % dry basis) on the quality traits of coriander powder were investigated. These include grinding parameters, colour parameters, specific heat, thermal conductivity, thermal diffusivity, glass transition temperature, essential oil, total phenolic content, total flavonoid content and DPPH scavenging (%) of coriander powder. For coriander seed, the geometric properties such as major, medium, minor dimensions, geometric mean diameter, arithmetic mean diameter, sphericity, surface area and volume of coriander seeds increased significantly with increasing moisture (6.4-13.6 % db). For coriander powder, the grinding parameters such as average particle size, volume surface mean diameter and volume mean diameter increased significantly with increasing moisture (6.4-13.6 % db). With the grinding method, the colour attributes of coriander powder such as L-value, a-value, b-value, hue angle and browning index varied significantly. It was observed that the specific heat followed second order polynomial relationship with temperature and moisture whereas thermal conductivity varied linearly with temperature and moisture content. The variation of glass transition temperature with moisture can be best represented in quadratic manner. Total flavonoid content (mg QE/g crude seed extract) and DPPH scavenging % activity of coriander powder is significantly affected by grinding methods. A lower value of specific heat was observed for hammer ground coriander powder as compared to pin mill ground coriander powder. The thermal conductivity of hammer mill ground coriander powder was higher as compared to pin mill ground coriander. It was observed that hammer mill yields more fine coriander powder in comparison to pin mill. The browning index was more in hammer mill ground coriander powder.

Exploring the Influence of Topography on Belowground C Processes Using a Coupled Hydrologic-Biogeochemical Model

NASA Astrophysics Data System (ADS)

Shi, Y.; Davis, K. J.; Eissenstat, D. M.; Kaye, J. P.; Duffy, C.; Yu, X.; He, Y.

2014-12-01

Belowground carbon processes are affected by soil moisture and soil temperature, but current biogeochemical models are 1-D and cannot resolve topographically driven hill-slope soil moisture patterns, and cannot simulate the nonlinear effects of soil moisture on carbon processes. Coupling spatially-distributed physically-based hydrologic models with biogeochemical models may yield significant improvements in the representation of topographic influence on belowground C processes. We will couple the Flux-PIHM model to the Biome-BGC (BBGC) model. Flux-PIHM is a coupled physically-based land surface hydrologic model, which incorporates a land-surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model. Because PIHM is capable of simulating lateral water flow and deep groundwater, Flux-PIHM is able to represent the link between groundwater and the surface energy balance, as well as the land surface heterogeneities caused by topography. The coupled Flux-PIHM-BBGC model will be tested at the Susquehanna/Shale Hills critical zone observatory (SSHCZO). The abundant observations, including eddy covariance fluxes, soil moisture, groundwater level, sap flux, stream discharge, litterfall, leaf area index, above ground carbon stock, and soil carbon efflux, make SSHCZO an ideal test bed for the coupled model. In the coupled model, each Flux-PIHM model grid will couple a BBGC cell. Flux-PIHM will provide BBGC with soil moisture and soil temperature information, while BBGC provides Flux-PIHM with leaf area index. Preliminary results show that when Biome- BGC is driven by PIHM simulated soil moisture pattern, the simulated soil carbon is clearly impacted by topography.

Investigating Soil Moisture Feedbacks on Precipitation With Tests of Granger Causality

NASA Astrophysics Data System (ADS)

Salvucci, G. D.; Saleem, J. A.; Kaufmann, R.

2002-05-01

Granger causality (GC) is used in the econometrics literature to identify the presence of one- and two-way coupling between terms in noisy multivariate dynamical systems. Here we test for the presence of GC to identify a soil moisture (S) feedback on precipitation (P) using data from Illinois. In this framework S is said to Granger cause P if F(Pt;At-dt)does not equal F(P;(A-S)t-dt) where F denotes the conditional distribution of P at time t, At-dt represents the set of all knowledge available at time t-dt, and (A-S)t-dt represents all knowledge available at t-dt except S. Critical for land-atmosphere interaction research is that At-dt includes all past information on P as well as S. Therefore that part of the relation between past soil moisture and current precipitation which results from precipitation autocorrelation and soil water balance will be accounted for and not attributed to causality. Tests for GC usually specify all relevant variables in a coupled vector autoregressive (VAR) model and then calculate the significance level of decreased predictability as various coupling coefficients are omitted. But because the data (daily precipitation and soil moisture) are distinctly non-Gaussian, we avoid using a VAR and instead express the daily precipitation events as a Markov model. We then test whether the probability of storm occurrence, conditioned on past information on precipitation, changes with information on soil moisture. Past information on precipitation is expressed both as the occurrence of previous day precipitation (to account for storm-scale persistence) and as a simple soil moisture-like precipitation-wetness index derived solely from precipitation (to account for seasonal-scale persistence). In this way only those fluctuations in moisture not attributable to past fluctuations in precipitation (e.g., those due to temperature) can influence the outcome of the test. The null hypothesis (no moisture influence) is evaluated by comparing observed changes in storm probability to Monte-Carlo simulated differences generated with unconditional occurrence probabilities. The null hypothesis is not rejected (p>0.5) suggesting that contrary to recently published results, insufficient evidence exists to support an influence of soil moisture on precipitation in Illinois.

The impact of moisture sources on the oxygen isotope composition of precipitation at a continental site in central Europe

NASA Astrophysics Data System (ADS)

Krklec, Kristina; Domínguez-Villar, David; Lojen, Sonja

2018-06-01

The stable isotope composition of precipitation records processes taking place within the hydrological cycle. Potentially, moisture sources are important controls on the stable isotope composition of precipitation, but studies focused on this topic are still scarce. We studied the moisture sources contributing to precipitation at Postojna (Slovenia) from 2009 to 2013. Back trajectory analyses were computed for the days with precipitation at Postojna. The moisture uptake locations were identified along these trajectories using standard hydrometeorological formulation. The moisture uptake locations were integrated in eight source regions to facilitate its comparison to the monthly oxygen isotope composition (δ18O values) of precipitation. Nearly half of the precipitation originated from continental sources (recycled moisture), and >40% was from central and western Mediterranean. Results show that moisture sources do not have a significant impact on the oxygen isotope composition at this site. We suggest that the large proportion of recycled moisture originated from transpiration rather than evaporation, which produced water vapour with less negative δ18O values. Thus the difference between the oceanic and local vapour source was reduced, which prevented the distinction of the moisture sources based on their oxygen isotope signature. Nevertheless, δ18O values of precipitation are partially controlled by climate parameters, which is of major importance for paleoclimate studies. We found that the main climate control on Postojna δ18O values of precipitation is the surface temperature. Amount effect was not recorded at this site, and the winter North Atlantic Oscillation (NAO) does not impact the δ18O values of precipitation. The Western Mediterranean Oscillation (WeMO) was correlated to oxygen stable isotope composition, although this atmospheric pattern was not a control. Instead we found that the link to δ18O values results from synoptic scenarios affecting WeMO index as well as temperature. Therefore, interpretation of δ18O values of precipitation in terms of climate is limited to surface temperature, although at least half of the variability observed still depends on unknown controls of the hydrological cycle.

Comparative drought resistance of five conifers and foliage moisture content as a viability index.

Treesearch

Richard P. Pharis

1966-01-01

Whole plant lethal points of foliage moisture content (FMC) for ponderosa pine, sugar pine, Douglas-fir, grand fir, and incense-cedar were established from foliage tissue of various ages. Exact lethal level depended upon the age of the tissue, but there was a general plateau between the ages 6 and 13 months for sugar pine and Douglas-fir and 3 and 13 months for incense...

Improvement of plastic optical fiber microphone based on moisture pattern sensing in devoiced breath

NASA Astrophysics Data System (ADS)

Taki, Tomohito; Honma, Satoshi; Morisawa, Masayuki; Muto, Shinzo

2008-03-01

Conversation is the most practical and common form in communication. However, people with a verbal handicap feel a difficulty to produce words due to variations in vocal chords. This research leads to develop a new devoiced microphone system based on distinguishes between the moisture patterns for each devoiced breaths, using a plastic optical fiber (POF) moisture sensor. In the experiment, five POF-type moisture sensors with fast response were fabricated by coating swell polymer with a slightly larger refractive index than that of fiber core and were set in front of mouth. When these sensors are exposed into humid air produced by devoiced breath, refractive index in cladding layer decreases by swelling and then the POF sensor heads change to guided type. Based on the above operation principle, the output light intensities from the five sensors set in front of mouth change each other. Using above mentioned output light intensity patterns, discernment of devoiced vowels in Japanese (a,i,u,e,o) was tried by means of DynamicProgramming-Matching (DP-matching) method. As the result, distinction rate over 90% was obtained to Japanese devoiced vowels. Therefore, using this system and a voice synthesizer, development of new microphone for the person with a functional disorder in the vocal chords seems to be possible.

Upper-soil moisture inter-comparison from SMOS's products and land surface models over the Iberian Peninsula

NASA Astrophysics Data System (ADS)

Polcher, Jan; Barella-Ortiz, Anaïs; Aires, Filipe; Balsamo, Gianpaolo; Gelati, Emiliano; Rodríguez-Fernández, Nemesio

2015-04-01

Soil moisture is a key state variable of the hydrological cycle. It conditions runoff, infiltration and evaporation over continental surfaces, and is key for forecasting droughts and floods. It plays thus an important role in surface-atmosphere interactions. Surface Soil Moisture (SSM) can be measured by in situ measurements, by satellite observations or modelled using land surface models. As a complementary tool, data assimilation can be used to combine both modelling and satellite observations. The work presented here is an inter-comparison of retrieved and modelled SSM data, for the 2010 - 2012 period, over the Iberian Peninsula. The region has been chosen because its vegetation cover is not very dense and includes strong contrasts in the rainfall regimes and thus a diversity of behaviours for SSM. Furthermore this semi-arid region is strongly dependent on a good management of its water resources. Satellite observations correspond to the Soil Moisture and Ocean Salinity (SMOS) retrievals: the L2 product from an optimal interpolation retrieval, and 3 other products using Neural Network retrievals with different input information: SMOS time indexes, purely SMOS data, or addition of the European Advanced Scaterometer (ASCAT) backscattering, and the Moderate-Resolution Imaging Spectrometer (MODIS) surface temperature information. The modelled soil moistures have been taken from the ORCHIDEE (ORganising Carbon and Hydrology In Dynamic EcosystEms) and the HTESSEL (Hydrology-Tiled ECMWF Scheme for Surface Exchanges over Land) land surface models. Both models are forced with the same atmospheric conditions (as part of the Earth2Observe FP7 project) over the period but they represent the surface soil moisture with very different degrees of complexity. ORCHIDEE has 5 levels in the top 5 centimetres of soil while in HTESSEL this variable is part of the top soil moisture level. The two types of SMOS retrievals are compared to the model outputs in their spatial and temporal characteristics. The comparison with the model helps to identify which retrieval configuration is most consistent with our understanding of surface soil moisture in this region. In particular we have determined how each of the soil moisture products is related to the spatio-temporal variations of rainfall. In large parts of the Iberian Peninsula the co-variance of remote sensed SSM and rainfall is consistent with that of the models. But for some regions questions are raised. The variability of SSM observed by SMOS in the North West of the Iberian Peninsula is similar to that of rainfall, at least this relation of SSM and rainfall is closer than suggested by the two models.

Relationship Between Palmer's Drought Severity Index and the Moisture Index of Woody Debris in the Southern Coastal Plain

Treesearch

James D. Haywood; Richard H. Stagg; Allan E. Tiarks

2004-01-01

After the 1998 through 2000 drought in Louisiana, some prescribed burns had uncommonly severe fire behavior. A significant portion of the consumed fuels most likely were larger material normally unavailable for burning. Therefore at sites in Louisiana, Mississippi, and Texas, we studied the relationship between Palmer’s Drought Severity Index (PDSI) and the drying rate...

An algorithm for temperature correcting substrate moisture measurements: aligning substrate moisture responses with environmental drivers in polytunnel-grown strawberry plants

NASA Astrophysics Data System (ADS)

Goodchild, Martin; Janes, Stuart; Jenkins, Malcolm; Nicholl, Chris; Kühn, Karl

2015-04-01

The aim of this work is to assess the use of temperature corrected substrate moisture data to improve the relationship between environmental drivers and the measurement of substrate moisture content in high porosity soil-free growing environments such as coir. Substrate moisture sensor data collected from strawberry plants grown in coir bags installed in a table-top system under a polytunnel illustrates the impact of temperature on capacitance-based moisture measurements. Substrate moisture measurements made in our coir arrangement possess the negative temperature coefficient of the permittivity of water where diurnal changes in moisture content oppose those of substrate temperature. The diurnal substrate temperature variation was seen to range from 7° C to 25° C resulting in a clearly observable temperature effect in substrate moisture content measurements during the 23 day test period. In the laboratory we measured the ML3 soil moisture sensor (ThetaProbe) response to temperature in Air, dry glass beads and water saturated glass beads and used a three-phase alpha (α) mixing model, also known as the Complex Refractive Index Model (CRIM), to derive the permittivity temperature coefficients for glass and water. We derived the α value and estimated the temperature coefficient for water - for sensors operating at 100MHz. Both results are good agreement with published data. By applying the CRIM equation with the temperature coefficients of glass and water the moisture temperature coefficient of saturated glass beads has been reduced by more than an order of magnitude to a moisture temperature coefficient of

Diamondlike carbon as a moisture barrier and antireflecting coating on optical materials

NASA Technical Reports Server (NTRS)

Woollam, John A.; De, Bhola N.; Chen, L. Y.; Pouch, John J.; Alterovitz, Samuel A.

1990-01-01

Diamondlike carbon (DLC) is amorphous, hard, semitransparent, and is under consideration for use as a coating material for infrared optics. DLC is also designated as a-C:H to indicate its amorphous nature as well as to indicate the presence of large (20 to 55 percent) amounts of hydrogen in the film. Two important questions arise with respect to use of DLC in infrared optics. Will the lack of grain boundaries help to keep moisture from penetrating the film. Secondly, application as an antireflection coating places restrictions on the allowed values of the index of refraction of the film relative to the particular substrate material being used. Will DLC have the correct index range. These two questions are addressed in this paper.

Predicting Soil Strength in Terms of Cone Index and California Bearing Ratio for Trafficability

DTIC Science & Technology

2016-03-01

conditions, however, soil strength will be a key factor. The Wet- Slippery conditions are considered when the top layer has reached a point of...the soil . Modeling moisture content of a soil in a layered system can be conducted using a finite difference water budget model illustrated in...Figure 2 (Sellers et al. 1986). Figure 2 shows how flow Q through the soil layer ij is modeled. In general, saturation of layer Qi due to rainfall is

PROTOCOL TO EVALUATE THE MOISTURE DURABILITY OF ENERGY-EFFICIENT WALLS

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

Boudreaux, Philip R; Pallin, Simon B; Hun, Diana E

Walls account for about 8% of the energy used in residential buildings. This energy penalty can be reduced with higher insulation levels and increased airtightness. However, these measures can compromise the moisture durability and long-term performance of wall assemblies because they can lead to lower moisture tolerance due to reduced drying potential. To avert these problems, a moisture durability protocol was developed to evaluate the probability that an energy-efficient wall design will experience mold growth. This protocol examines the effects of moisture sources in walls through a combination of simulations and lab experiments, uses the mold growth index as themore » moisture durability indicator, and is based on a probabilistic approach that utilizes stochastically varying input parameters. The simulation tools used include a new validated method for taking into account the effects of air leakage in wall assemblies This paper provides an overview of the developed protocol, discussion of the probabilistic simulation approach and describes results from the evaluation of two wall assemblies in Climate Zones 2, 4, and 6. The protocol will be used to supply builders with wall designs that are energy efficient, moisture durable and cost-effective.« less

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Linking Soil Moisture Variation and Abundance of Plants to Geomorphic Processes: A Generalized Model for Erosion-Uplifting Landscapes

NASA Astrophysics Data System (ADS)

Ding, Junyan; Johnson, Edward A.; Martin, Yvonne E.

2018-03-01

The diffusive and advective erosion-created landscapes have similar structure (hillslopes and channels) across different scales regardless of variations in drivers and controls. The relative magnitude of diffusive erosion to advective erosion (D/K ratio) in a landscape development model controls hillslope length, shape, and drainage density, which regulate soil moisture variation, one of the critical resources of plants, through the contributing area (A) and local slope (S) represented by a topographic index (TI). Here we explore the theoretical relation between geomorphic processes, TI, and the abundance and distribution of plants. We derived an analytical model that expresses the TI with D, K, and A. This gives us the relation between soil moisture variation and geomorphic processes. Plant tolerance curves are used to link plant performance to soil moisture. Using the hypothetical tolerance curves of three plants, we show that the abundance and distribution of xeric, mesic, and hydric plants on the landscape are regulated by the D/K ratio. Where diffusive erosion is the major erosion process (large D/K ratio), mesic plants have higher abundance relative to xeric and hydric plants and the landscape has longer and convex-upward hillslope and low channel density. Increasing the dominance of advective erosion increases relative abundance of xeric and hydric plants dominance, and the landscape has short and concave hillslope and high channel density.

[Estimation model for daily transpiration of greenhouse muskmelon in its vegetative growth period].

PubMed

Zhang, Da-Long; Li, Jian-Ming; Wu, Pu-Te; Li, Wei-Li; Zhao, Zhi-Hua; Xu, Fei; Li, Jun

2013-07-01

For developing an estimation method of muskmelon transpiration in greenhouse, an estimation model for the daily transpiration of greenhouse muskmelon in its vegetative growth period was established, based on the greenhouse environmental parameters, muskmelon growth and development parameters, and soil moisture parameters. According to the specific environment in greenhouse, the item of aerodynamics in Penman-Monteith equation was modified, and the greenhouse environmental sub-model suitable for calculating the reference crop evapotranspiration in greenhouse was deduced. The crop factor sub-model was established with the leaf area index as independent variable, and the form of the model was linear function. The soil moisture sub-model was established with the soil relative effective moisture content as independent variable, and the form of the model was logarithmic function. With interval sowing, the model parameters were estimated and analyzed, according to the measurement data of different sowing dates in a year. The prediction accuracy of the model for sufficient irrigation and water-saving irrigation was verified, according to measurement data when the relative soil moisture content was 80%, 70%, and 60%, and the mean relative error was 11.5%, 16.2% , and 16.9% respectively. The model was a beneficial exploration for the application of Penman-Monteith equation under greenhouse environment and water-saving irrigation, having good application foreground and popularization value.

Developing Soil Moisture Profiles Utilizing Remotely Sensed MW and TIR Based SM Estimates Through Principle of Maximum Entropy

NASA Astrophysics Data System (ADS)

Mishra, V.; Cruise, J. F.; Mecikalski, J. R.

2015-12-01

Developing accurate vertical soil moisture profiles with minimum input requirements is important to agricultural as well as land surface modeling. Earlier studies show that the principle of maximum entropy (POME) can be utilized to develop vertical soil moisture profiles with accuracy (MAE of about 1% for a monotonically dry profile; nearly 2% for monotonically wet profiles and 3.8% for mixed profiles) with minimum constraints (surface, mean and bottom soil moisture contents). In this study, the constraints for the vertical soil moisture profiles were obtained from remotely sensed data. Low resolution (25 km) MW soil moisture estimates (AMSR-E) were downscaled to 4 km using a soil evaporation efficiency index based disaggregation approach. The downscaled MW soil moisture estimates served as a surface boundary condition, while 4 km resolution TIR based Atmospheric Land Exchange Inverse (ALEXI) estimates provided the required mean root-zone soil moisture content. Bottom soil moisture content is assumed to be a soil dependent constant. Mulit-year (2002-2011) gridded profiles were developed for the southeastern United States using the POME method. The soil moisture profiles were compared to those generated in land surface models (Land Information System (LIS) and an agricultural model DSSAT) along with available NRCS SCAN sites in the study region. The end product, spatial soil moisture profiles, can be assimilated into agricultural and hydrologic models in lieu of precipitation for data scarce regions.Developing accurate vertical soil moisture profiles with minimum input requirements is important to agricultural as well as land surface modeling. Previous studies have shown that the principle of maximum entropy (POME) can be utilized with minimal constraints to develop vertical soil moisture profiles with accuracy (MAE = 1% for monotonically dry profiles; MAE = 2% for monotonically wet profiles and MAE = 3.8% for mixed profiles) when compared to laboratory and field data. In this study, vertical soil moisture profiles were developed using the POME model to evaluate an irrigation schedule over a maze field in north central Alabama (USA). The model was validated using both field data and a physically based mathematical model. The results demonstrate that a simple two-constraint entropy model under the assumption of a uniform initial soil moisture distribution can simulate most soil moisture profiles within the field area for 6 different soil types. The results of the irrigation simulation demonstrated that the POME model produced a very efficient irrigation strategy with loss of about 1.9% of the total applied irrigation water. However, areas of fine-textured soil (i.e. silty clay) resulted in plant stress of nearly 30% of the available moisture content due to insufficient water supply on the last day of the drying phase of the irrigation cycle. Overall, the POME approach showed promise as a general strategy to guide irrigation in humid environments, with minimum input requirements.

Current and future droughts in the Southeastern Mediterranean

NASA Astrophysics Data System (ADS)

Törnros, Tobias; Menzel, Lucas

2016-04-01

The southeastern Mediterranean region (i.e., Israel, Palestine, Jordan and neighboring countries) increasingly suffers significant water stress. The semi-arid to arid conditions with low precipitation amounts, high temperatures and strong interannual climate variability recurrently trigger drought conditions. However, the complex political situation, showing a low degree of mutual cooperation, favors an unsustainable use of water resources and no long-term, cross-boundary water management plan exists. In order to address the drought conditions under current and future climates in this region, the Standardized Precipitation-Evaporation Index (SPEI) was applied. In the first step, the SPEI was derived from spatially interpolated monthly precipitation and temperature data at multiple timescales: accumulated precipitation and monthly mean temperature were considered over a different number of consecutive months. To investigate the performance of the drought index, correlation analyses were conducted with simulated soil moisture and the Normalized Difference Vegetation Index (NDVI) obtained from remote sensing. A comparison with the Standardized Precipitation Index (SPI), i.e., a drought index that does not incorporate temperature, was also conducted. The results show that the choice of the SPEI/SPI timescale is crucial. In our study, the 6-month SPEI has the highest correlation with simulated soil moisture and best explains the interannual variation of the monthly NDVI. Although not extensively addressed, the SPI performs almost just as well and could be applied if temperature data are not available. In the second step, the 6-month SPEI was derived from three climate projections based on the IPCC emission scenario A1B. When comparing the period 2031-2060 with 1961-1990, it is shown that the percentage of time with moderate, severe and extreme drought conditions is projected to strongly increase for all scenarios. Since agriculture is by far the most water demanding sector in the region, the impact of drought on agriculture was addressed. For this, the irrigation water demand during certain drought years was simulated with a hydrological model on a spatial resolution of 1 km. A large increase in the demand for irrigation water was simulated, showing that the agricultural sector is expected to become even more vulnerable to drought in the future.

Soil salinity mapping and hydrological drought indices assessment in arid environments based on remote sensing techniques

NASA Astrophysics Data System (ADS)

Elhag, Mohamed; Bahrawi, Jarbou A.

2017-03-01

Vegetation indices are mostly described as crop water derivatives. The normalized difference vegetation index (NDVI) is one of the oldest remote sensing applications that is widely used to evaluate crop vigor directly and crop water relationships indirectly. Recently, several NDVI derivatives were exclusively used to assess crop water relationships. Four hydrological drought indices are examined in the current research study. The water supply vegetation index (WSVI), the soil-adjusted vegetation index (SAVI), the moisture stress index (MSI) and the normalized difference infrared index (NDII) are implemented in the current study as an indirect tool to map the effect of different soil salinity levels on crop water stress in arid environments. In arid environments, such as Saudi Arabia, water resources are under pressure, especially groundwater levels. Groundwater wells are rapidly depleted due to the heavy abstraction of the reserved water. Heavy abstractions of groundwater, which exceed crop water requirements in most of the cases, are powered by high evaporation rates in the designated study area because of the long days of extremely hot summer. Landsat 8 OLI data were extensively used in the current research to obtain several vegetation indices in response to soil salinity in Wadi ad-Dawasir. Principal component analyses (PCA) and artificial neural network (ANN) analyses are complementary tools used to understand the regression pattern of the hydrological drought indices in the designated study area.

Soil Texture Often Exerts a Stronger Influence Than Precipitation on Mesoscale Soil Moisture Patterns

NASA Astrophysics Data System (ADS)

Dong, Jingnuo; Ochsner, Tyson E.

2018-03-01

Soil moisture patterns are commonly thought to be dominated by land surface characteristics, such as soil texture, at small scales and by atmospheric processes, such as precipitation, at larger scales. However, a growing body of evidence challenges this conceptual model. We investigated the structural similarity and spatial correlations between mesoscale (˜1-100 km) soil moisture patterns and land surface and atmospheric factors along a 150 km transect using 4 km multisensor precipitation data and a cosmic-ray neutron rover, with a 400 m diameter footprint. The rover was used to measure soil moisture along the transect 18 times over 13 months. Spatial structures of soil moisture, soil texture (sand content), and antecedent precipitation index (API) were characterized using autocorrelation functions and fitted with exponential models. Relative importance of land surface characteristics and atmospheric processes were compared using correlation coefficients (r) between soil moisture and sand content or API. The correlation lengths of soil moisture, sand content, and API ranged from 12-32 km, 13-20 km, and 14-45 km, respectively. Soil moisture was more strongly correlated with sand content (r = -0.536 to -0.704) than with API for all but one date. Thus, land surface characteristics exhibit coherent spatial patterns at scales up to 20 km, and those patterns often exert a stronger influence than do precipitation patterns on mesoscale spatial patterns of soil moisture.

EFFECT OF HYDROPHILIC AND HYDROPHOBIC POLYMER ON IN VITRO DISSOLUTION AND PERMEATION OF BISOPROLOL FUMARATE THROUGH TRANSDERMAL PATCH.

PubMed

Shabbir, Maryam; Ali, Sajid; Raza, Moosa; Sharif, Ali; Akhtar, Furoan Muhammad; Manan, Abdul; Fazli, Ali Raza; Younas, Neelofar; Manzoor, Iqra

2017-01-01

A matrix transdermal patch of bisoprolol fumarate was formulated with different concentrations of Eudragit RS 100 and Methocel E5 with PEG 400 as plasticizer by solvent evaporation technique. Tween 80 was added to the optimized patch to evaluate the effect of permeation enhancer at different concentration through the excised rabbit's skin. The patches were analyzed for weight variation, drug content, swelling index, erosion studies, moisture content, moisture uptake, water vapor transmission rate (WVTR) and water vapor permeability (WVP). In vitro dissolution test was carried out in USP dissolution apparatus V to select the optimized formulation. In vitr skin permeation studies were done in Franz diffusion cell using rabbit skin as a model membrane. The cumulative drug release and flux were determined to compare the result of test patches with a control patch. The greatest enhancement ratio (ER) was obtained in F03-PE with 30% Tween 80. F03-PE seemed to follow zero order kinetics with super case II mechanism of drug release. Statistical ANOVA suggested that there was a significant difference in formulations, steady flux and cumulative permeation rate at different Tween 80 concentrations.

Large-scale vegetation responses to terrestrial moisture storage changes

NASA Astrophysics Data System (ADS)

Andrew, Robert L.; Guan, Huade; Batelaan, Okke

2017-09-01

The normalised difference vegetation index (NDVI) is a useful tool for studying vegetation activity and ecosystem performance at a large spatial scale. In this study we use the Gravity Recovery and Climate Experiment (GRACE) total water storage (TWS) estimates to examine temporal variability of the NDVI across Australia. We aim to demonstrate a new method that reveals the moisture dependence of vegetation cover at different temporal resolutions. Time series of monthly GRACE TWS anomalies are decomposed into different temporal frequencies using a discrete wavelet transform and analysed against time series of the NDVI anomalies in a stepwise regression. The results show that combinations of different frequencies of decomposed GRACE TWS data explain NDVI temporal variations better than raw GRACE TWS alone. Generally, the NDVI appears to be more sensitive to interannual changes in water storage than shorter changes, though grassland-dominated areas are sensitive to higher-frequencies of water-storage changes. Different types of vegetation, defined by areas of land use type, show distinct differences in how they respond to the changes in water storage, which is generally consistent with our physical understanding. This unique method provides useful insight into how the NDVI is affected by changes in water storage at different temporal scales across land use types.

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.

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.

Vegetation regulation on streamflow intra-annual variability through adaption to climate variations

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

Ye, Sheng; Li, Hongyi; Li, Shuai

2015-12-16

This study aims to provide a mechanistic explanation of the empirical patterns of streamflow intra-annual variability revealed by watershed-scale hydrological data across the contiguous United States. A mathematical extension of the Budyko formula with explicit account for the soil moisture storage change is used to show that, in catchments with a strong seasonal coupling between precipitation and potential evaporation, climate aridity has a dominant control on intra-annual streamflow variability, but in other catchments, additional factors related to soil water storage change also have important controls on how precipitation seasonality propagates to streamflow. More importantly, use of leaf area index asmore » a direct and indirect indicator of the above ground biomass and plant root system, respectively, reveals the vital role of vegetation in regulating soil moisture storage and hence streamflow intra-annual variability under different climate conditions.« less

Assimilating Remote Sensing Observations of Leaf Area Index and Soil Moisture for Wheat Yield Estimates: An Observing System Simulation Experiment

NASA Technical Reports Server (NTRS)

Nearing, Grey S.; Crow, Wade T.; Thorp, Kelly R.; Moran, Mary S.; Reichle, Rolf H.; Gupta, Hoshin V.

2012-01-01

Observing system simulation experiments were used to investigate ensemble Bayesian state updating data assimilation of observations of leaf area index (LAI) and soil moisture (theta) for the purpose of improving single-season wheat yield estimates with the Decision Support System for Agrotechnology Transfer (DSSAT) CropSim-Ceres model. Assimilation was conducted in an energy-limited environment and a water-limited environment. Modeling uncertainty was prescribed to weather inputs, soil parameters and initial conditions, and cultivar parameters and through perturbations to model state transition equations. The ensemble Kalman filter and the sequential importance resampling filter were tested for the ability to attenuate effects of these types of uncertainty on yield estimates. LAI and theta observations were synthesized according to characteristics of existing remote sensing data, and effects of observation error were tested. Results indicate that the potential for assimilation to improve end-of-season yield estimates is low. Limitations are due to a lack of root zone soil moisture information, error in LAI observations, and a lack of correlation between leaf and grain growth.

Complex responses of spring vegetation growth to climate in a moisture-limited alpine meadow

PubMed Central

Ganjurjav, Hasbagan; Gao, Qingzhu; Schwartz, Mark W.; Zhu, Wenquan; Liang, Yan; Li, Yue; Wan, Yunfan; Cao, Xujuan; Williamson, Matthew A.; Jiangcun, Wangzha; Guo, Hongbao; Lin, Erda

2016-01-01

Since 2000, the phenology has advanced in some years and at some locations on the Qinghai-Tibetan Plateau, whereas it has been delayed in others. To understand the variations in spring vegetation growth in response to climate, we conducted both regional and experimental studies on the central Qinghai-Tibetan Plateau. We used the normalized difference vegetation index to identify correlations between climate and phenological greening, and found that greening correlated negatively with winter-spring time precipitation, but not with temperature. We used open top chambers to induce warming in an alpine meadow ecosystem from 2012 to 2014. Our results showed that in the early growing season, plant growth (represented by the net ecosystem CO2 exchange, NEE) was lower in the warmed plots than in the control plots. Late-season plant growth increased with warming relative to that under control conditions. These data suggest that the response of plant growth to warming is complex and non-intuitive in this system. Our results are consistent with the hypothesis that moisture limitation increases in early spring as temperature increases. The effects of moisture limitation on plant growth with increasing temperatures will have important ramifications for grazers in this system. PMID:26983697

Complex responses of spring vegetation growth to climate in a moisture-limited alpine meadow

NASA Astrophysics Data System (ADS)

Ganjurjav, Hasbagan; Gao, Qingzhu; Schwartz, Mark W.; Zhu, Wenquan; Liang, Yan; Li, Yue; Wan, Yunfan; Cao, Xujuan; Williamson, Matthew A.; Jiangcun, Wangzha; Guo, Hongbao; Lin, Erda

2016-03-01

Since 2000, the phenology has advanced in some years and at some locations on the Qinghai-Tibetan Plateau, whereas it has been delayed in others. To understand the variations in spring vegetation growth in response to climate, we conducted both regional and experimental studies on the central Qinghai-Tibetan Plateau. We used the normalized difference vegetation index to identify correlations between climate and phenological greening, and found that greening correlated negatively with winter-spring time precipitation, but not with temperature. We used open top chambers to induce warming in an alpine meadow ecosystem from 2012 to 2014. Our results showed that in the early growing season, plant growth (represented by the net ecosystem CO2 exchange, NEE) was lower in the warmed plots than in the control plots. Late-season plant growth increased with warming relative to that under control conditions. These data suggest that the response of plant growth to warming is complex and non-intuitive in this system. Our results are consistent with the hypothesis that moisture limitation increases in early spring as temperature increases. The effects of moisture limitation on plant growth with increasing temperatures will have important ramifications for grazers in this system.

Complex responses of spring vegetation growth to climate in a moisture-limited alpine meadow.

PubMed

Ganjurjav, Hasbagan; Gao, Qingzhu; Schwartz, Mark W; Zhu, Wenquan; Liang, Yan; Li, Yue; Wan, Yunfan; Cao, Xujuan; Williamson, Matthew A; Jiangcun, Wangzha; Guo, Hongbao; Lin, Erda

2016-03-17

Since 2000, the phenology has advanced in some years and at some locations on the Qinghai-Tibetan Plateau, whereas it has been delayed in others. To understand the variations in spring vegetation growth in response to climate, we conducted both regional and experimental studies on the central Qinghai-Tibetan Plateau. We used the normalized difference vegetation index to identify correlations between climate and phenological greening, and found that greening correlated negatively with winter-spring time precipitation, but not with temperature. We used open top chambers to induce warming in an alpine meadow ecosystem from 2012 to 2014. Our results showed that in the early growing season, plant growth (represented by the net ecosystem CO2 exchange, NEE) was lower in the warmed plots than in the control plots. Late-season plant growth increased with warming relative to that under control conditions. These data suggest that the response of plant growth to warming is complex and non-intuitive in this system. Our results are consistent with the hypothesis that moisture limitation increases in early spring as temperature increases. The effects of moisture limitation on plant growth with increasing temperatures will have important ramifications for grazers in this system.

An 1800-yr record of decadal-scale hydroclimatic variability in the upper Arkansas River basin from bristlecone pine

USGS Publications Warehouse

Woodhouse, C.A.; Pederson, G.T.; Gray, S.T.

2011-01-01

Bristlecone pine trees are exceptionally long-lived, and with the incorporation of remnant material have been used to construct multi-millennial length ring-width chronologies. These chronologies can provide valuable information about past temperature and moisture variability. In this study, we outline a method to build a moisture-sensitive bristlecone chronology and assess the robustness and consistency of this sensitivity over the past 1200. yr using new reconstructions of Arkansas River flow (AD 1275-2002 and 1577-2002) and the summer Palmer Drought Sensitivity Index. The chronology, a composite built from parts of three collections in the central Rocky Mountains, is a proxy for decadal-scale moisture variability for the past 18 centuries. Since the sample size is small in some portions of the time series, the chronology should be considered preliminary; the timing and duration of drought events are likely the most robust characteristics. This chronology suggests that the region experienced increased aridity during the medieval period, as did much of western North America, but that the timing and duration of drought episodes within this period were somewhat different from those in other western locations, such as the upper Colorado River basin. ?? 2010 University of Washington.

Analysis of Terrestrial Conditions and Dynamics

NASA Technical Reports Server (NTRS)

Goward, S. N.

1985-01-01

An ecological model is developed to estimate annual net primary productivity of vegetation in twelve major North American biomes. Three models are adapted and combined, each addressing a different factor known to govern primary productivity, i.e., photosynthesis, respiration, and moisture availability. Measures of intercepted photosynthetically active radiation (1PAR) for input to the photosynthesis model are derived from spectral vegetation index data. Normalized Difference Vegetation Index (NDVI) data are produced from NOAA-7 Advanced Very High Resolution Radiometer (AVHRR) observations for April 1982 through March 1983. NDVI values are sampled from within the biomes at locations for which climatological data are available. Monthly estimates of Net Primary Productivity (NPP) for each sample location are generated and summed over the twelve month period. These monthly estimates are averaged to produce a single annual estimated NPP value for each biomes. Comparison of estimated NPP values with figures reported in the literature produces a correlation coefficient of 85.

Estimation of regional surface resistance to evapotranspiration from NDVI and thermal-IR AVHRR data. [Normalized Difference Vegetation Index

NASA Technical Reports Server (NTRS)

Nemani, Ramakrishna R.; Running, Steven W.

1989-01-01

Infrared surface temperatures from satellite sensors have been used to infer evaporation and soil moisture distribution over large areas. However, surface energy partitioning to latent versus sensible heat changes with surface vegetation cover and water availability. The hypothesis that the relationship between surface temperature and canopy density is sensitivite to seasonal changes in canopy resistance of conifer forests is presently tested. Surface temperature and canopy density were computed for a 20 x 25 km forested region in Montana, from the NOAA/AVHRR for 8 days during the summer of 1985. A forest ecosystem model, FOREST-BGC, simulated canopy resistance for the same period. For all eight days, surface temperatures had high association with canopy density, measured as Normalized Difference Vegetation Index, implying that latent heat exchange is the major cause of spatial variations in surface radiant tmeperatures.

Understanding moisture stress on light-use efficiency based on MODIS and global flux tower data

NASA Astrophysics Data System (ADS)

Zhang, Y.; Song, C.; Sun, G.

2014-12-01

Gross primary productivity (GPP) is a key indicator of terrestrial ecosystem functions and global carbon balance. However, accurately estimating GPP is still one of the major challenges in global change study. Compared with other prognostic models, remote-sensing-based light-use efficiency (LUE) modes are considered to have the most potential to characterize the spatial-temporal dynamics of GPP. However, the environmental regulations on LUE, especially from water stress, have relatively large uncertainties, which reversely constrained the applications of LUE models. Here, we used MODIS and global flux tower data to investigate the moisture stress on LUE for different biomes on daily, 8-day and monthly scales. Three groups of moisture stress indicators were adopted in our study, including atmosphere (i.e. precipitation and daytime vapor pressure deficit (VPD)), soil (i.e. soil water content (SWC) and scaled SWC (SWCs) by field capacity and wilting point) , and plant indicators (i.e. land surface wetness index (LSWI) and the ratio of latent heat to the sum of latent and sensible heat (L/(L+H)). We applied a series of steps to eliminate the effects of high/low temperature and diffuse radiation effects on observed LUE. Our analysis showed that there were great variations in moisture stress effects on LUE between and within biomes. Generally, the moisture stress effects on LUE are ranked as plant indicator (i.e. L/(L+H) & LSWI) > atmosphere indicator (i.e. VPD) > soil indicator (i.e. SWC/SWCs). Precipitation has the poorest relationship with observed LUE and doesn't show any significant lag effects. For deep-root biomes (e.g. forest), LUE shows higher sensitivity in VPD than SWC; but for short-root biomes (e.g. grass), LUE is more sensitive to SWC than VPD. Most indicators (except SWC/SWCs) are more effective in affecting LUE at the daily/8-day scale than at the monthly scale probably because the observed LUE becomes more stable as temporal scale increases. SWC do not show close relationship with LUE, suggesting that the current measured SWC in the top-soil layer may not be sufficient to capture the moisture effects on LUE for biomes with different root distributions. Our study highlights the complexity of moisture stress on observed LUE, and provides useful guidance for developing more reliable LUE models to estimate GPP.

Preparation and characterization of starch-based loose-fill packaging foams

NASA Astrophysics Data System (ADS)

Fang, Qi

Regular and waxy corn starches were blended in various ratios with biodegradable polymers including polylactic acid (PLA), Eastar Bio Copolyester 14766 (EBC) and Mater-Bi ZF03U (MBI) and extruded with a C. W. Brabender laboratory twin screw extruder using a 3-mm die nozzle at 150°C and 150 rev/min. Physical characteristics including radial expansion, unit density and bulk density and water solubility index, water absorption characteristics, mechanical properties including compressibility, Young's modulus, spring index, bulk compressibility and bulk spring index and abrasion resistance were investigated as affected by the ingredient formulations, i.e. type of polymers, type of starches, polymer to starch ratio and starch moisture content. A completely randomized factorial blocking experimental design was used. Fifty-four treatments resulted. Each treatment was replicated three times. SAS statistical software package was used to analyze the data. Foams made of waxy starch had better radial expansion, lower unit density and bulk density than did foams made of regular starch. Regular starch foams had significantly lower water solubility index than did the waxy starch foams. PLA-starch foams had the lowest compressibility and Young's modulus. MBI-starch foams were the most rigid. All foams had excellent spring indices and bulk spring indices which were comparable to the spring index of commercial expanded polystyrene foam. Correlations were established between the foam mechanical properties and the physical characteristics. Foam compressibility and Young's modulus decreased as increases in radial expansion and decreases in unit and bulk densities. Their relationships were modeled with power law equations. No correlation was observed between spring index and bulk spring index and foam physical characteristics. MBI-starch foams had the highest equilibrium moisture content. EBC-starch and PLA-starch foams had similar water absorption characteristics. No significant difference existed in water absorption characteristics between foams made of regular and waxy starches. Empirical models were developed to correlate foam water absorption characteristics with relative humidity and polymer content. The developed models fit the data well with relatively small standard errors and uniformly scattered residual plots. Foams with higher polymer content had better abrasion resistance than did foams with lower polymer content.

Co-composting of livestock manure with rice straw: characterization and establishment of maturity evaluation system.

PubMed

Qian, Xiaoyong; Shen, Genxiang; Wang, Zhenqi; Guo, Chunxia; Liu, Yangqing; Lei, Zhongfang; Zhang, Zhenya

2014-02-01

Composting is considered to be a primary treatment method for livestock manure and rice straw, and high degree of maturity is a prerequisite for safe land application of the composting products. In this study pilot-scale experiments were carried out to characterize the co-composting process of livestock manure with rice straw, as well as to establish a maturity evaluation index system for the composts obtained. Two pilot composting piles with different feedstocks were conducted for 3 months: (1) swine manure and rice straw (SM-RS); and (2) dairy manure and rice straw (DM-RS). During the composting process, parameters including temperature, moisture, pH, total organic carbon (TOC), organic matter (OM), different forms of nitrogen (total, ammonia and nitrate), and humification index (humic acid and fulvic acid) were monitored in addition to germination index (GI), plant growth index (PGI) and Solvita maturity index. OM loss followed the first-order kinetic model in both piles, and a slightly faster OM mineralization was achieved in the SM-RS pile. Also, the SM-RS pile exhibited slightly better performance than the DM-RS according to the evolutions of temperature, OM degradation, GI and PGI. The C/N ratio, GI and PGI could be included in the maturity evaluation index system in which GI>120% and PGI>1.00 signal mature co-composts. Copyright © 2013 Elsevier Ltd. All rights reserved.

[Key physical parameters of hawthorn leaf granules by stepwise regression analysis method].

PubMed

Jiang, Qie-Ying; Zeng, Rong-Gui; Li, Zhe; Luo, Juan; Zhao, Guo-Wei; Lv, Dan; Liao, Zheng-Gen

2017-05-01

The purpose of this study was to investigate the effect of key physical properties of hawthorn leaf granule on its dissolution behavior. Hawthorn leaves extract was utilized as a model drug. The extract was mixed with microcrystalline cellulose or starch with the same ratio by using different methods. Appropriate amount of lubricant and disintegrating agent was added into part of the mixed powder, and then the granules were prepared by using extrusion granulation and high shear granulation. The granules dissolution behavior was evaluated by using equilibrium dissolution quantity and dissolution rate constant of the hypericin as the indicators. Then the effect of physical properties on dissolution behavior was analyzed through the stepwise regression analysis method. The equilibrium dissolution quantity of hypericin and adsorption heat constant in hawthorn leaves were positively correlated with the monolayer adsorption capacity and negatively correlated with the moisture absorption rate constant. The dissolution rate constants were decreased with the increase of Hausner rate, monolayer adsorption capacity and adsorption heat constant, and were increased with the increase of Carr index and specific surface area. Adsorption heat constant, monolayer adsorption capacity, moisture absorption rate constant, Carr index and specific surface area were the key physical properties of hawthorn leaf granule to affect its dissolution behavior. Copyright© by the Chinese Pharmaceutical Association.

Predicting moisture dynamics of fine understory fuels in a moist tropical rainforest system: results of a pilot study undertaken to identify proxy variables useful for rating fire danger.

PubMed

Ray, David; Nepstad, Dan; Brando, Paulo

2010-08-01

*The use of fire as a land management tool in the moist tropics often has the unintended consequence of degrading adjacent forest, particularly during severe droughts. Reliable models of fire danger are needed to help mitigate these impacts. *Here, we studied the moisture dynamics of fine understory fuels in the east-central Brazilian Amazon during the 2003 dry season. Drying stations established under varying amounts of canopy cover (leaf area index (LAI) = 0 - 5.3) were subjected to a range of water inputs (5-15 mm) and models were developed to forecast litter moisture content (LMC). Predictions were then compared with independent field data. *A multiple linear regression relating litter moisture content to forest structure (LAI), ambient vapor pressure deficit (VPD(M)) and an index of elapsed time since a precipitation event (d(-1)) was identified as the best-fit model (adjusted R(2) = 0.89). Relative to the independent observations, model predictions were relatively unbiased when the LMC was

Impact of aerial infrared roof moisture scans on the U.S. Army's ROOFER program

NASA Astrophysics Data System (ADS)

Knehans, Al; Ledford, Jim

1993-04-01

The ROOFER program is being used by the U.S. Army to inspect and evaluate its built-up and single-ply membrane roofs. The results of the inspection effort are used to develop an overall roof condition index. The condition of the roof insulation can greatly alter the final condition index. By using an aerial infrared (IR) roof moisture scan, all the insulated roofs at most Army installations can be effectively surveyed in a very short time. The aerial scans have detected numerous areas of wet roof insulation, which has had a profound impact on the results of the ROOFER program. The scans have also provided management personnel with more accurate analysis as to the actual condition of the installation's insulated roofs.

Early harvest increases post-harvest physiological quality of Araucaria angustifolia (Araucariaceae) seeds.

PubMed

Shibata, Marília; Medeiros Coelho, Cileide Maria

2016-06-01

Araucaria angustifolia is a conifer native to Brazil and is an endangered species. Since this species seeds have a short period of viability, its vulnerability is higher. Thus the aim of this study was to evaluate the physiological quality of A. angustifolia seeds during the development and post-storage periods. For this, cones of A. angustifolia were collected from a natural population in Curitibanos, Santa Catarina, Brazil, in March, April, May and June 2012. The collected seeds were classified into developmental stages of cotyledonary, I, II and III according to the month of collection; a total of 10 cones were collected for each stage. Seeds were stored in a refrigerator for 60 and 120 days, and were submitted to a chamber germination test (25 °C-photoperiod 12 h). Additionally, seeds were tested for moisture content (105 °C for 24 hours), tetrazolium (0.1 % for 1 hour) and vigor (electric conductivity [75 mL distilled water at 25 °C], germination speed index, and shoot and root length). Our results showed that during seed development, moisture content decreased from the cotyledonary stage (66.54 %) to stage III (49.69 %), and vigor increased in the last stage. During storage, moisture content at cotyledonary stage and stage I was stable. On the other hand, stored seeds exhibited a decrease in moisture content after 120 days at stages II and III. Physiological quality at the cotyledonary stage resulted in an increased germination rate of 86 % and 93 % after 60 and 120 days of storage, respectively; unlike stages II and III exhibited a decrease in seed viability and vigor after storage. Electrical conductivity was higher for fresh seeds at the cotyledonary stage, than for those stored for 60 and 120 days. However, in other stages, released leachate content after 120 days of storage, increased with the advance of the collection period. Germination speed index and shoot and root lengths after storage were highest for seeds at the cotyledonary stage and stage I; unlike stages II and III which had short root and shoot lengths during storage. Thus, the maintenance of seed moisture content during storage was variable and dependent on the period of collection. Furthermore, the physiological quality differed among earlier and later stages. Early collection favored seed physiological quality, and may be a strategy for better conservation of A. angustifolia seeds.

Sensitivity of Polygonum aviculare Seeds to Light as Affected by Soil Moisture Conditions

PubMed Central

Batlla, Diego; Nicoletta, Marcelo; Benech-Arnold, Roberto

2007-01-01

Background and Aims It has been hypothesized that soil moisture conditions could affect the dormancy status of buried weed seeds, and, consequently, their sensitivity to light stimuli. In this study, an investigation is made of the effect of different soil moisture conditions during cold-induced dormancy loss on changes in the sensitivity of Polygonum aviculare seeds to light. Methods Seeds buried in pots were stored under different constant and fluctuating soil moisture environments at dormancy-releasing temperatures. Seeds were exhumed at regular intervals during storage and were exposed to different light treatments. Changes in the germination response of seeds to light treatments during storage under the different moisture environments were compared in order to determine the effect of soil moisture on the sensitivity to light of P. aviculare seeds. Key Results Seed acquisition of low-fluence responses during dormancy release was not affected by either soil moisture fluctuations or different constant soil moisture contents. On the contrary, different soil moisture environments affected seed acquisition of very low fluence responses and the capacity of seeds to germinate in the dark. Conclusions The results indicate that under field conditions, the sensitivity to light of buried weed seeds could be affected by the soil moisture environment experienced during the dormancy release season, and this could affect their emergence pattern. PMID:17430979

Proteolysis and sensory properties of dry-cured bacon as affected by the partial substitution of sodium chloride with potassium chloride.

PubMed

Wu, Haizhou; Zhang, Yingyang; Long, Men; Tang, Jing; Yu, Xiang; Wang, Jiamei; Zhang, Jianhao

2014-03-01

Quadriceps femoris muscle samples (48) from 24 pigs were processed into dry-cured bacon. This study investigated the influence of partial substitution of sodium chloride (NaCl) with potassium chloride (KCl) on proteolysis and sensory properties of dry-cured bacon. Three salt treatments were considered, namely, I (100% NaCl), II (60% NaCl, 40% KCl), and III (30% NaCl, 70% KCl). No significant differences were observed among treatments in the proteolysis, which was reflected by SDS-PAGE, proteolysis index, amino acid nitrogen, and peptide nitrogen contents. Furthermore, there were no significant differences in the moisture content between control and treatment II, whereas the moisture content in treatment III was significantly higher (p<0.05) in comparison with control (treatment I). The sensory analysis indicated that it was possible to reduce NaCl by 40% without adverse effects on sensory properties, but 70% replacement of NaCl with KCl resulted in bacon with less hardness and saltiness and higher (p<0.05) juiciness and bitterness. Copyright © 2013 Elsevier Ltd. All rights reserved.

Optical transparency of paper as a function of moisture content with applications to moisture measurement.

PubMed

Forughi, A F; Green, S I; Stoeber, B

2016-02-01

Accurate measurement of the moisture content of paper is essential in papermaking and is also important in some paper-based microfluidic devices. Traditional measurement techniques provide very limited spatiotemporal resolution and working range. This article presents a novel method for moisture content measurement whose operating principle is the strong correlation between the optical transparency of paper and its moisture content. Spectrographic and microscopic measurement techniques were employed to characterize the relation of moisture content and relative transparency of four types of paper: hardwood chemi-thermomechanical pulp paper, Northern bleached softwood kraft paper, unbleached softwood kraft paper, and General Electric(®) Whatman™ grade 1 chromatography paper. It was found that for all paper types, the paper transparency increased monotonically with the moisture content (as the ratio of the mass-of-water to the mass-of-dry-paper increased from 0% to 120%). This significant increase in relative transparency occurred due to the refractive index matching role of water in wet paper. It is further shown that mechanical loading of the paper has little impact on the relative transparency, for loadings that would be typical on a paper machine. The results of two transient water absorption experiments are presented that show the utility and accuracy of the technique.

Investigating soil moisture feedbacks on precipitation with tests of Granger causality

NASA Astrophysics Data System (ADS)

Salvucci, Guido D.; Saleem, Jennifer A.; Kaufmann, Robert

Granger causality (GC) is used in the econometrics literature to identify the presence of one- and two-way coupling between terms in noisy multivariate dynamical systems. Here we test for the presence of GC to identify a soil moisture ( S) feedback on precipitation ( P) using data from Illinois. In this framework S is said to Granger cause P if F(P t|Ω t- Δt )≠F(P t|Ω t- Δt -S t- Δt ) where F denotes the conditional distribution of P, Ω t- Δt represents the set of all knowledge available at time t-Δ t, and Ω t- Δt -S t- Δt represents all knowledge except S. Critical for land-atmosphere interaction research is that Ω t- Δt includes all past information on P as well as S. Therefore that part of the relation between past soil moisture and current precipitation which results from precipitation autocorrelation and soil water balance will be accounted for and not attributed to causality. Tests for GC usually specify all relevant variables in a coupled vector autoregressive (VAR) model and then calculate the significance level of decreased predictability as various coupling coefficients are omitted. But because the data (daily precipitation and soil moisture) are distinctly non-Gaussian, we avoid using a VAR and instead express the daily precipitation events as a Markov model. We then test whether the probability of storm occurrence, conditioned on past information on precipitation, changes with information on soil moisture. Past information on precipitation is expressed both as the occurrence of previous day precipitation (to account for storm-scale persistence) and as a simple soil moisture-like precipitation-wetness index derived solely from precipitation (to account for seasonal-scale persistence). In this way only those fluctuations in moisture not attributable to past fluctuations in precipitation (e.g., those due to temperature) can influence the outcome of the test. The null hypothesis (no moisture influence) is evaluated by comparing observed changes in storm probability to Monte-Carlo simulated differences generated with unconditional occurrence probabilities. The null hypothesis is not rejected ( p>0.5) suggesting that contrary to recently published results, insufficient evidence exists to support an influence of soil moisture on precipitation in Illinois.

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.

Development of an early warning system of crop moisture conditions using passive microwave

NASA Technical Reports Server (NTRS)

Mcfarland, M. J.; Harder, P. H., II (Principal Investigator)

1982-01-01

Emissivities were calculated from the Nimbus 5 electrically scanning microwave radiometer (ESMR) over 25 km grid cells for the southern Great Plains includin the western two-thirds of Kansas and Oklahoma and northwest Texas. These emissivities, normalized for seasonal temperature changes, were in excellent agreement with theory and measurements made from aircraft and truck sensors at the 1.55 cm wavelength of ESMR. These emissivities were related to crop moisture conditions of the winter wheat in the major wheat producing counties of the three states. High correlations were noted between emissitivity and an antecedent precipitation index (API) used to infer soil moisture for periods when the soils were essentially bare. The emissivities from ESMR were related through API and actual crop condition reports to progress of fall planting, adequacy of crop moisture for stand establishment, and periods of excessive moisture that necessitated replanting. Periods of prolonged frozen soil in the winter were observable at several grid points. The average emissivities of the canopy/soil surface during the maximum canopy development times in the spring showed a good agreement with moisture stress inferred from rainfall and yield data.

Predicting US Drought Monitor (USDM) states using precipitation, soil moisture, and evapotranspiration anomalies, Part I: Development of a non-discrete USDM index

USDA-ARS?s Scientific Manuscript database

The U.S. Drought Monitor (USDM) classifies drought into five discrete dryness/drought categories based on expert synthesis of numerous data sources. In this study, an empirical methodology is presented for creating a non-discrete U.S. Drought Monitor (USDM) index that simultaneously 1) represents th...

Use of Radar Vegetation Index (RVI) in Passive Microwave Algorithms for Soil Moisture Estimates

NASA Astrophysics Data System (ADS)

Rowlandson, T. L.; Berg, A. A.

2013-12-01

The Soil Moisture Active Passive (SMAP) satellite will provide a unique opportunity for the estimation of soil moisture by having simultaneous radar and radiometer measurements available. As with the Soil Moisture and Ocean Salinity (SMOS) satellite, the soil moisture algorithms will need to account for the contribution of vegetation to the brightness temperature. Global maps of vegetation volumetric water content (VWC) are difficult to obtain, and the SMOS mission has opted to estimate the optical depth of standing vegetation by using a relationship between the VWC and the leaf area index (LAI). LAI is estimated from optical remote sensing or through soil-vegetation-atmosphere transfer modeling. During the growing season, the VWC of agricultural crops can increase rapidly, and if cloud cover exists during an optical acquisition, the estimation of LAI may be delayed, resulting in an underestimation of the VWC and overestimation of the soil moisture. Alternatively, the radar vegetation index (RVI) has shown strong correlation and linear relationship with VWC for rice and soybeans. Using the SMAP radar to produce RVI values that are coincident to brightness temperature measurements may eliminate the need for LAI estimates. The SMAP Validation Experiment 2012 (SMAPVEX12) was a cal/val campaign for the SMAP mission held in Manitoba, Canada, during a 6-week period in June and July, 2012. During this campaign, soil moisture measurements were obtained for 55 fields with varying soil texture and vegetation cover. Vegetation was sampled from each field weekly to determine the VWC. Soil moisture measurements were taken coincident to overpasses by an aircraft carrying the Passive and Active L-band System (PALS) instrumentation. The aircraft flew flight lines at both high and low altitudes. The low altitude flight lines provided a footprint size approximately equivalent to the size of the SMAPVEX12 field sites. Of the 55 field sites, the low altitude flight lines provided measurements for 15 fields. One field was planted in corn; three were pasture; six were soybeans; three were wheat; and two were winter wheat. The average RVI for each field was determined for each PALS overpass, with sampled radar data confined to the field dimensions. A linear interpolation was conducted between measured values of VWC to estimate a daily VWC value. A linear regression was conducted between the average VWC and the RVI, for each vegetation type. A positive linear relationship was found for all crops, with the exception of pasture. The correlation between the RVI and VWC was strong for corn and pasture, but moderate for soybeans and winter wheat; however, the correlation for corn was not significant. The developed models were utilized to provide a calculated VWC which was inputted into a modified version of the Land Parameter Retrieval Model (LPRM) to determine the error associated with using a calculated VWC from the RVI versus measured VWC data. The LPRM outputs for both scenarios were compared to the PALS radiometer measurements of brightness temperature.

Spatial and radiometric characterization of multi-spectrum satellite images through multi-fractal analysis

NASA Astrophysics Data System (ADS)

Alonso, Carmelo; Tarquis, Ana M.; Zúñiga, Ignacio; Benito, Rosa M.

2017-03-01

Several studies have shown that vegetation indexes can be used to estimate root zone soil moisture. Earth surface images, obtained by high-resolution satellites, presently give a lot of information on these indexes, based on the data of several wavelengths. Because of the potential capacity for systematic observations at various scales, remote sensing technology extends the possible data archives from the present time to several decades back. Because of this advantage, enormous efforts have been made by researchers and application specialists to delineate vegetation indexes from local scale to global scale by applying remote sensing imagery. In this work, four band images have been considered, which are involved in these vegetation indexes, and were taken by satellites Ikonos-2 and Landsat-7 of the same geographic location, to study the effect of both spatial (pixel size) and radiometric (number of bits coding the image) resolution on these wavelength bands as well as two vegetation indexes: the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI). In order to do so, a multi-fractal analysis of these multi-spectral images was applied in each of these bands and the two indexes derived. The results showed that spatial resolution has a similar scaling effect in the four bands, but radiometric resolution has a larger influence in blue and green bands than in red and near-infrared bands. The NDVI showed a higher sensitivity to the radiometric resolution than EVI. Both were equally affected by the spatial resolution. From both factors, the spatial resolution has a major impact in the multi-fractal spectrum for all the bands and the vegetation indexes. This information should be taken in to account when vegetation indexes based on different satellite sensors are obtained.

Dual Assimilation of Microwave and Thermal-Infrared Satellite Observations of Soil Moisture into NLDAS for Improved Drought Monitoring

NASA Astrophysics Data System (ADS)

Hain, C.; Crow, W. T.; Anderson, M. C.; Zhan, X.; Wardlow, B.; Svoboda, M. D.; Mecikalski, J. R.

2011-12-01

Our research group is currently developing an operational data assimilation (DA) system for the optimal assimilation of thermal infrared (TIR) and microwave (MV) soil moisture (SM) and insertion of near real-time green vegetation fraction (GVF) into the Noah land-surface model component of the National Land Data Assimilation System (NLDAS). NLDAS produces the hydrologic products (e.g. soil moisture, evapotranspiration, and runoff) used by NCEP for operational drought monitoring, but these products are sensitive to model input errors in soil texture (affecting infiltration rates) and prescribed precipitation rates. Periodic updates of SM state variables in LSMs achieved by assimilating diagnostic moisture information retrieved using satellite remote sensing have been shown to compensate for model errors and result in improved hydrologic output. The work proposed here will build on a project currently funded under the Climate Test Bed Program entitled "A GOES Thermal-Based Drought Early Warning Index for NIDIS", which is developing an operational TIR SM index (Evaporative Stress Index; ESI) based on maps of the ratio of actual to potential ET (fPET) generated with the Atmosphere-Land Exchange Inverse (ALEXI) surface energy balance algorithm. The research team has demonstrated that diagnostic information about SM and evapotranspiration (ET) from MW and TIR remote sensing can significantly reduce SM drifts in LSMs such as Noah. The two different SM retrievals have been shown to be quite complementary: TIR provides relatively high spatial (down to 100 m) and low temporal resolution (due to cloud cover) retrievals over a wide range of GVF, while MW provides relatively low spatial (25 to 60 km) and high temporal resolution (can retrieve through cloud cover), but only over areas with low GVF. Furthermore, MW retrievals are sensitive to SM only in the first few centimeters of the soil profile, while TIR provides information about SM conditions integrated over the full root-zone, reflected in the observed canopy temperature. The added value of TIR over MW alone is most significant in areas of moderate to dense vegetation cover where MW retrievals have very little sensitivity to SM at any depth. Finally, climatological estimates of GVF currently used in the operational NLDAS are not always representative of observed seasonal and intra-seasonal GVF conditions, especially in regions experiencing drought conditions. A detailed methodology of the assimilation system will be presented along with an analysis of initial results, with an emphasis on comparisons with in-situ SM observations and standard drought metrics.

Linking the soil moisture distribution pattern to dynamic processes along slope transects in the Loess Plateau, China.

PubMed

Wang, Shuai; Fu, Bojie; Gao, Guangyao; Zhou, Ji; Jiao, Lei; Liu, Jianbo

2015-12-01

Soil moisture pulses are a prerequisite for other land surface pulses at various spatiotemporal scales in arid and semi-arid areas. The temporal dynamics and profile variability of soil moisture in relation to land cover combinations were studied along five slopes transect on the Loess Plateau during the rainy season of 2011. Within the 3 months of the growing season coupled with the rainy season, all of the soil moisture was replenished in the area, proving that a type stability exists between different land cover soil moisture levels. Land cover combinations disturbed the trend determined by topography and increased soil moisture variability in space and time. The stability of soil moisture resulting from the dynamic processes could produce stable patterns on the slopes. The relationships between the mean soil moisture and vertical standard deviation (SD) and coefficient of variation (CV) were more complex, largely due to the fact that different land cover types had distinctive vertical patterns of soil moisture. The spatial SD of each layer had a positive correlation and the spatial CV exhibited a negative correlation with the increase in mean soil moisture. The soil moisture stability implies that sampling comparisons in this area can be conducted at different times to accurately compare different land use types.

Quantifying the Causes and Propogation of the 2015 Washington Wildfires

NASA Astrophysics Data System (ADS)

Engel, R.; Marlier, M. E.; Lettenmaier, D. P.

2017-12-01

In the summer of 2015, Washington state experienced wildfires that burned over 450,000 ha, more than five times the average and more than three times the next-most severe fire season in the 30-year record. We examine the confluence of factors that led to the extreme fire season, and evaluate whether 2015 can be used as a predictor of possible future conditions that will be affected by climate warming. In previous work, we have found that 2015 was an extremely warm summer (nearly 1 degree C warmer than the previous year in the 30-year record) but was not particularly anomalous in terms of many other climatic indicators, including reconstructed soil moisture, the Palmer Drought Severity Index (PDSI), and the Canadian Fire Weather Index. However, according to the Dead Fuel Moisture (DFM), a drying index used by the US Forest Service, 2015 was an extreme year of record. The DFM relies on temperature, precipitation, and relative humidity to establish a daily equilibrium moisture content of dead material. We examine both Washington's 2015 fire season and the 30-year fire record with respect to climatology and other potential drivers of fire (e.g. forest health, ignition). Additionally, we explore the role of land cover with respect to fire propagation through the season. While too many potential causes of extreme fires exist to establish a concrete long-term relationship at such a fine scale, we find that the 2015 fire anomaly was at least partially climatically driven.

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.

Evaluating soil moisture and yield of winter wheat in the Great Plains using Landsat data

NASA Technical Reports Server (NTRS)

Heilman, J. L.; Kanemasu, E. T.; Bagley, J. O.; Rasmussen, V. P.

1977-01-01

Locating areas where soil moisture is limiting to crop growth is important for estimating winter-wheat yields on a regional basis. In the 1975-76 growing season, we evaluated soil-moisture conditions and winter-wheat yields for a five-state region of the Great Plains using Landsat estimates of leaf area index (LAI) and an evapotranspiration (ET) model described by Kanemasu et al (1977). Because LAI was used as an input, the ET model responded to changes in crop growth. Estimated soil-water depletions were high for the Nebraska Panhandle, southwestern Kansas, southeastern Colorado, and the Texas Panhandle. Estimated yields in five-state region ranged from 1.0 to 2.9 metric ton/ha.

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.

Influence of wood-derived biochar on the compactibility and strength of silt loam soil

NASA Astrophysics Data System (ADS)

Ahmed, Ahmed; Gariepy, Yvan; Raghavan, Vijaya

2017-04-01

Biochar is proven to enhance soil fertility and increase crop productivity. Given that the influence of biochar on soil compaction remains unclear, selected physico-mechanical properties of soil amended with wood-derived biochar were assessed. For unamended silt loam, the bulk density, maximum bulk density, optimum moisture content, plastic limit, liquid limit, and plasticity index were 1.05 Mg m-3, 1.69 Mg m-3, 16.55, 17.1, 29.3, and 12.2%, respectively. The penetration resistance and shear strength of the unamended silt loam compacted in the standard compaction Proctor mold and at its optimum moisture content were 1800 kPa and 850 kPa, respectively. Results from amending the silt loam with 10% particle size ranges (0.5-212 μm) led to relative decreases of 18.1, 17.75, 66.66, and 97.4% in bulk density, maximum bulk density, penetration resistance, and shear strength, respectively; a 26.8% relative increase in optimum moisture content; along with absolute increases in plastic limit, liquid limit, and plasticity index of 5.3, 13.7, and 8.4%, respectively. While the biochar-amended silt loam soil was more susceptible to compaction, however, soil mechanical impedance enhanced.

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.

A new multi-sensor integrated index for drought monitoring

NASA Astrophysics Data System (ADS)

Jiao, W.; Wang, L.; Tian, C.

2017-12-01

Drought is perceived as one of the most expensive and least understood natural disasters. The remote-sensing-based integrated drought indices, which integrate multiple variables, could reflect the drought conditions more comprehensively than single drought indices. However, most of current remote-sensing-based integrated drought indices focus on agricultural drought (i.e., deficit in soil moisture), their application in monitoring meteorological drought (i.e., deficit in precipitation) was limited. More importantly, most of the remote-sensing-based integrated drought indices did not take into consideration of the spatially non-stationary nature of the related variables, so such indices may lose essential local details when integrating multiple variables. In this regard, we proposed a new mathematical framework for generating integrated drought index for meteorological drought monitoring. The geographically weighted regression (GWR) model and principal component analysis were used to composite Moderate-resolution Imaging Spectroradiometer (MODIS) based temperature condition index (TCI), the Vegetation Index based on the Universal Pattern Decomposition method (VIUPD) based vegetation condition index (VCI), tropical rainfall measuring mission (TRMM) based Precipitation Condition Index (PCI) and Advanced Microwave Scanning Radiometer-EOS (AMSR-E) based soil moisture condition index (SMCI). We called the new remote-sensing-based integrated drought index geographical-location-based integrated drought index (GLIDI). We examined the utility of the GLIDI for drought monitoring in various climate divisions across the continental United States (CONUS). GLIDI showed high correlations with in-situ drought indices and outperformed most other existing drought indices. The results also indicate that the performance of GLIDI is not affected by environmental factors such as land cover, precipitation, temperature and soil conditions. As such, the GLIDI has considerable potential for drought monitoring across various environmental conditions.

Influence of Leaf Area Index Prescriptions on Simulations of Heat, Moisture, and Carbon Fluxes

NASA Technical Reports Server (NTRS)

Kala, Jatin; Decker, Mark; Exbrayat, Jean-Francois; Pitman, Andy J.; Carouge, Claire; Evans, Jason P.; Abramowitz, Gab; Mocko, David

2013-01-01

Leaf-area index (LAI), the total one-sided surface area of leaf per ground surface area, is a key component of land surface models. We investigate the influence of differing, plausible LAI prescriptions on heat, moisture, and carbon fluxes simulated by the Community Atmosphere Biosphere Land Exchange (CABLEv1.4b) model over the Australian continent. A 15-member ensemble monthly LAI data-set is generated using the MODIS LAI product and gridded observations of temperature and precipitation. Offline simulations lasting 29 years (1980-2008) are carried out at 25 km resolution with the composite monthly means from the MODIS LAI product (control simulation) and compared with simulations using each of the 15-member ensemble monthly-varying LAI data-sets generated. The imposed changes in LAI did not strongly influence the sensible and latent fluxes but the carbon fluxes were more strongly affected. Croplands showed the largest sensitivity in gross primary production with differences ranging from -90 to 60 %. PFTs with high absolute LAI and low inter-annual variability, such as evergreen broadleaf trees, showed the least response to the different LAI prescriptions, whilst those with lower absolute LAI and higher inter-annual variability, such as croplands, were more sensitive. We show that reliance on a single LAI prescription may not accurately reflect the uncertainty in the simulation of the terrestrial carbon fluxes, especially for PFTs with high inter-annual variability. Our study highlights that the accurate representation of LAI in land surface models is key to the simulation of the terrestrial carbon cycle. Hence this will become critical in quantifying the uncertainty in future changes in primary production.

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.

Effects of fibre type and structure of longissimus lumborum (Ll), biceps femoris (Bf) and semimembranosus (Sm) deer muscles salting with different Nacl addition on proteolysis index and texture of dry-cured meats.

PubMed

Żochowska-Kujawska, J

2016-11-01

The aim of the present study was to describe the effect of fibre type and structure as well as NaCl level on the proteolysis index and texture parameters observed in dry-cured meats produced from individual deer muscles. The biceps femoris, semimembranosus and longissimus lumborum muscles were cut from deer main elements, shaped into blocks by trimming off the edges, cured by adding 4, 6 and 8% of salt (w/w) and dried in a ripening chamber for 29days. The results indicated that deer dry-cured muscles with higher percentage of red fibres (type I) showed higher texture parameters, proteolysis index as well as lower moisture losses than muscles with higher amount of white fibres (type IIB). Dry-cured deer muscles with lower NaCl content showed higher values of proteolysis index and lower hardness, cohesiveness, springiness, and chewiness, as well as lower changes in structure elements. Copyright © 2016. Published by Elsevier Ltd.

Assessing mechanical deconstruction of softwood cell wall for cellulosic biofuels production

NASA Astrophysics Data System (ADS)

Jiang, Jinxue

Mechanical deconstruction offers a promising strategy to overcome biomass recalcitrance for facilitating enzymatic hydrolysis of pretreated substrates with zero chemicals input and presence of inhibitors. The goal of this dissertation research is to gain a more fundamental understanding on the impact of mechanical pretreatment on generating digestible micronized-wood and how the physicochemical characteristics influence the subsequent enzymatic hydrolysis of micronized wood. The initial moisture content of feedstock was found to be the key factor affecting the development of physical features and enzymatic hydrolysis of micronized wood. Lower moisture content resulted in much rounder particles with lower crystallinity, while higher moisture content resulted in the milled particles with larger aspect ratio and crystallinity. The enzymatic hydrolysis of micronized wood was improved as collectively increasing surface area (i.e., reducing particle size and aspect ratio) and decreasing crystallinity during mechanical milling pretreatment. Energy efficiency analysis demonstrated that low-moisture content feedstock with multi-step milling process would contribute to cost-effectiveness of mechanical pretreatment for achieving more than 70% of total sugars conversion. In the early stage of mechanical pretreatment, the types of cell fractures were distinguished by the initial moisture contents of wood, leading to interwall fracture at the middle lamella region for low moisture content samples and intrawall fracture at the inner cell wall for high moisture content samples. The changes in cell wall fractures also resulted in difference in the distribution of surface chemical composition and energy required for milling process. In an effort to exploit the underlying mechanism associated with the reduced recalcitrance in micronized wood, we reported the increased enzymatic sugar yield and correspondingly structural and accessible properties of micronized feedstock. Electronic microscopy analysis detailed the structural alternation of cell wall during mechanical process, including cell fracture and delamination, ultrastructure disintegration, and cell wall fragments amorphization, as coincident with the particle size reduction. It was confirmed with Simons' staining that longer milling time resulted in increased substrate accessibility and porosity. The changes in cellulose molecular structure with respect to degree of polymerization (DP) and crystallinity index (CrI) also benefited to decreasing recalcitrance and facilitating enzymatic hydrolysis of micronized wood.

Assessment of soil biological quality index (QBS-ar) in different crop rotation systems in paddy soils

NASA Astrophysics Data System (ADS)

Nadimi-Goki, Mandana; Bini, Claudio; haefele, Stephan

2013-04-01

New methods, based on soil microarthropods for soil quality evaluation have been proposed by some Authors. Soil microarthropods demonstrated to respond sensitively to land management practices and to be correlated with beneficial soil functions. QBS Index (QBS-ar) is calculated on the basis of microarthropod groups present in a soil sample. Each biological form found in the sample receives a score from 1 to 20 (eco-morphological index, EMI), according to its adaptation to soil environment. The objective of this study was to evaluate the effect of various rotation systems and sampling periods on soil biological quality index, in paddy soils. For the purpose of this study surface soil samples (0-15 cm depth) were collected from different rotation systems (rice-rice-rice, soya-rice-rice, fallow-rice and pea-soya-rice) with three replications, and four sampling times in April (after field preparation), June (after seedling), August (after tillering stage) and October (after rice harvesting). The study area is located in paddy soils of Verona area, Northern Italy. Soil microarthropods from a total of 48 samples were extracted and classified according to the Biological Quality of Soil Index (QBS-ar) method. In addition soil moisture, Cumulative Soil Respiration and pH were measured in each site. More diversity of microarthropod groups was found in June and August sampling times. T-test results between different rotations did not show significant differences while the mean difference between rotation and different sampling times is statistically different. The highest QBS-ar value was found in the fallow-rice rotation in the forth soil sampling time. Similar value was found in soya-rice-rice rotation. Result of linear regression analysis indicated that there is significant correlation between QBS-ar values and Cumulative Soil Respiration. Keywords: soil biological quality index (QBS-ar), Crop Rotation System, paddy soils, Italy

Transpiration-driven aridification of the American West in 21st-Century model projections

NASA Astrophysics Data System (ADS)

Mankin, J. S.; Smerdon, J. E.; Cook, B.; Williams, P.; Seager, R.

2016-12-01

Climate models project significant 21st-Century declines in soil moisture and runoff over the American West from anthropogenic climate change, but the associated physical mechanisms are poorly characterized. In particular, there are significant uncertainties regarding the modulation of evaporative losses by vegetation and how the physical determinants (i.e., changes in moisture supply and demand) of future surface moisture balance will vary in time, space, and depth in the soil. Using 35-members of the NCAR CESM large ensemble (LENS) and 1800 years of its pre-industrial control simulation, we examine the response of Western surface moisture balance (soil moisture and runoff) to anthropogenic forcing. Declines in runoff and soil moisture are forced primarily by robust increases in evapotranspiration (from increased plant transpiration and canopy evaporation from leaf area index increases), rather than more uncertain changes in total precipitation. This increased water loss occurs even with significant and widespread increases in plant water-use efficiency. Additionally, snowpack reductions in the Rockies and the Pacific Northwest contribute to reductions in summer-season deep soil moisture, while increased transpiration dries out near surface soil moisture even in regions where total precipitation increases. When coupled with a warming- and CO2-induced shift in phenology and increase in net primary production, these vegetation changes reduce peak summer soil moisture and runoff considerably. Our results thus point to a large role for simulated vegetation responses in determining future Western aridity, highlighting the importance of reducing the substantial extant uncertainties in vegetation processes simulated within climate models.

Canadian Experiment for Soil Moisture in 2010 (CanEX-SM10): Overview and Preliminary Results

NASA Technical Reports Server (NTRS)

Magagi, Ramata; Berg, Aaron; Goita, Kalifa; Belair, Stephane; Jackson, Tom; Toth, B.; Walker, A.; McNairn, H.; O'Neill, P.; Moghdam. M;

MODIS-based spatiotemporal patterns of soil moisture and evapotranspiration interactions in Tampa Bay urban watershed

NASA Astrophysics Data System (ADS)

Chang, Ni-Bin; Xuan, Zhemin; Wimberly, Brent

2011-09-01

Soil moisture and evapotranspiration (ET) is affected by both water and energy balances in the soilvegetation- atmosphere system, it involves many complex processes in the nexus of water and thermal cycles at the surface of the Earth. These impacts may affect the recharge of the upper Floridian aquifer. The advent of urban hydrology and remote sensing technologies opens new and innovative means to undertake eventbased assessment of ecohydrological effects in urban regions. For assessing these landfalls, the multispectral Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing images can be used for the estimation of such soil moisture change in connection with two other MODIS products - Enhanced Vegetation Index (EVI), Land Surface Temperature (LST). Supervised classification for soil moisture retrieval was performed for Tampa Bay area on the 2 kmx2km grid with MODIS images. Machine learning with genetic programming model for soil moisture estimation shows advances in image processing, feature extraction, and change detection of soil moisture. ET data that were derived by Geostationary Operational Environmental Satellite (GOES) data and hydrologic models can be retrieved from the USGS web site directly. Overall, the derived soil moisture in comparison with ET time series changes on a seasonal basis shows that spatial and temporal variations of soil moisture and ET that are confined within a defined region for each type of surfaces, showing clustered patterns and featuring space scatter plot in association with the land use and cover map. These concomitant soil moisture patterns and ET fluctuations vary among patches, plant species, and, especially, location on the urban gradient. Time series plots of LST in association with ET, soil moisture and EVI reveals unique ecohydrological trends. Such ecohydrological assessment can be applied for supporting the urban landscape management in hurricane-stricken regions.

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

In humid areas it is generally considered that soil moisture scales spatially according to the wetness index of the landscape. This scaling arises from lateral flow downslope of ground water within the soil zone. However, in semi-arid and drier regions, this lateral flow is small and fluxes are dominated by vertical flows driven by infiltration and evapotranspiration. Thus, in the absence of runon processes, soil moisture at a location is more driven by local factors such as soil and vegetation properties at that location rather than upstream processes draining to that point. The 'apparent' spatial randomness of soil and vegetation properties generally suggests that soil moisture for semi-arid regions is spatially random. In this presentation a new analysis of neutron probe data during summer from the Tarrawarra site near Melbourne, Australia shows persistent spatial organisation of soil moisture over several years. This suggests a link between permanent features of the catchment (e.g. soil properties) and soil moisture distribution, even though the spatial pattern of soil moisture during the 4 summers monitored appears spatially random. This and other data establishes a prima facie case that soil variations drive spatial variation in soil moisture. Accordingly, we used a previously published spatial scaling relationship for soil properties derived using the mARM pedogenesis model to simulate the spatial variation of soil grading. This soil grading distribution was used in the Rosetta pedotransfer model to derive a spatial distribution of soil functional properties (e.g. saturated hydraulic conductivity, porosity). These functional properties were then input into the HYDRUS-1D soil moisture model and soil moisture simulated for 3 years at daily resolution. The HYDRUS model used had previously been calibrated to field observed soil moisture data at our SASMAS field site. The scaling behaviour of soil moisture derived from this modelling will be discussed and compared with observed data from our SASMAS field sites.

Correlations between soil respiration and soil properties in sugarcane areas under green and slash-and-burn management systems

NASA Astrophysics Data System (ADS)

Rodrigo Panosso, Alan; Milori, Débora M. B. P.; Marques Júnior, José; Martin-Neto, Ladislau; La Scala, Newton, Jr.

2010-05-01

Soil management causes changes in soil physical, chemical, and biological properties that consequently affect its CO2 emission. In this work we studied soil respiration (FCO2) in areas with sugarcane production in southern Brazil under two different sugarcane management systems: green (G), consisting of mechanized harvesting that produces a large amount of crop residues left on the soil surface, and slash-and-burn (SB), in which the residues are burned before manual harvest, leaving no residues on the soil surface. The study was conducted after the harvest period in two side-by-side grids installed in adjacent areas, having 20 measurement points each. The objective of this work was to determinate whether soil physical and chemical properties within each plot were useful in order to explain the spatial variability of FCO2, supposedly influence by each management system. Most of the soil physical properties studied showed no significant differences between management systems, but on the other hand most of the chemical properties differed significantly when SB and G areas were compared. Total FCO2 was 31% higher in the SB plot (729 g CO2 m-2) when compared to the G plot (557 g CO2 m-2) throughout the 70-day period after harvest studied. This seems to be related to the sensitivity of FCO2 to precipitation events, as respiration in this plot increased significantly with increases in soil moisture. Despite temporal variability showed to be positively related to soil moisture, inside each management system there was a negative correlation (p<0.01) between the spatial changes of FCO2 and soil moisture (MS), R= -0.56 and -0.59 for G and SB respectively. There was no spatial correlation between FCO2 and soil organic matter in each management system, however, the humification index (Hum) of organic matter was negatively linear correlated with FCO2 in SB (R= -0.53, p<0.05) while positively linear correlated in G area (R=0.42, p<0.10). The multiple regression model analysis applied in each management system indicates that 63% of the FCO2 spatial variability in G managed could be explained by the model: FCO2(G)= 4.11978 -0.07672MS + 0.0045Hum +1.5352K -0.04474FWP, where K and FWP are potassium content and free water porosity in G area, respectively. On the other hand, 75% of FCO2 spatial variability in SB managed plot was accounted by the model: FCO2(SB) = 10.66774 -0.08624MS -0.02904Hum -2.42548K. Therefore, soil moisture, humification index of organic matter and potassium level were the main properties able to explain the spatial variability of FCO2 in both sugarcane management systems. This result indicates that changes in sugarcane management systems could result in changes on the soil chemical properties, mostly, especially humification index of organic matter. It seems that in conversion from slash-and-burn to green harvest system, free water porosity turns to be an important aspect in order to explain part of FCO2 spatial variability in green managed system.

Probabilistic Assessment of Soil Moisture using C-band Quad-polarized Remote Sensing Data from RISAT1

NASA Astrophysics Data System (ADS)

Pal, Manali; Suman, Mayank; Das, Sarit Kumar; Maity, Rajib

2017-04-01

Information on spatio-temporal distribution of surface Soil Moisture Content (SMC) is essential in several hydrological, meteorological and agricultural applications. There has been increasing importance of microwave active remote sensing data for large-scale estimation of surface SMC because of its ability to monitor spatial and temporal variation of surface SMC at regional, continental and global scale at a reasonably fine spatial and temporal resolution. The use of Synthetic Aperture Radar (SAR) is highly potential for catchment-scale applications due to high spatial resolution (˜10-20 m) both for vegetated and bare soil surface as well as because of its all-weather and day and night characteristics. However, one prime disadvantage of SAR is that their signal is subjective to SMC along with Land Use Land Cover (LULC) and surface roughness conditions, making the retrieval of SMC from SAR data an "ill-posed" problem. Moreover, the quantification of uncertainty due to inappropriate surface roughness characterization, soil texture, inversion techniques etc. even in the latest established retrieval methods, is little explored. This paper reports a recently developed method to estimate the surface SMC with probabilistic assessment of uncertainty associated with the estimation (Pal et al., 2016). Quad-polarized SAR data from Radar Imaging Satellite1 (RISAT1), launched in 2012 by Indian Space Research Organization (ISRO) and information on LULC regarding bareland and vegetated land (<30 cm height) are used in estimation using the potential of multivariate probabilistic assessment through copulas. The salient features of the study are: 1) development of a combined index to understand the role of all the quad-polarized backscattering coefficients and soil texture information in SMC estimation; 2) applicability of the model for different incidence angles using normalized incidence angle theory proposed by Zibri et al. (2005); and 3) assessment of uncertainty range of the estimated SMC. Supervised Principal Component Analysis (SPCA) is used for development of combined index and Frank copula is found to be the best-fit copula. The developed model is validated with the field soil moisture values over 334 monitoring points within the study area and used for development of a soil moisture map. While the performance is promising, the model is applicable only for bare and vegetated land. References: Pal, M., Maity, R., Suman, M., Das, S.K., Patel, P., and Srivastava, H.S., (2016). "Satellite-Based Probabilistic Assessment of Soil Moisture Using C-Band Quad-Polarized RISAT1 Data." IEEE Transactions on Geoscience and Remote Sensing, In Press, doi:10.1109/TGRS.2016.2623378. Zribi, M., Baghdadi, N., Holah, N., and Fafin, O., (2005)."New methodology for soil surface moisture estimation and its application to ENVISAT-ASAR multi-incidence data inversion." Remote Sensing of Environment, vol. 96, nos. 3-4, pp. 485-496.

Regional variation in fire weather controls the reported occurrence of Scottish wildfires

PubMed Central

Legg, Colin J.

2016-01-01

Fire is widely used as a traditional habitat management tool in Scotland, but wildfires pose a significant and growing threat. The financial costs of fighting wildfires are significant and severe wildfires can have substantial environmental impacts. Due to the intermittent occurrence of severe fire seasons, Scotland, and the UK as a whole, remain somewhat unprepared. Scotland currently lacks any form of Fire Danger Rating system that could inform managers and the Fire and Rescue Services (FRS) of periods when there is a risk of increased of fire activity. We aimed evaluate the potential to use outputs from the Canadian Fire Weather Index system (FWI system) to forecast periods of increased fire risk and the potential for ignitions to turn into large wildfires. We collated four and a half years of wildfire data from the Scottish FRS and examined patterns in wildfire occurrence within different regions, seasons, between urban and rural locations and according to FWI system outputs. We used a variety of techniques, including Mahalanobis distances, percentile analysis and Thiel-Sen regression, to scope the best performing FWI system codes and indices. Logistic regression showed significant differences in fire activity between regions, seasons and between urban and rural locations. The Fine Fuel Moisture Code and the Initial Spread Index did a tolerable job of modelling the probability of fire occurrence but further research on fuel moisture dynamics may provide substantial improvements. Overall our results suggest it would be prudent to ready resources and avoid managed burning when FFMC > 75 and/or ISI > 2. PMID:27833814

Regional variation in fire weather controls the reported occurrence of Scottish wildfires.

PubMed

Davies, G Matt; Legg, Colin J

2016-01-01

Fire is widely used as a traditional habitat management tool in Scotland, but wildfires pose a significant and growing threat. The financial costs of fighting wildfires are significant and severe wildfires can have substantial environmental impacts. Due to the intermittent occurrence of severe fire seasons, Scotland, and the UK as a whole, remain somewhat unprepared. Scotland currently lacks any form of Fire Danger Rating system that could inform managers and the Fire and Rescue Services (FRS) of periods when there is a risk of increased of fire activity. We aimed evaluate the potential to use outputs from the Canadian Fire Weather Index system (FWI system) to forecast periods of increased fire risk and the potential for ignitions to turn into large wildfires. We collated four and a half years of wildfire data from the Scottish FRS and examined patterns in wildfire occurrence within different regions, seasons, between urban and rural locations and according to FWI system outputs. We used a variety of techniques, including Mahalanobis distances, percentile analysis and Thiel-Sen regression, to scope the best performing FWI system codes and indices. Logistic regression showed significant differences in fire activity between regions, seasons and between urban and rural locations. The Fine Fuel Moisture Code and the Initial Spread Index did a tolerable job of modelling the probability of fire occurrence but further research on fuel moisture dynamics may provide substantial improvements. Overall our results suggest it would be prudent to ready resources and avoid managed burning when FFMC > 75 and/or ISI > 2.

Assimilation of Leaf Area Index and Soil Wetness Index into the ISBA-A-gs land surface model over France

NASA Astrophysics Data System (ADS)

Barbu, A. L.; Calvet, J.-C.; Lafont, S.

2012-04-01

The development of a Land Data Assimilation System (LDAS) dedicated to carbon and water cycles is considered as a key aspect for monitoring activities of terrestrial carbon fluxes. It allows the assimilation of biophysical products in order to reduce the bias between the model simulations and the observations and have a positive impact on carbon and water fluxes. This work shows the benefits of data assimilation of Earth observations for the monitoring of vegetation status and carbon fluxes, in the framework of the GEOLAND2 project, co-funded by the European Commission within the GMES initiative in FP7. In this study, the SURFEX modelling platform developed at Meteo-France is used for describing the continental vegetation state, surface fluxes and soil moisture. It consists of the land surface model ISBA-A-gs that simulates photosynthesis and plant growth. The vegetation biomass and Leaf Area Index (LAI) evolve dynamically in response to weather and climate conditions. The ECOCLIMAP database provides detailed information about the land cover at a resolution of 1 km. Over the France domain, the most present ecosystem types are grasslands (32%), C3 crop lands (24%), deciduous forest (20%), bare soil (11%), and C4 crop lands (8%).The model also includes a representation of the soil moisture stress with two different types of drought responses for herbaceous vegetation and forests. A version of the Extended Kalman Filter (EKF) scheme is developed for the joint assimilation of satellite-derived surface soil moisture from ASCAT-25 km product, namely Soil Wetness Index (SWI-01) developed by TU-Wien, and remote sensing LAI product provided by GEOLAND2. The GEOLAND2 LAI product is derived from CYCLOPES V3.1 and MODIS collection 5 data. It is more consistent with an effective LAI for low LAI and close to the actual LAI for high values. The assimilation experiment was conducted across France at a spatial resolution of 8 km. The study period ranges from July 2007 to December 2010. In the model simulation, the start of the growing season tends to occur later than in the observations. Similarly, the senescence phase is delayed. The assimilation is able to reduce this bias. The lack of detailed knowledge of the farming practices and other shortcomings of the model are compensated by the assimilation of the remotely sensed LAI. The analyzed seasonal LAI cycle across large cropland regions (north-eastern France) is closer to the observations. A coherent impact of LAI and soil moisture updates on the carbon fluxes is noticed. Increased LAI values in the growing season due to data assimilation corrections trigger an increased photosynthetic activity. Similarly, lower LAI values corresponding to the senescence phase cause a decrease in the carbon dioxide uptake when compared to the original model simulations.

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.

Enhancing SMAP Soil Moisture Retrievals via Superresolution Techniques

NASA Astrophysics Data System (ADS)

Beale, K. D.; Ebtehaj, A. M.; Romberg, J. K.; Bras, R. L.

2017-12-01

Soil moisture is a key state variable that modulates land-atmosphere interactions and its high-resolution global scale estimates are essential for improved weather forecasting, drought prediction, crop management, and the safety of troop mobility. Currently, NASA's Soil Moisture Active/Passive (SMAP) satellite provides a global picture of soil moisture variability at a resolution of 36 km, which is prohibitive for some hydrologic applications. The goal of this research is to enhance the resolution of SMAP passive microwave retrievals by a factor of 2 to 4 using modern superresolution techniques that rely on the knowledge of high-resolution land surface models. In this work, we explore several super-resolution techniques including an empirical dictionary method, a learned dictionary method, and a three-layer convolutional neural network. Using a year of global high-resolution land surface model simulations as training set, we found that we are able to produce high-resolution soil moisture maps that outperform the original low-resolution observations both qualitatively and quantitatively. In particular, on a patch-by-patch basis we are able to produce estimates of high-resolution soil moisture maps that improve on the original low-resolution patches by on average 6% in terms of mean-squared error, and 14% in terms of the structural similarity index.

Atmospheric Moisture Variability and Transmission of Hemorrhagic Fever with Renal Syndrome in Changsha City, Mainland China, 1991–2010

PubMed Central

Li, Xiu-Jun; Tong, Shi-Lu; Gao, Li-Dong; Qin, Jian-Xin; Lin, Xiao-Ling; Liu, Hai-Ning; Zhang, Xi-Xing

2013-01-01

Background The transmission of hemorrhagic fever with renal syndrome (HFRS) is influenced by environmental determinants. This study aimed to explore the association between atmospheric moisture variability and the transmission of hemorrhagic fever with renal syndrome (HFRS) for the period of 1991–2010 in Changsha, China. Methods and Findings Wavelet analyses were performed by using monthly reported time series data of HFRS cases to detect and quantify the periodicity of HFRS. A generalized linear model with a Poisson distribution and a log link model were used to quantify the relationship between climate and HFRS cases, highlighting the importance of moisture conditions. There was a continuous annual oscillation mode and multi-annual cycle around 3–4 years from 1994 to 1999. There was a significant association of HFRS incidence with moisture conditions and the Multivariate El Niño–Southern Oscillation Index (MEI). Particularly, atmospheric moisture has a significant effect on the propagation of HFRS; annual incidence of HFRS was positively correlated with annual precipitation and annual mean absolute humidity. Conclusions The final model had good accuracy in forecasting the occurrence of HFRS and moisture condition can be used in disease surveillance and risk management to provide early warning of potential epidemics of this disease. PMID:23755316

Stability of loess

USGS Publications Warehouse

Lutenegger, A.J.; Hallberg, G.R.

1988-01-01

Lutenegger, A.J. and Hallberg, G.R., 1988. Stability of loess. Eng. Geol., 25: 247-261. The natural stability of loess soils can be related to fundamental geotechnical properties such as Atterberg limits, water content and void ratio. Field observations of unstable conditions in loess deposits in the upper midwest, U.S.A. show relationships between instability and the in situ moisture content and the liquidity index of the loess. Unstable loess can attain natural moisture contents equal to, or greater than, its liquid limit. Implications of these observations for applied engineering works are described. ?? 1988.

Remote estimation of surface moisture over a watershed. M.S. Thesis; [Goodwater Creek Watershed, Missouri

NASA Technical Reports Server (NTRS)

Kocin, P. J. (Principal Investigator)

1979-01-01

The author has identified the following significant results. Contoured analyses of moisture availability, moisture flux, sensible heat flux, thermal inertia, and day and nighttime temperatures over a Missouri watershed for a date in June and in September show that forests and creeks exhibit the highest values of moisture availability, whereas farmlands and villages are relatively dry. The distribution of moisture availability over agricultural districts differs significantly between the two cases. This difference is attributed to a change in the surface's vegetative canopy between June and September, with higher moisture availabilities found in the latter case. Horizontal variations of moisture, however, do indicate some relationship between moisture availability and both local rainfall accumulations and the nature of the terrain.

Modulation of SSM/I microwave soil radiances by rainfall

NASA Technical Reports Server (NTRS)

Heymsfield, Gerald M.; Fulton, Richard

1992-01-01

The feasibility of using SSM/I satellite data for estimating the soil moisture content was investigated by correlating the rainfall and soil moisture data with values of the SSM/I microwave brightness temperature obtained for the lower Great Plains in the United States during 1987. It was found that the areas of lowest brightness temperatures coincided with regions of bare soil which had received significant rainfall. The time-history plots of the brightness temperature and the antecedent precipitation index during an extremely large rain event indicated a slow recovery period (about 15 days) back to the dry soil state. However, regions covered with vegetation showed smaller temperature drops and much weaker correlation with rain events, questioning the feasibility of using SSM/I measurements for estimations of soil moisture in regions containing vegetation-covered soil.

TRMM-TMI Satellite Observed Soil Moisture and Vegetation Density (1998-2005) Show Strong Connection with El Nino in Eastern Australia

NASA Technical Reports Server (NTRS)

Liu, Yi; van Dijk, Albert I.J.M.; Owe, Manfred

2007-01-01

Spatiotemporal patterns in soil moisture and vegetation water content across mainland Australia were investigated from 1998 through 2005, using TRMMITMI passive microwave observations. The Empirical Orthogonal Function technique was used to extract dominant spatial and temporal patterns in retrieved estimates of moisture content for the top 1-cm of soil (theta) and vegetation moisture content (via optical depth tau). The dominant temporal theta and tau patterns were strongly correlated to El Nino/Southern Oscillation (ENSO) in spring (3 = 0.90), and to a progressively lesser extent autumn, summer and winter. The Indian Ocean Dipole (IOD) index also explained part of the variation in spring 8 and z. Cluster analysis suggested that the regions most affected by ENS0 are mainly located in eastern Australia. The results suggest that the drought conditions experienced in eastern Australia since 2000 an clearly expressed in these satellite observations have a strong connection with ENSO patterns.

Research on the remote sensing methods of drought monitoring in Chongqing

NASA Astrophysics Data System (ADS)

Yang, Shiqi; Tang, Yunhui; Gao, Yanghua; Xu, Yongjin

2011-12-01

There are regional and periodic droughts in Chongqing, which impacted seriously on agricultural production and people's lives. This study attempted to monitor the drought in Chongqing with complex terrain using MODIS data. First, we analyzed and compared three remote sensing methods for drought monitoring (time series of vegetation index, temperature vegetation dryness index (TVDI), and vegetation supply water index (VSWI)) for the severe drought in 2006. Then we developed a remote sensing based drought monitoring model for Chongqing by combining soil moisture data and meteorological data. The results showed that the three remote sensing based drought monitoring models performed well in detecting the occurrence of drought in Chongqing on a certain extent. However, Time Series of Vegetation Index has stronger sensitivity in time pattern but weaker in spatial pattern; although TVDI and VSWI can reflect inverse the whole process of severe drought in 2006 summer from drought occurred - increased - relieved - increased again - complete remission in spatial domain, but TVDI requires the situation of extreme drought and extreme moist both exist in study area which it is more difficult in Chongqing; VSWI is simple and practicable, which the correlation coefficient between VSWI and soil moisture data reaches significant levels. In summary, VSWI is the best model for summer drought monitoring in Chongqing.

Designing basin-customized combined drought indices via feature extraction

NASA Astrophysics Data System (ADS)

Zaniolo, Marta; Giuliani, Matteo; Castelletti, Andrea

2017-04-01

The socio-economic costs of drought are progressively increasing worldwide due to the undergoing alteration of hydro-meteorological regimes induced by climate change. Although drought management is largely studied in the literature, most of the traditional drought indexes fail in detecting critical events in highly regulated systems, which generally rely on ad-hoc formulations and cannot be generalized to different context. In this study, we contribute a novel framework for the design of a basin-customized drought index. This index represents a surrogate of the state of the basin and is computed by combining the available information about the water available in the system to reproduce a representative target variable for the drought condition of the basin (e.g., water deficit). To select the relevant variables and how to combine them, we use an advanced feature extraction algorithm called Wrapper for Quasi Equally Informative Subset Selection (W-QEISS). The W-QEISS algorithm relies on a multi-objective evolutionary algorithm to find Pareto-efficient subsets of variables by maximizing the wrapper accuracy, minimizing the number of selected variables (cardinality) and optimizing relevance and redundancy of the subset. The accuracy objective is evaluated trough the calibration of a pre-defined model (i.e., an extreme learning machine) of the water deficit for each candidate subset of variables, with the index selected from the resulting solutions identifying a suitable compromise between accuracy, cardinality, relevance, and redundancy. The proposed methodology is tested in the case study of Lake Como in northern Italy, a regulated lake mainly operated for irrigation supply to four downstream agricultural districts. In the absence of an institutional drought monitoring system, we constructed the combined index using all the hydrological variables from the existing monitoring system as well as the most common drought indicators at multiple time aggregations. The soil moisture deficit in the root zone computed by a distributed-parameter water balance model of the agricultural districts is used as target variable. Numerical results show that our framework succeeds in constructing a combined drought index that reproduces the soil moisture deficit. Moreover, this index represents a valuable information for supporting appropriate drought management strategies, including the possibility of directly informing the lake operations about the drought conditions and improve the overall reliability of the irrigation supply system.

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

NASA Technical Reports Server (NTRS)

Srivastava, Prashant K.; Han, Dawei; Rico-Ramirez, Miguel A.; O'Neill, Peggy; Islam, Tanvir; Gupta, Manika

2014-01-01

Soil Moisture and Ocean Salinity (SMOS) is the latest mission which provides flow of coarse resolution soil moisture data for land applications. However, the efficient retrieval of soil moisture for hydrological applications depends on optimally choosing the soil and vegetation parameters. The first stage of this work involves the evaluation of SMOS Level 2 products and then several approaches for soil moisture retrieval from SMOS brightness temperature are performed to estimate Soil Moisture Deficit (SMD). The most widely applied algorithm i.e. Single channel algorithm (SCA), based on tau-omega is used in this study for the soil moisture retrieval. In tau-omega, the soil moisture is retrieved using the Horizontal (H) polarisation following Hallikainen dielectric model, roughness parameters, Fresnel's equation and estimated Vegetation Optical Depth (tau). The roughness parameters are empirically calibrated using the numerical optimization techniques. Further to explore the improvement in retrieval models, modifications have been incorporated in the algorithms with respect to the sources of the parameters, which include effective temperatures derived from the European Center for Medium-Range Weather Forecasts (ECMWF) downscaled using the Weather Research and Forecasting (WRF)-NOAH Land Surface Model and Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) while the s is derived from MODIS Leaf Area Index (LAI). All the evaluations are performed against SMD, which is estimated using the Probability Distributed Model following a careful calibration and validation integrated with sensitivity and uncertainty analysis. The performance obtained after all those changes indicate that SCA-H using WRF-NOAH LSM downscaled ECMWF LST produces an improved performance for SMD estimation at a catchment scale.

The sensitivity of numerically simulated climates to land-surface boundary conditions

NASA Technical Reports Server (NTRS)

Mintz, Y.

1982-01-01

Eleven sensitivity experiments that were made with general circulation models to see how land-surface boundary conditions can influence the rainfall, temperature, and motion fields of the atmosphere are discussed. In one group of experiments, different soil moistures or albedos are prescribed as time-invariant boundary conditions. In a second group, different soil moistures or different albedos are initially prescribed, and the soil moisture (but not the albedo) is allowed to change with time according to the governing equations for soil moisture. In a third group, the results of constant versus time-dependent soil moistures are compared.

Improving Multi-Sensor Drought Monitoring, Prediction and Recovery Assessment Using Gravimetry Information

NASA Astrophysics Data System (ADS)

Aghakouchak, Amir; Tourian, Mohammad J.

2015-04-01

Development of reliable drought monitoring, prediction and recovery assessment tools are fundamental to water resources management. This presentation focuses on how gravimetry information can improve drought assessment. First, we provide an overview of the Global Integrated Drought Monitoring and Prediction System (GIDMaPS) which offers near real-time drought information using remote sensing observations and model simulations. Then, we present a framework for integration of satellite gravimetry information for improving drought prediction and recovery assessment. The input data include satellite-based and model-based precipitation, soil moisture estimates and equivalent water height. Previous studies show that drought assessment based on one single indicator may not be sufficient. For this reason, GIDMaPS provides drought information based on multiple drought indicators including Standardized Precipitation Index (SPI), Standardized Soil Moisture Index (SSI) and the Multivariate Standardized Drought Index (MSDI) which combines SPI and SSI probabilistically. MSDI incorporates the meteorological and agricultural drought conditions and provides composite multi-index drought information for overall characterization of droughts. GIDMaPS includes a seasonal prediction component based on a statistical persistence-based approach. The prediction component of GIDMaPS provides the empirical probability of drought for different severity levels. In this presentation we present a new component in which the drought prediction information based on SPI, SSI and MSDI are conditioned on equivalent water height obtained from the Gravity Recovery and Climate Experiment (GRACE). Using a Bayesian approach, GRACE information is used to evaluate persistence of drought. Finally, the deficit equivalent water height based on GRACE is used for assessing drought recovery. In this presentation, both monitoring and prediction components of GIDMaPS will be discussed, and the results from 2014 California Drought will be presented. Further Reading: Hao Z., AghaKouchak A., Nakhjiri N., Farahmand A., 2014, Global Integrated Drought Monitoring and Prediction System, Scientific Data, 1:140001, 1-10, doi: 10.1038/sdata.2014.1.

Effect of heat–moisture treatment on digestibility of different cultivars of sweet potato (Ipomea batatas (L.) Lam) starch

PubMed Central

Senanayake, Suraji; Gunaratne, Anil; Ranaweera, K K D S; Bamunuarachchi, Arthur

2014-01-01

Different heat–moisture levels were applied to native starches from different cultivars of sweet potatoes available in Sri Lanka (Wariyapola red, Wariyapola white, Pallepola variety, Malaysian variety and CARI 273) to study the digestibility level. Samples were treated with 20, 25, and 30% moisture at 85°C and 120°C for 6 h and in vitro starch digestibility was tested with porcine pancreatin enzyme. A range of 19.3–23.5% digestibility was shown by the native starches with no significant difference (P < 0.05). Significant changes were observed in the digestibility level of the hydrothermally modified starches and the moisture content showed a positive impact on the digestibility. Heat–moisture treatment at 85°C brought an overall increase in digestibility and temperature beyond 85°C had a negative impact. No significant difference (P < 0.05) in the digestibility was observed with 20% and 25% moisture at 85°C and increased level were seen at 85°C and 30% moisture. PMID:25473497

Comparison of Agricultural Drought Indicators over West Africa

NASA Astrophysics Data System (ADS)

Husak, G. J.; Turner, W.; McNally, A.; Shukla, S.; Funk, C. C.

2017-12-01

The Famine Early Warning Systems Network (FEWS NET) monitors critical environmental variables that impact food production in developing countries, including over 30 countries in Africa. Much of this work focuses on the identification of agricultural drought using remotely sensed and modeled estimates of conditions. These variables estimate precipitation, potential evapotranspiration, water availability for crops and soil moisture - among others - at a critical time, or accumulated over intervals within the season. Frequently, these variables are used in a "convergence of evidence" approach to identify the location and severity of agricultural drought over a region. While much work has gone into identifying and calculating these key indicators, little attention has been given to the relationships between these variables. This work explores the relationship between four key agricultural drought indicators over West Africa to determine the extent to which they are providing unique information and also to expose where certain variables may not be adding independent information to the identification of agricultural drought and the potential for food insecurity. These variables investigated in this study are the Standardized Precipitation Index (SPI), the Standardized Precipitation Evapotranspiration Index (SPEI), the Water Requirement Satisfaction Index (WRSI) and modeled soil moisture (SM) from the FEWSNET Land Data Assimilation System (FLDAS). We look at 35 years of data (1982-2016) over West Africa and identify the primary growing season for the region, then compare the four variables above during this prime season. Because the computational costs of calculating these different indicators varies, we seek to identify where products that are less cost/data intensive adequately capture the same information as the more intensive indicators. The outcome highlights where particular products are most useful for the identification of agricultural drought over the region.

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).

Nutrient transformation during aerobic composting of pig manure with biochar prepared at different temperatures.

PubMed

Li, Ronghua; Wang, Quan; Zhang, Zengqiang; Zhang, Guangjie; Li, Zhonghong; Wang, Li; Zheng, Jianzhong

2015-01-01

The effects of the corn stalk charred biomass (CB) prepared at different pyrolysis temperatures as additives on nutrient transformation during aerobic composting of pig manure were investigated. The results showed that the addition of CB carbonized at different temperatures to pig manure compost significantly influenced the compost temperature, moisture, pH, electrical conductivity, organic matter degradation, total nitrogen, [Formula: see text] and NH3 variations during composting. Compared with control and adding CB charred at lower temperature treatments, the addition of CB prepared over 700°C resulted in higher pH (over 9.2) and NH3 emission and lower potherb mustard seed germination index value during the thermophilic phase. Peak temperatures of composts appeared at 7 days for control and 11 days for CB added treatments. During 90 days composting, the organic matter degradation could be increased over 14.8-29.6% after adding of CB in the compost mixture. The introduction of CB in pig manure could prolong the thermophilic phase, inhibit moisture reduce, facilitate the organic matter decomposition, reduce diethylene triamine pentaacetic acid (DTPA) extractable Zn and Cu contents in pig manure composts and increase ryegrass growth. The study indicated that the corn stalk CB prepared around 500°C was a suitable additive in pig manure composting.

The Temporal Dynamics of Spatial Patterns of Observed Soil Moisture Interpreted Using the Hydrus 1-D Model

NASA Astrophysics Data System (ADS)

Chen, M.; Willgoose, G. R.; Saco, P. M.

2009-12-01

This paper investigates the soil moisture dynamics over two subcatchments (Stanley and Krui) in the Goulburn River in NSW during a three year period (2005-2007) using the Hydrus 1-D unsaturated soil water flow model. The model was calibrated to the seven Stanley microcatchment sites (1 sqkm site) using continuous time surface 30cm and full profile soil moisture measurements. Soil type, leaf area index and soil depth were found to be the key parameters changing model fit to the soil moisture time series. They either shifted the time series up or down, changed the steepness of dry-down recessions or determined the lowest point of soil moisture dry-down respectively. Good correlations were obtained between observed and simulated soil water storage (R=0.8-0.9) when calibrated parameters for one site were applied to the other sites. Soil type was also found to be the main determinant (after rainfall) of the mean of modelled soil moisture time series. Simulations of top 30cm were better than those of the whole soil profile. Within the Stanley microcatchment excellent soil moisture matches could be generated simply by adjusting the mean of soil moisture up or down slightly. Only minor modification of soil properties from site to site enable good fits for all of the Stanley sites. We extended the predictions of soil moisture to a larger spatial scale of the Krui catchment (sites up to 30km distant from Stanley) using soil and vegetation parameters from Stanley but the locally recorded rainfall at the soil moisture measurement site. The results were encouraging (R=0.7~0.8). These results show that it is possible to use a calibrated soil moisture model to extrapolate the soil moisture to other sites for a catchment with an area of up to 1000km2. This paper demonstrates the potential usefulness of continuous time, point scale soil moisture (typical of that measured by permanently installed TDR probes) in predicting the soil wetness status over a catchment of significant size.

Climate Prediction Center - Forecasts & Outlook Maps, Graphs and Tables

Science.gov Websites

moisture, and a forecast for daily ultraviolet (UV) radiation index. Many of the outlook maps have an watches and warnings to protect life and property from acute short-term threats due to severe weather

Campomanesia adamantium (Cambess.) O. Berg seed desiccation: influence on vigor and nucleic acids.

PubMed

Dresch, Daiane M; Masetto, Tathiana E; Scalon, Silvana P Q

2015-01-01

The aim of this study was to evaluate the sensitivity of Campomanesia adamantium seeds to desiccation by drying in activated silica gel (fast) and under laboratory conditions (slow). To assess the sensitivity of the seeds to desiccation, we used drying with silica gel and drying under laboratory conditions (25 °C), in order to obtain seeds with moisture content of 45, 35, 30, 25, 20, 15, 10 and 5%. The physiological potential of the seeds after desiccation was evaluated by measuring primary root protrusion, percentage of normal seedlings, germination seed index, seedling length, total seedling dry mass, electrical conductivity and DNA and RNA integrities. The C. adamantium seeds were sensitive to desiccation and to a reduction in moisture content to 21.1% or less by desiccation using silica gel, and to 17.2% or less by desiccation under laboratory conditions; impairment of the physiological potential of the seeds was observed at these low moisture content levels. The integrity of the seed genomic DNA was not affected after drying seeds in the two methods. However, drying in silica gel to 4.5% moisture content and drying under laboratory conditions to 5.4% moisture content resulted in the loss of seed RNA integrity.

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.

Detecting Soil Moisture Related Impacts on Gross Primary Productivity using the MODIS-based Photochemical Reflectance Index

NASA Astrophysics Data System (ADS)

He, M.; Kimball, J. S.; Running, S. W.; Ballantyne, A.; Guan, K.; Huemmrich, K. F.

2016-12-01

Satellite remote sensing provides continuous observations of vegetation properties that can be used to estimate ecosystem gross primary production (GPP). The Photochemical Reflectance Index (PRI) has been shown to be sensitive to photosynthetic light use efficiency (LUE), GPP and canopy water-stress. The NASA EOS MODIS (Moderate Resolution Imaging Spectroradiometer) sensor provides potential PRI estimation globally at daily time step and 1-km spatial resolution for more than 10 years. Here, we use the MODIS based PRI with eddy covariance CO2 flux measurements and meteorological observations from 20 tower sites representing 5 major plant functional types (PFT) within the continental USA (CONUS) to assess GPP sensitivity to seasonal water supply variability. The sPRI (scaled PRI) derived using MODIS band 13 as a reference band (sPRI13) generally shows higher correspondence with tower GPP observations than other potential MODIS reference bands (MODIS band 1, 4, 10 and 12). The sPRI13 was used to represent soil moisture related water supply constraints to LUE within a terrestrial carbon flux model to estimate GPP (GPPPRI). The GPPPRI calculations show generally strong relationships with tower GPP observations (0.457 ≤ R2 ≤ 0.818), except for lower GPPPRI performance over evergreen needleleaf forest (ENF) sites. A regional model sensitivity analysis using the sPRI13 as a proxy for soil moisture related water supply limits indicated that water restrictions limit GPP over more than 21% of the CONUS domain, particularly in northwest and southwest CONUS subregions, and drier climate areas where atmospheric moisture deficits (VPD) alone are insufficient to represent both atmosphere demand and soil water supply controls affecting productivity. Our results indicate strong potential of the MODIS sPRI13 to represent GPP sensitivity to seasonal soil moisture related water supply variability, with enhanced (1-km resolution) delineation of these processes closer to the scale of in situ tower observations, providing an effective tool to characterize sub-grid spatial heterogeneity in soil moisture related water supply controls that inform coarser scale observations and estimates determined from other satellite observations and global carbon, and climate models.

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

PubMed

Naithani, Kusum J; Baldwin, Doug C; Gaines, Katie P; Lin, Henry; Eissenstat, David M

2013-01-01

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

Evaluation of Remote Sensing and Hydrological Model Based Soil Moisture Datasets in Drought Perspective

NASA Astrophysics Data System (ADS)

Hüsami Afşar, M.; Bulut, B.; Yilmaz, M. T.

2017-12-01

Soil moisture is one of the fundamental parameters of the environment that plays a major role in carbon, energy, and water cycles. Spatial distribution and temporal changes of soil moisture is one of the important components in climatic, ecological and natural hazards at global, regional and local levels scales. Therefore retrieval of soil moisture datasets has a great importance in these studies. Given soil moisture can be retrieved through different platforms (i.e., in-situ measurements, numerical modeling, and remote sensing) for the same location and time period, it is often desirable to evaluate these different datasets to assign the most accurate estimates for different purposes. During last decades, efforts have been given to provide evaluations about different soil moisture products based on various statistical analysis of the soil moisture time series (i.e., comparison of correlation, bias, and their error standard deviation). On the other hand, there is still need for the comparisons of the soil moisture products in drought analysis context. In this study, LPRM and NOAH Land Surface Model soil moisture datasets are investigated in drought analysis context using station-based watershed average datasets obtained over four USDA ARS watersheds as ground truth. Here, the drought analysis are performed using the standardized soil moisture datasets (i.e., zero mean and one standard deviation) while the droughts are defined as consecutive negative anomalies less than -1 for longer than 3 months duration. Accordingly, the drought characteristics (duration and severity) and false alarm and hit/miss ratios of LPRM and NOAH datasets are validated using station-based datasets as ground truth. Results showed that although the NOAH soil moisture products have better correlations, LPRM based soil moisture retrievals show better consistency in drought analysis. This project is supported by TUBITAK Project number 114Y676.

The Utility of Using a Near-Infrared (NIR) Camera to Measure Beach Surface Moisture

NASA Astrophysics Data System (ADS)

Nelson, S.; Schmutz, P. P.

2017-12-01

Surface moisture content is an important factor that must be considered when studying aeolian sediment transport in a beach environment. A few different instruments and procedures are available for measuring surface moisture content (i.e. moisture probes, LiDAR, and gravimetric moisture data from surface scrapings); however, these methods can be inaccurate, costly, and inapplicable, particularly in the field. Near-infrared (NIR) spectral band imagery is another technique used to obtain moisture data. NIR imagery has been predominately used through remote sensing and has yet to be used for ground-based measurements. Dry sand reflects infrared radiation given off by the sun and wet sand absorbs IR radiation. All things considered, this study assesses the utility of measuring surface moisture content of beach sand with a modified NIR camera. A traditional point and shoot digital camera was internally modified with the placement of a visible light-blocking filter. Images were taken of three different types of beach sand at controlled moisture content values, with sunlight as the source of infrared radiation. A technique was established through trial and error by comparing resultant histogram values using Adobe Photoshop with the various moisture conditions. The resultant IR absorption histogram values were calibrated to actual gravimetric moisture content from surface scrapings of the samples. Overall, the results illustrate that the NIR spectrum modified camera does not provide the ability to adequately measure beach surface moisture content. However, there were noted differences in IR absorption histogram values among the different sediment types. Sediment with darker quartz mineralogy provided larger variations in histogram values, but the technique is not sensitive enough to accurately represent low moisture percentages, which are of most importance when studying aeolian sediment transport.

Evaluation of HCMM data for assessing soil moisture and water table depth. [South Dakota

NASA Technical Reports Server (NTRS)

Moore, D. G.; Heilman, J. L.; Tunheim, J. A.; Westin, F. C.; Heilman, W. E.; Beutler, G. A.; Ness, S. D. (Principal Investigator)

1981-01-01

Soil moisture in the 0-cm to 4-cm layer could be estimated with 1-mm soil temperatures throughout the growing season of a rainfed barley crop in eastern South Dakota. Empirical equations were developed to reduce the effect of canopy cover when radiometrically estimating the soil temperature. Corrective equations were applied to an aircraft simulation of HCMM data for a diversity of crop types and land cover conditions to estimate the soil moisture. The average difference between observed and measured soil moisture was 1.6% of field capacity. Shallow alluvial aquifers were located with HCMM predawn data. After correcting the data for vegetation differences, equations were developed for predicting water table depths within the aquifer. A finite difference code simulating soil moisture and soil temperature shows that soils with different moisture profiles differed in soil temperatures in a well defined functional manner. A significant surface thermal anomaly was found to be associated with shallow water tables.

Effects of moisture conditions of dental enamel surface on bond strength of brackets bonded with moisture-insensitive primer adhesive system.

PubMed

Endo, Toshiya; Ozoe, Rieko; Sanpei, Sugako; Shinkai, Koichi; Katoh, Yoshiroh; Shimooka, Shohachi

2008-07-01

The purposes of this study were to evaluate the effects of different degrees of water contamination on the shear bond strength of orthodontic brackets bonded to dental enamel with a moisture-insensitive primer (MIP) adhesive system and to compare the modes of bracket/adhesive failure. A total of 68 human premolars were divided into four groups by primers and enamel surface conditions (desiccated, blot dry, and overwet). In group I, the hydrophobic Transbond XT primer adhesive system was used under desiccated conditions for bonding the brackets; in group II, the hydrophilic Transbond MIP adhesive system was used under desiccated conditions; in group III, the hydrophilic Transbond MIP adhesive system was used under blot dry conditions; and in group IV, the hydrophilic Transbond MIP adhesive system was used under overwet conditions. Shear bond strength was measured with a universal testing machine, and the mode of bracket/adhesive failure was determined according to the adhesive remnant index. The mean shear bond strengths were not significantly different among groups I, II, and III, and were higher than the clinically required range of 6 to 8 MPa. The mean shear bond strength achieved in group IV was significantly lower than that achieved in groups I, II, and III, and also lower than the clinically required values. Bond failure occurred at the enamel-adhesive interface more frequently in group IV than in groups I and III. To achieve clinically sufficient bond strengths with the hydrophilic MIP adhesive system, excess water should be blotted from the water-contaminated enamel surface.

Estimation of Soil Moisture Content from the Spectral Reflectance of Bare Soils in the 0.4–2.5 μm Domain

PubMed Central

Fabre, Sophie; Briottet, Xavier; Lesaignoux, Audrey

2015-01-01

This work aims to compare the performance of new methods to estimate the Soil Moisture Content (SMC) of bare soils from their spectral signatures in the reflective domain (0.4–2.5 μm) in comparison with widely used spectral indices like Normalized Soil Moisture Index (NSMI) and Water Index SOIL (WISOIL). Indeed, these reference spectral indices use wavelengths located in the water vapour absorption bands and their performance are thus very sensitive to the quality of the atmospheric compensation. To reduce these limitations, two new spectral indices are proposed which wavelengths are defined using the determination matrix tool by taking into account the atmospheric transmission: Normalized Index of Nswir domain for Smc estimatiOn from Linear correlation (NINSOL) and Normalized Index of Nswir domain for Smc estimatiOn from Non linear correlation (NINSON). These spectral indices are completed by two new methods based on the global shape of the soil spectral signatures. These methods are the Inverse Soil semi-Empirical Reflectance model (ISER), using the inversion of an existing empirical soil model simulating the soil spectral reflectance according to soil moisture content for a given soil class, and the convex envelope model, linking the area between the envelope and the spectral signature to the SMC. All these methods are compared using a reference database built with 32 soil samples and composed of 190 spectral signatures with five or six soil moisture contents. Half of the database is used for the calibration stage and the remaining to evaluate the performance of the SMC estimation methods. The results show that the four new methods lead to similar or better performance than the one obtained by the reference indices. The RMSE is ranging from 3.8% to 6.2% and the coefficient of determination R2 varies between 0.74 and 0.91 with the best performance obtained with the ISER model. In a second step, simulated spectral radiances at the sensor level are used to analyse the sensitivity of these methods to the sensor spectral resolution and the water vapour content knowledge. The spectral signatures of the database are then used to simulate the signal at the top of atmosphere with a radiative transfer model and to compute the integrated incident signal representing the spectral radiance measurements of the HYMAP airborne hyperspectral instrument. The sensor radiances are then corrected from the atmosphere by an atmospheric compensation tool to retrieve the surface reflectances. The SMC estimation methods are then applied on the retrieve spectral reflectances. The adaptation of the spectral index wavelengths to the HyMap sensor spectral bands and the application of the convex envelope and ISER models to boarder spectral bands lead to an error on the SMC estimation. The best performance is then obtained with the ISER model (RMSE of 2.9% and R2 of 0.96) while the four other methods lead to quite similar RMSE (from 6.4% to 7.8%) and R2 (between 0.79 and 0.83) values. In the atmosphere compensation processing, an error on the water vapour content is introduced. The most robust methods to water vapour content variations are WISOIL, NINSON, NINSOL and ISER model. The convex envelope model and NSMI index require an accurate estimation of the water vapour content in the atmosphere. PMID:25648710

SMOS+RAINFALL: Evaluating the ability of different methodologies to improve rainfall estimations using soil moisture data from SMOS

NASA Astrophysics Data System (ADS)

Pellarin, Thierry; Brocca, Luca; Crow, Wade; Kerr, Yann; Massari, Christian; Román-Cascón, Carlos; Fernández, Diego

2017-04-01

Recent studies have demonstrated the usefulness of soil moisture retrieved from satellite for improving rainfall estimations of satellite based precipitation products (SBPP). The real-time version of these products are known to be biased from the real precipitation observed at the ground. Therefore, the information contained in soil moisture can be used to correct the inaccuracy and uncertainty of these products, since the value and behavior of this soil variable preserve the information of a rain event even for several days. In this work, we take advantage of the soil moisture data from the Soil Moisture and Ocean Salinity (SMOS) satellite, which provides information with a quite appropriate temporal and spatial resolution for correcting rainfall events. Specifically, we test and compare the ability of three different methodologies for this aim: 1) SM2RAIN, which directly relate changes in soil moisture to rainfall quantities; 2) The LMAA methodology, which is based on the assimilation of soil moisture in two models of different complexity (see EGU2017-5324 in this same session); 3) The SMART method, based on the assimilation of soil moisture in a simple hydrological model with a different assimilation/modelling technique. The results are tested for 6 years over 10 sites around the world with different features (land surface, rainfall climatology, orography complexity, etc.). These preliminary and promising results are shown here for the first time to the scientific community, as also the observed limitations of the different methodologies. Specific remarks on the technical configurations, filtering/smoothing of SMOS soil moisture or re-scaling techniques are also provided from the results of different sensitivity experiments.

Pupation Behaviors and Emergence Successes of Ectropis grisescens (Lepidoptera: Geometridae) in Response to Different Substrate Types and Moisture Contents.

PubMed

Wang, Huifang; Ma, Tao; Xiao, Qiang; Cao, Panrong; Chen, Xuan; Wen, Yuzhen; Xiong, Hongpeng; Qin, Wenquan; Liang, Shiping; Jian, Shengzhe; Li, Yanjun; Sun, Zhaohui; Wen, Xiujun; Wang, Cai

2017-12-08

Ectropis grisescens Warren (Lepidoptera: Geometridae) is one of the most severe pests of tea plants in China. This species commonly pupates in soil; however, little is known about its pupation ecology. In the present study, choice and no-choice tests were conducted to investigate the pupation behaviors and emergence success of E. grisescens in response to different substrates (sand, sandy loam 1, sandy loam 2, and silt loam) and moisture contents (5, 20, 35, 50, 65, and 80%). Moisture-choice bioassays showed that significantly more E. grisescens individuals pupated in or on soil (sandy loam 1 and 2 and silt loam) that was at the intermediate moisture levels, whereas 5%- and 35%-moisture sand was significantly more preferred over 80%-moisture sand for pupating. Substrate-choice bioassays showed that sand was most preferred by E. grisescens individuals at 20%- and 80%-moisture levels, but no preference was detected among the four substrates at 50%-moisture content. No-choice tests showed that the percentage of burrowed E. grisescens individuals and pupation depth were significantly lower when soil was dry (20% moisture) or wet (80% moisture). In addition, 20%-moisture sandy loam 2 and silt loam significantly decreased the body water content of pupae and emergence success of adults compared to 50%-moisture content. However, each measurement (percentage of burrowed individuals, pupation depth, body water content, or emergence success) was similar when compared among different moisture levels of sand. Interestingly, pupae buried with 80%-moisture soil exhibited significantly lower emergence success than that were unburied. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Characterizing ecosystem response to water supply changes inferred from GRACE drought severity index and surface soil moisture anomalies from ESA CCI and SMAP

NASA Astrophysics Data System (ADS)

Zhao, M.; Velicogna, I.; Kimball, J. S.

2017-12-01

Climate change such as more frequent heatwaves and drought is threatening our food security and ecosystem by reducing water supply to vegetation. Characterizing vegetation response to water supply changes is not only important for evaluating and mitigating climatic change impacts on ecosystem functions and services, but also to determine the feedback mechanisms that ecosystem response may generate on the climate itself. However, such characterization is not well-known at the global scale partly because large scale observations of underground water supply changes are limited. Satellite observations of soil moisture (SM) datasets such as from Soil Moisture Active and Passive (SMAP) and European Space Agency Climate Change Initiative (ESA CCI) do not penetrate more than a few centimeters and do not capture the entire root-zone. Here we employ a newly developed Drought Severity Index from Gravity Recovery and Climate Experiment (GRACE-DSI) to complement SM observations by informing total water supply changes in the entire terrestrial hydrological cycle. We use MODIS vegetation indices as proxies for vegetation growth and investigate their seasonal and interannual variability in relation to GRACE-DSI. We find that total water supply constrains vegetation growth across the entire continental US. Water constraint begins at an earlier date of year and lasts for a longer period in the lower latitude than in the higher latitude. We also find that water constraint occurs at different phenological stages depending on vegetation type. For instance, water constrain forest growth during reproductive period in eastern US but constrain shrub land growth during green-up in Arizona (Fig. 1). In western United States, eastern Australia and the horn of Africa, we find that vegetation growth changes closely follows GRACE-DSI but can have 16-day to one-month delay with respect to SM anomalies from SMAP and ESA CCI. This suggests that in these regions, vegetation is sensitive to water supply changes in the deeper soil layers than in the shallower surface.

Climate Prediction Center - Forecasts & Outlook Maps, Graphs and Tables

Science.gov Websites

moisture, and a forecast for daily ultraviolet (UV) radiation index. Many of the outlook maps have an acute short-term threats due to severe weather events. Another of the many products available is the GFS

Relative performance evaluation of a custom-made near infrared reflectance instrument and two commercial instruments (Foss and ASD) in the nondestructive moisture content measurement of in-shell peanuts

USDA-ARS?s Scientific Manuscript database

A custom made Near Infrared Reflectance (NIR) spectroscope was used to determine the moisture content of in-shell peanuts of Virginia type peanuts. Peanuts were conditioned to different moisture levels between 6 and 26 % (wet basis) and samples from different moisture levels were separated into two...

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.

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.

Utilization of downscaled microwave satellite data and GRACE Total Water Storage anomalies for improving streamflow prediction in the Lower Mekong Basin

NASA Astrophysics Data System (ADS)

Lakshmi, V.; Gupta, M.; Bolten, J. D.

2016-12-01

The Mekong river is the world's eighth largest in discharge with draining an area of 795,000 km² from the Eastern watershed of the Tibetan Plateau to the Mekong Delta including, Myanmar, Laos PDR, Thailand, Cambodia, Vietnam and three provinces of China. The populations in these countries are highly dependent on the Mekong River and they are vulnerable to the availability and quality of the water resources within the Mekong River Basin. Soil moisture is one of the most important hydrological cycle variables and is available from passive microwave satellite sensors (such as AMSR-E, SMOS and SMAP), but their spatial resolution is frequently too coarse for effective use by land managers and decision makers. The merging of satellite observations with numerical models has led to improved land surface predictions. Although performance of the models have been continuously improving, the laboratory methods for determining key hydraulic parameters are time consuming and expensive. The present study assesses a method to determine the effective soil hydraulic parameters using a downscaled microwave remote sensing soil moisture product based on the NASA Advanced Microwave Scanning Radiometer (AMSR-E). The soil moisture downscaling algorithm is based on a regression relationship between 1-km MODIS land surface temperature and 1-km Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) to produce an enhanced spatial resolution ASMR-E-based soil moisture product. Since the optimized parameters are based on the near surface soil moisture information, further constraints are applied during the numerical simulation through the assimilation of GRACE Total Water Storage (TWS) within the land surface model. This work improves the hydrological fluxes and the state variables are optimized and the optimal parameter values are then transferred for retrieving hydrological fluxes. To evaluate the performance of the system in helping improve simulation accuracy and whether they can be used to obtain soil moisture profiles at poorly gauged catchments the root mean square error (RMSE) and Mean Bias error (MBE) are used to measure the performance of the simulations.

Evaluation of AMSR2 soil moisture products over the contiguous United States using in situ data from the International Soil Moisture Network

NASA Astrophysics Data System (ADS)

Wu, Qiusheng; Liu, Hongxing; Wang, Lei; Deng, Chengbin

2016-03-01

High quality soil moisture datasets are required for various environmental applications. The launch of the Advanced Microwave Scanning Radiometer 2 (AMSR2) on board the Global Change Observation Mission 1-Water (GCOM-W1) in May 2012 has provided global near-surface soil moisture data, with an average revisit frequency of two days. Since AMSR2 is a new passive microwave system in operation, it is very important to evaluate the quality of AMSR2 products before widespread utilization of the data for scientific research. In this paper, we provide a comprehensive evaluation of the AMSR2 soil moisture products retrieved by the Japan Aerospace Exploration Agency (JAXA) algorithm. The evaluation was performed for a three-year period (July 2012-June 2015) over the contiguous United States. The AMSR2 soil moisture products were evaluated by comparing ascending and descending overpass products to each other as well as comparing them to in situ soil moisture observations of 598 monitoring stations obtained from the International Soil Moisture Network (ISMN). The accuracy of AMSR2 soil moisture product was evaluated against several types of monitoring networks, and for different land cover types and ecoregions. Three performance metrics, including mean difference (MD), root mean squared difference (RMSD), and correlation coefficient (R), were used in our accuracy assessment. Our evaluation results revealed that AMSR2 soil moisture retrievals are generally lower than in situ measurements. The AMSR2 soil moisture retrievals showed the best agreement with in situ measurements over the Great Plains and the worst agreement over forested areas. This study offers insights into the suitability and reliability of AMSR2 soil moisture products for different ecoregions. Although AMSR2 soil moisture retrievals represent useful and effective measurements for some regions, further studies are required to improve the data accuracy.

Rheological and physical parameters correlations in formulations with pinhão derivatives stability study: building up an analytical route.

PubMed

Moschini Daudt, Renata; Medeiros Cardozo, Nilo Sergio; Damasceno Ferreira Marczak, Ligia; Clemes Külkamp Guerreiro, Irene

2018-07-01

This study focuses on the correlation investigation between rheological and physical parameters and how it can contribute to optimize the topical formulations development. A gel and an emulgel containing pinhão derivatives, and their respective controls, were analyzed along six months of storage. A flowchart of analyses was proposed to use in topical formulation development when a benchmark is the goal or when it is necessary to change some raw material. All formulations were stable over the storage time and the formulations containing pinhão starch and coat extract presented similar properties to those of the control formulations. Correlations between rheological and physical data, as moisture content and particle size, were determined using Pearson's correlation coefficient. A moderate positive correlation was verified between particle size distribution and flow index, and a strong positive correlation between particle size and flow index. It was also found that the higher the moisture content, the higher the consistency index, quality factor, and apparent viscosity. The correlation analyses applied in this study contributed to build up an analytical route for topical formulation development, saving time and costs.

Impact of Drought on Groundwater and Soil Moisture - A Geospatial Tool for Water Resource Management

NASA Astrophysics Data System (ADS)

Ziolkowska, J. R.; Reyes, R.

2016-12-01

For many decades, recurring droughts in different regions in the US have been negatively impacting ecosystems and economic sectors. Oklahoma and Texas have been suffering from exceptional and extreme droughts in 2011-2014, with almost 95% of the state areas being affected (Drought Monitor, 2015). Accordingly, in 2011 alone, around 1.6 billion were lost in the agricultural sector alone as a result of drought in Oklahoma (Stotts 2011), and 7.6 billion in Texas agriculture (Fannin 2012). While surface water is among the instant indicators of drought conditions, it does not translate directly to groundwater resources that are the main source of irrigation water. Both surface water and groundwater are susceptible to drought, while groundwater depletion is a long-term process and might not show immediately. However, understanding groundwater availability is crucial for designing water management strategies and sustainable water use in the agricultural sector and other economic sectors. This paper presents an interactive geospatially weighted evaluation model and a tool at the same time to analyze groundwater resources that can be used for decision support in water management. The tool combines both groundwater and soil moisture changes in Oklahoma and Texas in 2003-2014, thus representing the most important indicators of agricultural and hydrological drought. The model allows for analyzing temporal and geospatial long-term drought at the county level. It can be expanded to other regions in the US and the world. The model has been validated with the Palmer Drought Index Severity Index to account for other indicators of meteorological drought. It can serve as a basis for an upcoming socio-economic and environmental analysis of drought events in the short and long-term in different geographic regions.

Aloe sterol supplementation improves skin elasticity in Japanese men with sunlight-exposed skin: a 12-week double-blind, randomized controlled trial

PubMed Central

Tanaka, Miyuki; Yamamoto, Yuki; Misawa, Eriko; Nabeshima, Kazumi; Saito, Marie; Yamauchi, Koji; Abe, Fumiaki; Furukawa, Fukumi

2016-01-01

Background/objective Recently, it was confirmed that the daily oral intake of plant sterols of Aloe vera gel (Aloe sterol) significantly increases the skin barrier function, moisture, and elasticity in photoprotected skin. This study aimed to investigate whether Aloe sterol intake affected skin conditions following sunlight exposure in Japanese men. Methods We performed a 12-week, randomized, double-blind, placebo-controlled study to evaluate the effects of oral Aloe sterol supplementation on skin conditions in 48 apparently healthy men (age range: 30–59 years; average: 45 years). The subjects were instructed to expose the measurement position of the arms to the sunlight outdoors every day for 12 weeks. The skin parameters were measured at 0 (baseline), 4, 8, and 12 weeks. Results Depending on the time for the revelation of the sunlight, the b* value and melanin index increased and the skin moisture decreased. After taking an Aloe sterol tablet daily for 12 weeks, the skin elasticity index (R2, R5, and R7) levels were significantly higher than the baseline value. There were no differences between the groups in these skin elasticity values. In the subgroup analysis of subjects aged <46 years, the change in the R5 and R7 was significantly higher in the Aloe group than in the placebo group at 8 weeks (P=0.0412 and P=0.0410, respectively). There was a difference in the quantity of sun exposure between each subject, and an additional clinical study that standardizes the amount of ultraviolet rays is warranted. No Aloe sterol intake-dependent harmful phenomenon was observed during the intake period. Conclusion Aloe sterol ingestion increased skin elasticity in the photodamaged skin of men aged <46 years. PMID:27877061

Simulated Surface Energy Budgets Over the Southeastern US: The GHCC Satellite Assimilation System and the NCEP Early Eta

NASA Technical Reports Server (NTRS)

Lapenta, William M.; Suggs, Ron; McNider, Richard T.; Jedlovec, Gary

1999-01-01

A technique has been developed for assimilating GOES-derived skin temperature tendencies and insolation into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature change closely agrees with the satellite observations. A critical assumption of the technique is that the availability of moisture (either from the soil or vegetation) is the least known term in the model's surface energy budget. Therefore, the simulated latent heat flux, which is a function of surface moisture availability, is adjusted based upon differences between the modeled and satellite-observed skin temperature tendencies. An advantage of this technique is that satellite temperature tendencies are assimilated in an energetically consistent manner that avoids energy imbalances and surface stability problems that arise from direct assimilation of surface shelter temperatures. The fact that the rate of change of the satellite skin temperature is used rather than the absolute temperature means that sensor calibration is not as critical. An advantage of this technique for short-range forecasts (0-48h) is that it does not require a complex land-surface formulation within the atmospheric model. As a result, we can avoid having to specify land surface characteristics such as vegetation resistances, green fraction, leaf area index, soil physical and hydraulic characteristics, stream flow, runoff, and the vertical and horizontal distribution of soil moisture.

Gastro-intestinal nematode infection in lambs — A model based on climatic indices for forecasting peak pasture larval contamination

NASA Astrophysics Data System (ADS)

Paton, G.

1987-06-01

The parasite Ostertagia circumcincta is the primary cause of parasitic gastro-enteritis in lambs during their first season at grass. The life-cycle of this nematode parasite involves the development and survival of the free-living stages on pasture. Accordingly the pasture is the site of deposition, development and transmission of infection and meteorological factors affecting the pasture will affect the parasites. In this paper two empirical models for forecasting the timing of the “summer wave” of infective larvae on pasture are presented. These models are similar in form to that described by Starr and Thomas (1980) but involve different approaches to assessing the temperature and moisture components of the daily index value. Further, using the prediction model described by Paton, Thomas and Waller (1984) as an investigative tool, certain tentative suggestions are made as to a general fundamental weakness of empirical index methods.

Soybean canopy reflectance as influenced by cultural practices. [West Lafayette, Indiana

NASA Technical Reports Server (NTRS)

Bauer, M. E. (Principal Investigator); Kollenkark, J. C.; Daughtry, C. S. T.

1981-01-01

Experiments were conducted at West Lafayette, Indiana in 1978 and 1979 to study the reflectance factor of soybean canopies as affected by differences in row width, population, planting date, cultivar and soil type. Reflectance factor data were acquired throughout the growing season with a LANDSAT-band radiometer. Agronomic data included plant height, leaf area index, development stage, total fresh and dry biomass, percent soil cover, and grain yield. The results indicate that row width, planting date, and cultivar influence the percent soil cover, leaf area index, and biomass present, which are in turn related to the multispectral reflectance. Additionally, the reflectance data were quite sensitive to the onset of senescence. Soil color and moisture were found to be important factors influencing the reflectance in single LANDSAT bands, but the near infrared/red reflectance ratio and the greeness transformation were less sensitive than the single bands to the soil background present.

Estimates of leaf area index from spectral reflectance of wheat under different cultural practices and solar angle

NASA Technical Reports Server (NTRS)

Asrar, G.; Kanemasu, E. T.; Yoshida, M.

1985-01-01

The influence of management practices and solar illumination angle on the leaf area index (LAI) was estimated from measurements of wheat canopy reflectance evaluated by two methods, a regression formula and an indirect technique. The date of planting and the time of irrigation in relation to the stage of plant growth were found to have significant effects on the development of leaves in spring wheat. A reduction in soil moisture adversely affected both the duration and magnitude of the maximum LAI for late planting dates. In general, water stress during vegetative stages resulted in a reduction in maximum LAI, while water stress during the reproductive period shortened the duration of green LAI in spring wheat. Canopy geometry and solar angle also affected the spectral properties of the canopies, and hence the estimated LAI. Increase in solar zenith angles resulted in a general increase in estimated LAI obtained from both methods.

Low-Cost Soil Moisture Profile Probe Using Thin-Film Capacitors and a Capacitive Touch Sensor.

PubMed

Kojima, Yuki; Shigeta, Ryo; Miyamoto, Naoya; Shirahama, Yasutomo; Nishioka, Kazuhiro; Mizoguchi, Masaru; Kawahara, Yoshihiro

2016-08-15

Soil moisture is an important property for agriculture, but currently commercialized soil moisture sensors are too expensive for many farmers. The objective of this study is to develop a low-cost soil moisture sensor using capacitors on a film substrate and a capacitive touch integrated circuit. The performance of the sensor was evaluated in two field experiments: a grape field and a mizuna greenhouse field. The developed sensor captured dynamic changes in soil moisture at 10, 20, and 30 cm depth, with a period of 10-14 days required after sensor installation for the contact between capacitors and soil to settle down. The measured soil moisture showed the influence of individual sensor differences, and the influence masked minor differences of less than 0.05 m³·m(-3) in the soil moisture at different locations. However, the developed sensor could detect large differences of more than 0.05 m³·m(-3), as well as the different magnitude of changes, in soil moisture. The price of the developed sensor was reduced to 300 U.S. dollars and can be reduced even more by further improvements suggested in this study and by mass production. Therefore, the developed sensor will be made more affordable to farmers as it requires low financial investment, and it can be utilized for decision-making in irrigation.

Low-Cost Soil Moisture Profile Probe Using Thin-Film Capacitors and a Capacitive Touch Sensor

PubMed Central

Kojima, Yuki; Shigeta, Ryo; Miyamoto, Naoya; Shirahama, Yasutomo; Nishioka, Kazuhiro; Mizoguchi, Masaru; Kawahara, Yoshihiro

2016-01-01

Soil moisture is an important property for agriculture, but currently commercialized soil moisture sensors are too expensive for many farmers. The objective of this study is to develop a low-cost soil moisture sensor using capacitors on a film substrate and a capacitive touch integrated circuit. The performance of the sensor was evaluated in two field experiments: a grape field and a mizuna greenhouse field. The developed sensor captured dynamic changes in soil moisture at 10, 20, and 30 cm depth, with a period of 10–14 days required after sensor installation for the contact between capacitors and soil to settle down. The measured soil moisture showed the influence of individual sensor differences, and the influence masked minor differences of less than 0.05 m3·m−3 in the soil moisture at different locations. However, the developed sensor could detect large differences of more than 0.05 m3·m−3, as well as the different magnitude of changes, in soil moisture. The price of the developed sensor was reduced to 300 U.S. dollars and can be reduced even more by further improvements suggested in this study and by mass production. Therefore, the developed sensor will be made more affordable to farmers as it requires low financial investment, and it can be utilized for decision-making in irrigation. PMID:27537881

Combining SAR with LANDSAT for Change Detection of Riparian Buffer Zone in a Semi-arid River Basin

NASA Astrophysics Data System (ADS)

Chang, N.

2006-12-01

A combination of RADARSAT-1 and Landsat 5 TM satellite images linking the soil moisture variation with Normalized Difference Vegetation Index (NDVI) measurements were used to accomplish remotely sensed change detection of riparian buffer zone in the Choke Canyon Reservoir Watershed (CCRW), South Texas. The CCRW was selected as the study area contributing to the reservoir, which is mostly agricultural and range land in a semi-arid coastal environment. This makes the study significant due to the interception capability of non-point source impact within the riparian buffer zone and the maintenance of ecosystem integrity region wide. First of all, an estimation of soil moisture using RADARSAT-1 Synthetic Aperture Radar (SAR) satellite imagery was conducted. With its all-weather capability, the RADARSAT-1 is a promising tool for measuring the surface soil moisture over seasons. The time constraint is almost negligible since the RADARSAT-1 is able to capture surface soil moisture over a large area in a matter of seconds, if the area is within its swath. RADARSAT-1 images presented at here were captured in two acquisitions, including April and September 2004. With the aid of five corner reflectors deployed by Alaska Satellite Facility (ASF), essential radiometric and geometric calibrations were performed to improve the accuracy of the SAR imagery. The horizontal errors were reduced from initially 560 meter down to less than 5 meter at the best try. Then two Landsat 5 TM satellite images were summarized based on its NDVI. The combination of and NDVI and SAR data obviously show that soil moisture and vegetation biomass wholly varies in space and time in the CCRW leading to identify the riparian buffer zone evolution over seasons. It is found that the seasonal soil moisture variation is highly tied with the NDVI values and the change detection of buffer zone is technically feasible. It will contribute to develop more effective management strategies for non-point source pollution control, bird habitat monitoring, and grazing and live stock handlings in the future. Future research focuses on comparison of soil moisture variability within RADARSAT-1 footprints and NDVI variations against interferometric SAR for studying riparian ecosystem functioning on a seasonal basis.

Identifying multiple timescale rainfall controls on Mojave Desert ecohydrology using an integrated data and modeling approach for Larrea tridentata

USGS Publications Warehouse

Ng, Gene-Hua Crystal; Bedford, David R.; Miller, David M.

2015-01-01

The perennial shrub Larrea tridentata is widely successful in North American warm deserts but is also susceptible to climatic perturbations. Understanding its response to rainfall variability requires consideration of multiple timescales. We examine intra-annual to multi-year relationships using model simulations of soil moisture and vegetation growth over 50 years in the Mojave National Preserve in southeastern California (USA). Ecohydrological model parameters are conditioned on field and remote sensing data using an ensemble Kalman filter. Although no specific periodicities were detected in the rainfall record, simulated leaf-area-index exhibits multi-year dynamics that are driven by multi-year (∼3-years) rains, but with up to a 1-year delay in peak response. Within a multi-year period, Larrea tridentata is more sensitive to winter rains than summer. In the most active part of the root zone (above ∼80 cm), >1-year average soil moisture drives vegetation growth, but monthly average soil moisture is controlled by root uptake. Moisture inputs reach the lower part of the root zone (below ∼80 cm) infrequently, but once there they can persist over a year to help sustain plant growth. Parameter estimates highlight efficient plant physiological properties facilitating persistent growth and high soil hydraulic conductivity allowing deep soil moisture stores. We show that soil moisture as an ecological indicator is complicated by bidirectional interactions with vegetation that depend on timescale and depth. Under changing climate, Larrea tridentata will likely be relatively resilient to shorter-term moisture variability but will exhibit higher sensitivity to shifts in seasonal to multi-year moisture inputs.

Moisture Content Influences Ignitability of Slash Pine Litter

Treesearch

Winfred H. Blackmarr

1972-01-01

The influence of moisture content on the ignitability of slash pine litter was measured by dropping lighted matches onto fuel beds conditioned to different levels of moisture content.The percentage of matches igniting the fuel bed was used to indicate ignition probability at each moisture content. The "critical range" of fuel moisture contents within which...

Forested communities of the pine mountain region, Georgia, USA

Treesearch

Robert Floyd; Robert Carter

2013-01-01

Seven landscape scale communities were identified in the Pine Mountain region having a mixture of Appalachian, Piedmont, and Coastal Plain species. The diagnostic environmental variables included elevation, B-horizon depth, A-horizon silt, topographic relative moisture index, and A-horizon potassium (K).

Development of the Metropolitan Water Availability Index (MWAI) and Short-term Assessment with Multi-scale Remote Sensing Technologies

EPA Science Inventory

Global climate change will change environmental conditions including temperature, precipitation, surface radiation, humidity, soil moisture, and sea level, and impact significantly the regional-scale hydrologic processes such as evapotranspiration (ET), runoff, groundwater levels...

An experimental investigation of the smoldering combustion of cotton with different moisture contents

NASA Astrophysics Data System (ADS)

Li, Wendong; Liu, Wanfu; Ni, Zhaopeng; Wang, Lu; Gao, Bo

2018-03-01

Cotton is an inflammable substance that can be ignited by a weak ignition source. Since, cotton fiber is typically removed from cottonseed, compressed into bales and stored in the warehouse for extended periods of time, the moisture content is a very important characteristic of cotton. In this study, the effect of moisture content on cotton smoldering combustion was studied experimentally by characterizing cotton samples with different moisture contents. The results showed that the higher moisture content of cotton delayed the smoldering combustion process of cotton and prolonged the duration of high temperature of cotton smoldering. And we could find that when the moisture content is higher than 10%, the characteristics of smoldering change obviously.

Analysis of vegetation recovery surrounding a restored wetland using the normalized difference infrared index (NDII) and normalized difference vegetation index (NDVI)

USGS Publications Warehouse

Wilson, Natalie R.; Norman, Laura

2018-01-01

Watershed restoration efforts seek to rejuvenate vegetation, biological diversity, and land productivity at Cienega San Bernardino, an important wetland in southeastern Arizona and northern Sonora, Mexico. Rock detention and earthen berm structures were built on the Cienega San Bernardino over the course of four decades, beginning in 1984 and continuing to the present. Previous research findings show that restoration supports and even increases vegetation health despite ongoing drought conditions in this arid watershed. However, the extent of restoration impacts is still unknown despite qualitative observations of improvement in surrounding vegetation amount and vigor. We analyzed spatial and temporal trends in vegetation greenness and soil moisture by applying the normalized difference vegetation index (NDVI) and normalized difference infrared index (NDII) to one dry summer season Landsat path/row from 1984 to 2016. The study area was divided into zones and spectral data for each zone was analyzed and compared with precipitation record using statistical measures including linear regression, Mann– Kendall test, and linear correlation. NDVI and NDII performed differently due to the presence of continued grazing and the effects of grazing on canopy cover; NDVI was better able to track changes in vegetation in areas without grazing while NDII was better at tracking changes in areas with continued grazing. Restoration impacts display higher greenness and vegetation water content levels, greater increases in greenness and water content through time, and a decoupling of vegetation greenness and water content from spring precipitation when compared to control sites in nearby tributary and upland areas. Our results confirm the potential of erosion control structures to affect areas up to 5 km downstream of restoration sites over time and to affect 1 km upstream of the sites.

Impact of postharvest drying conditions on in vitro starch digestibility and estimated glycemic index of cooked non-waxy long-grain rice (Oryza sativa L.).

PubMed

Donlao, Natthawuddhi; Ogawa, Yukiharu

2017-02-01

Wet paddy needs to be dried to reduce its moisture content after harvesting. In this study, effects of postharvest drying condition on in vitro starch digestibility and estimated glycemic index of cooked rice (Oryza sativa L.) were investigated. Varying drying conditions, i.e. hot-air drying at 40, 65, 90 and 115 °C, and sun drying were applied to raw paddy. After husking and polishing, polished grains were cooked using an electric rice cooker. Cooked samples were analyzed for their moisture content and amount of resistant and total starch. Five samples in both intact grain and slurry were digested under simulated in vitro gastrointestinal digestion process. The in vitro starch digestion rate was measured and the hydrolysis index (HI) and estimated glycemic index (eGI) were calculated. Cooked rice obtained from hot-air drying showed relatively lower HI and eGI than that obtained from sun-drying. Among samples from hot-air drying treatment, eGI of cooked rice decreased with increasing drying temperature, except for the drying temperature of 115 °C. As a result, cooked rice from the hot-air drying at 90 °C showed lowest eGI. The results indicated that cooked rice digestibility was affected by postharvest drying conditions. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Measuring soil moisture near soil surface ... minor differences due to neutron source type

Treesearch

Robert R. Ziemer; Irving Goldberg; Norman A. MacGillivray

1967-01-01

Abstract - Moisture measurements were made in three media--paraffin, water, saturated sand--with four neutron moisture meters, each containing 226-radium-beryllium, 227-actinium-beryllium, 239-plutonium-beryllium, or 241-americium-beryllium neutron sources. Variability in surface detection by the different sources may be due to differences in neutron sources, in...

Improvement of physiological parameters of rats subjected to hypercaloric diet, with the use of Pereskia grandifolia (Cactaceae) leaf flour.

PubMed

de Almeida, Martha Elisa Ferreira; Simão, Anderson Assaid; Corrêa, Angelita Duarte; de Barros Fernandes, Regiane Victória

The aim of the present study was to investigate the anti-obesity effects of Pereskia grandifolia leaf flour on rats fed a hypercaloric diet. After a hypercaloric diet for 10 weeks, 21 animals were divided into the following groups and were fed the following diets for 4 weeks: control (CH), hypercaloric diet with P. grandifolia flour (PGF) 5%, and hypercaloric diet with PGF 10%. Several measurements were performed including body weight, food consumption, body mass index, Lee index, liver weight, liver and body moisture content, and body and hepatic lipid level. Data were analyzed by Tukey's test at 5% probability. Rats fed PGF diet had decreased food consumption and body weight and showed lower body mass and Lee indices compared to control group. At week 2, weight of the PGF 10% group was statistically lower than the control group (CH). At week 4, the PGF 10% group demonstrated the highest body weight loss compared to the other two groups. There were no significant difference in total lipids and moisture level between the groups; however, rats fed PGF diet had lower hepatic lipids levels than control group and reduced liver weight. This suggests that PGF induced weight loss and decreased hepatic lipid level and may be effective in treating obesity and related metabolic diseases. Copyright © 2015 Asia Oceania Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.

An Observing System Simulation Experiment of assimilating leaf area index and soil moisture over cropland

NASA Astrophysics Data System (ADS)

Lafont, Sebastien; Barbu, Alina; Calvet, Jean-Christophe

2013-04-01

A Land Data Assimilation System (LDAS) is an off-line data assimilation system featuring uncoupled land surface model which is driven by observation-based atmospheric forcing. In this study the experiments were conducted with a surface externalized (SURFEX) modelling platform developed at Météo-France. It encompasses the land surface model ISBA-A-gs that simulates photosynthesis and plant growth. The photosynthetic activity depends on the vegetation types. The input soil and vegetation parameters are provided by the ECOCLIMAP II global database which assigns the ecosystem classes in several plant functional types as grassland, crops, deciduous forest and coniferous forest. New versions of the model have been recently developed in order to better describe the agricultural plant functional types. We present a set of observing system simulation experiments (OSSE) which asses leaf area index (LAI) and soil moisture assimilation for improving the land surface estimates in a controlled synthetic environment. Synthetic data were assimilated into ISBA-A-gs using an Extended Kalman Filter (EKF). This allows for an understanding of model responses to an augmentation of the number of crop types and different parameters associated to this modification. In addition, the interactions between uncertainties in the model and in the observations were investigated. This study represents the first step of a process that envisages the extension of LDAS to the new versions of the ISBA-A-gs model in order to assimilate remote sensing observations.

Analysis of the relationship between rusty root incidences and soil properties in Panax ginseng

NASA Astrophysics Data System (ADS)

Wang, Q. X.; Xu, C. L.; Sun, H.; Ma, L.; Li, L.; Zhang, D. D.; Zhang, Y. Y.

2016-08-01

Rusty root is a serious problem in ginseng cultivation that limits the production and quality of ginseng worldwide. The Changbai Mountains are the most famous area for ginseng cultivation in China. To clarify the relationship between rusty root and soil characteristics, physico-chemical properties and enzymatic activities of soil collected from five different fields in the Changbai Mountains were analyzed and a controlled experiment carried out by increasing the concentration of Fe (II). Soil bulk density, moisture, total iron (Fe) and total manganese (Mn) concentrations and polyphenol oxidase (PPO) activity were significantly higher in rusty root than healthy root groups (two-sample test, P<0.05 or P<0.01), respectively. Pearson test showed that there was a significant positive correlation between rusty root index and pH, N, Fe, Mn, Al, Zn and Ca of soil samples collected from fields (P<0.05 or P<0.01), and a significant positive correlation also occurred between rusty root index and Fe (II) added to soil in Fe (II) inducing rusty root (P<0.01). Physiological factors may be very important roles giving rise to ginseng rusty root. Fe (III) reduction and Fe (II) oxidation could be important in increasing the incidence of rusty root. Soil moisture and bulk density of non-rhizosphere soil not attached to the root surface, and pH, N and PPO content of rhizosphere soils attached to the root surface were heavily involved in the reduction, oxidation and sequestration of metal ions.

Interactive Vegetation Phenology, Soil Moisture, and Monthly Temperature Forecasts

NASA Technical Reports Server (NTRS)

Koster, R. D.; Walker, G. K.

2015-01-01

The time scales that characterize the variations of vegetation phenology are generally much longer than those that characterize atmospheric processes. The explicit modeling of phenological processes in an atmospheric forecast system thus has the potential to provide skill to subseasonal or seasonal forecasts. We examine this possibility here using a forecast system fitted with a dynamic vegetation phenology model. We perform three experiments, each consisting of 128 independent warm-season monthly forecasts: 1) an experiment in which both soil moisture states and carbon states (e.g., those determining leaf area index) are initialized realistically, 2) an experiment in which the carbon states are prescribed to climatology throughout the forecasts, and 3) an experiment in which both the carbon and soil moisture states are prescribed to climatology throughout the forecasts. Evaluating the monthly forecasts of air temperature in each ensemble against observations, as well as quantifying the inherent predictability of temperature within each ensemble, shows that dynamic phenology can indeed contribute positively to subseasonal forecasts, though only to a small extent, with an impact dwarfed by that of soil moisture.

Effects of pretreatment with a urea-containing emollient on nickel allergic skin reactions.

PubMed

Kuzmina, Natalia; Nyrén, Miruna; Lodén, Marie; Edlund, Fredrik; Emtestam, Lennart

2005-01-01

The aim of this study was to evaluate the effect of a moisturizer containing urea on allergic contact dermatitis. Twenty-five nickel-sensitized patients and five controls (non-sensitized volunteers) applied such a moisturizer on the volar side of one forearm twice daily for 20 days, while the other forearm served as the control. After treatment with the moisturizer, patch tests with 0%, 0.5% and 2% NiSO4 in petrolatum were applied in a randomized manner on each arm. After 72 h, the skin reactions were blindly evaluated by clinical scoring and by measuring transepidermal water loss and electrical impedance. After treatment, the baseline transepidermal water loss values were lower and the baseline magnitude impedance index values were higher on the pretreated forearm. According to clinical scoring and measurements with the two physical measurement techniques, the degree of the patch test reactions was equal. All control subjects had negative nickel tests. We concluded that the skin reactivity to nickel in nickel-sensitized patients is not significantly affected by use of the urea-containing moisturizer.

Effect of isolation techniques on the characteristics of pigeon pea (Cajanus cajan) protein isolates.

PubMed

Adenekan, Monilola K; Fadimu, Gbemisola J; Odunmbaku, Lukumon A; Oke, Emmanuel K

2018-01-01

In this study, the effect of different isolation techniques on the isolated proteins from pigeon pea was investigated. Water, methanol, ammonium sulfate, and acetone were used for the precipitation of proteins from pigeon pea. Proximate composition, and antinutritional and functional properties of the pigeon pea flour and the isolated proteins were measured. Data generated were statistically analyzed. The proximate composition of the water-extracted protein isolate was moisture 8.30%, protein 91.83%, fat 0.25%, ash 0.05%, and crude fiber 0.05%. The methanol-extracted protein isolate composition was moisture 7.87%, protein 91.83%, fat 0.17%, and ash 0.13%, while crude fiber and carbohydrates were not detected. The composition of the ammonium sulfate-extracted protein isolate was moisture 7.73%, protein 91.73%, fat 0.36, ash 0.13%, and crude fiber 0.67%. The acetone-extracted protein isolate composition was moisture 8.03%, protein 91.50%, ash 0.67%, and fat 0.30%, but crude fiber and carbohydrates were not detected. The isolate precipitated with ammonium sulfate displayed the highest foaming capacity (37.63%) and foaming stability (55.75%). Isolates precipitated with methanol and acetone had the highest water absorption capacity (160%). Pigeon pea protein isolates extracted with methanol and ammonium sulfate had the highest oil absorption capacity of 145%. Protein isolates recovered through acetone and methanol had the highest emulsifying capacity of 2.23% and emulsifying stability of 91.47%, respectively. The proximate composition of the recovered protein isolates were of high purity. This shows the efficiency of the extraction techniques. The isolates had desirable solubility index. All the isolation techniques brought significant impact on the characteristics of the isolated pigeon pea protein.

Simultaneous state-parameter estimation supports the evaluation of data assimilation performance and measurement design for soil-water-atmosphere-plant system

NASA Astrophysics Data System (ADS)

Hu, Shun; Shi, Liangsheng; Zha, Yuanyuan; Williams, Mathew; Lin, Lin

2017-12-01

Improvements to agricultural water and crop managements require detailed information on crop and soil states, and their evolution. Data assimilation provides an attractive way of obtaining these information by integrating measurements with model in a sequential manner. However, data assimilation for soil-water-atmosphere-plant (SWAP) system is still lack of comprehensive exploration due to a large number of variables and parameters in the system. In this study, simultaneous state-parameter estimation using ensemble Kalman filter (EnKF) was employed to evaluate the data assimilation performance and provide advice on measurement design for SWAP system. The results demonstrated that a proper selection of state vector is critical to effective data assimilation. Especially, updating the development stage was able to avoid the negative effect of ;phenological shift;, which was caused by the contrasted phenological stage in different ensemble members. Simultaneous state-parameter estimation (SSPE) assimilation strategy outperformed updating-state-only (USO) assimilation strategy because of its ability to alleviate the inconsistency between model variables and parameters. However, the performance of SSPE assimilation strategy could deteriorate with an increasing number of uncertain parameters as a result of soil stratification and limited knowledge on crop parameters. In addition to the most easily available surface soil moisture (SSM) and leaf area index (LAI) measurements, deep soil moisture, grain yield or other auxiliary data were required to provide sufficient constraints on parameter estimation and to assure the data assimilation performance. This study provides an insight into the response of soil moisture and grain yield to data assimilation in SWAP system and is helpful for soil moisture movement and crop growth modeling and measurement design in practice.

The response of vegetation to rising CO2 concentrations plays an important role in future changes in the hydrological cycle

NASA Astrophysics Data System (ADS)

Hong, Tao; Dong, Wenjie; Ji, Dong; Dai, Tanlong; Yang, Shili; Wei, Ting

2018-04-01

The effects of increasing CO2 concentrations on plant and carbon cycle have been extensively investigated; however, the effects of changes in plants on the hydrological cycle are still not fully understood. Increases in CO2 modify the stomatal conductance and water use of plants, which may have a considerable effect on the hydrological cycle. Using the carbon-climate feedback experiments from CMIP5, we estimated the responses of plants and hydrological cycle to rising CO2 concentrations to double of pre-industrial levels without climate change forcing. The mode results show that rising CO2 concentrations had a significant influence on the hydrological cycle by changing the evaporation and transpiration of plants and soils. The increases in the area covered by plant leaves result in the increases in vegetation evaporation. Besides, the physiological effects of stomatal closure were stronger than the opposite effects of changes in plant structure caused by the increases in LAI (leaf area index), which results in the decrease of transpiration. These two processes lead to overall decreases in evaporation, and then contribute to increases in soil moisture and total runoff. In the dry areas, the stronger increase in LAI caused the stronger increases in vegetation evaporation and then lead to the overall decreases in P - E (precipitation minus evaporation) and soil moisture. However, the soil moisture in sub-arid and wet areas would increase, and this may lead to the soil moisture deficit worse in the future in the dry areas. This study highlights the need to consider the different responses of plants and the hydrological cycle to rising CO2 in dry and wet areas in future water resources management, especially in water-limited areas.

Synergetic Use of Sentinel-1 and Sentinel-2 Data for Soil Moisture Mapping at 100 m Resolution.

PubMed

Gao, Qi; Zribi, Mehrez; Escorihuela, Maria Jose; Baghdadi, Nicolas

2017-08-26

The recent deployment of ESA's Sentinel operational satellites has established a new paradigm for remote sensing applications. In this context, Sentinel-1 radar images have made it possible to retrieve surface soil moisture with a high spatial and temporal resolution. This paper presents two methodologies for the retrieval of soil moisture from remotely-sensed SAR images, with a spatial resolution of 100 m. These algorithms are based on the interpretation of Sentinel-1 data recorded in the VV polarization, which is combined with Sentinel-2 optical data for the analysis of vegetation effects over a site in Urgell (Catalunya, Spain). The first algorithm has already been applied to observations in West Africa by Zribi et al., 2008, using low spatial resolution ERS scatterometer data, and is based on change detection approach. In the present study, this approach is applied to Sentinel-1 data and optimizes the inversion process by taking advantage of the high repeat frequency of the Sentinel observations. The second algorithm relies on a new method, based on the difference between backscattered Sentinel-1 radar signals observed on two consecutive days, expressed as a function of NDVI optical index. Both methods are applied to almost 1.5 years of satellite data (July 2015-November 2016), and are validated using field data acquired at a study site. This leads to an RMS error in volumetric moisture of approximately 0.087 m³/m³ and 0.059 m³/m³ for the first and second methods, respectively. No site calibrations are needed with these techniques, and they can be applied to any vegetation-covered area for which time series of SAR data have been recorded.

Synergetic Use of Sentinel-1 and Sentinel-2 Data for Soil Moisture Mapping at 100 m Resolution

PubMed Central

Gao, Qi; Zribi, Mehrez

2017-01-01

The recent deployment of ESA’s Sentinel operational satellites has established a new paradigm for remote sensing applications. In this context, Sentinel-1 radar images have made it possible to retrieve surface soil moisture with a high spatial and temporal resolution. This paper presents two methodologies for the retrieval of soil moisture from remotely-sensed SAR images, with a spatial resolution of 100 m. These algorithms are based on the interpretation of Sentinel-1 data recorded in the VV polarization, which is combined with Sentinel-2 optical data for the analysis of vegetation effects over a site in Urgell (Catalunya, Spain). The first algorithm has already been applied to observations in West Africa by Zribi et al., 2008, using low spatial resolution ERS scatterometer data, and is based on change detection approach. In the present study, this approach is applied to Sentinel-1 data and optimizes the inversion process by taking advantage of the high repeat frequency of the Sentinel observations. The second algorithm relies on a new method, based on the difference between backscattered Sentinel-1 radar signals observed on two consecutive days, expressed as a function of NDVI optical index. Both methods are applied to almost 1.5 years of satellite data (July 2015–November 2016), and are validated using field data acquired at a study site. This leads to an RMS error in volumetric moisture of approximately 0.087 m3/m3 and 0.059 m3/m3 for the first and second methods, respectively. No site calibrations are needed with these techniques, and they can be applied to any vegetation-covered area for which time series of SAR data have been recorded. PMID:28846601

Transpiration in response to variation in microclimate and soil moisture in southeastern deciduous forests.

PubMed

Oren, Ram; Pataki, Diane E

2001-05-01

Responses of forests to changes in environmental conditions reflect the integrated behavior of their constituent species. We investigated sap flux-scaled transpiration responses of two species prevalent in upland eastern hardwood forests, Quercus alba in the upper canopy and Acer rubrum in the low to mid canopy, to changes in photosynthetically active radiation above the canopy (Q o ), vapor pressure deficit within the canopy (D), and soil moisture depletion during an entire growing season. Water loss before bud break (presumably through the bark) increased linearly with D, reaching 8% of daily stand transpiration (E C ) as measured when leaf area index was at maximum, and accounting for 5% of annual water loss. After leaves were completely expanded and when soil moisture was high, sap flux-scaled daily E C increased linearly with the daily sum of Q o . Species differences in this response were observed. Q. alba reached a maximum transpiration at low Q o , while A. rubrum showed increasing transpiration with Q o at all light levels. Daily E C increased in response to daily average D, with an asymptotic response due to the behavior of Q. alba. Transpiration of A. rubrum showed a greater response to soil moisture depletion than did that of Q. alba. When evaluated at a half-hourly scale under high Q o , mean canopy stomatal conductance (G S ) of individuals decreased with D. The sensitivity of G S to D was greater in species with higher intrinsic G S . Regardless of position in the canopy, diffuse-porous species in this and an additional, more mesic stand showed higher G S and greater stomatal sensitivity to environmental variation than do ring-porous species.

Effect of sorbed water on disintegrant performance of four brands of Polacrilin Potassium NF.

PubMed

Bele, Mrudula H; Derle, Diliprao V

2012-03-01

Polacrilin Potassium NF is a commonly used weak cation exchange resin disintegrant in pharmaceutical tablets. The objective of this research was to evaluate the effects of sorbed moisture on physical characteristics and disintegrant performance of four brands of Polacrilin Potassium NF. The disintegrants were stored in five different relative humidity chambers and their dynamic vapor adsorption-desorption analysis, effect of moisture on their compressibility, compactability, particle size, morphology, water uptake rate, and disintegration ability were studied. Moisture seemed to plasticize the disintegrants, reducing their yield pressures. However, certain optimum amount of moisture was found to be useful in increasing the compactablity of the tablets containing disintegrants. The tablets, however, lost their tensile strengths beyond this optimum moisture content. Moisture caused two brands of the disintegrants to swell; however, two other brands aggregated upon exposure to moisture. Swelling without aggregation increased the water uptake, and in turn the disintegrant performance. However, aggregation probably reduced the porosities of the disintegrants, reducing their water uptake rate and disintegrant performance. Different brands of Polacrilin Potassium NF differed in the abilities to withstand the effects of moisture on their functionality. Effect of moisture on disintegrant performance of Polacrilin Potassium NF needs to be considered before its use in tablets made by wet granulation.

[Differentiation between moisture lesions and pressure ulcers using photographs in a critical area].

PubMed

Valls-Matarín, Josefa; Del Cotillo-Fuente, Mercedes; Pujol-Vila, María; Ribal-Prior, Rosa; Sandalinas-Mulero, Inmaculada

2016-01-01

To identify difficulties for nurses in differentiating between moisture lesions and pressure ulcers, proper classification of pressure ulcers to assess the adequate classification of the Grupo Nacional para el Estudio y Asesoramiento de Úlceras por Presión y Heridas Crónicas (GNEAUPP) and the degree of agreement in the correct assessment by type and category of injury. Cross-sectional study in a critical area during 2014. All nurses who agreed to participate were included. They performed a questionnaire with 14 photographs validated by experts of moisture lesions or pressure ulcers in the sacral area and buttocks, with 6 possible answers: Pressure ulcer category I, II, III, IV, moisture lesions and unknown. Demographics and knowledge of the classification system of the pressure ulcers were collected according to GNEAUPP. It involved 98% of the population (n=56); 98.2% knew the classification system of the GNEAUPP; 35.2% of moisture lesions were considered as pressure ulcers, most of them as a category II (18.9%). The 14.8% of the pressure ulcers photographs were identified as moisture lesions and 16.1% were classified in another category. The agreement between nurses earned a global Kappa index of .38 (95% CI: .29-.57). There are difficulties differentiating between pressure ulcers and moisture lesions, especially within initial categories. Nurses have the perception they know the pressure ulcers classification, but they do not classify them correctly. The degree of concordance in the diagnosis of skin lesions was low. Copyright © 2016 Elsevier España, S.L.U. All rights reserved.

Impact of Plant Functional Types on Coherence Between Precipitation and Soil Moisture: A Wavelet Analysis

NASA Astrophysics Data System (ADS)

Liu, Qi; Hao, Yonghong; Stebler, Elaine; Tanaka, Nobuaki; Zou, Chris B.

2017-12-01

Mapping the spatiotemporal patterns of soil moisture within heterogeneous landscapes is important for resource management and for the understanding of hydrological processes. A critical challenge in this mapping is comparing remotely sensed or in situ observations from areas with different vegetation cover but subject to the same precipitation regime. We address this challenge by wavelet analysis of multiyear observations of soil moisture profiles from adjacent areas with contrasting plant functional types (grassland, woodland, and encroached) and precipitation. The analysis reveals the differing soil moisture patterns and dynamics between plant functional types. The coherence at high-frequency periodicities between precipitation and soil moisture generally decreases with depth but this is much more pronounced under woodland compared to grassland. Wavelet analysis provides new insights on soil moisture dynamics across plant functional types and is useful for assessing differences and similarities in landscapes with heterogeneous vegetation cover.

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

NASA Astrophysics Data System (ADS)

Raja Shekhar, S. S.; Chandrasekar, K.; Sesha Sai, M. V. R.; Diwakar, P. G.; Dadhwal, V. K.

2014-11-01

Drought is a frequently occurring disaster affecting lives of millions of people across the world every year. Several parameters, indices and models are being used globally to forecast / early warning of drought and monitoring drought for its prevalence, persistence and severity. Since drought is a complex phenomenon, large number of parameter/index need to be evaluated to sufficiently address the problem. It is a challenge to generate input parameters from different sources like space based data, ground data and collateral data in short intervals of time, where there may be limitation in terms of processing power, availability of domain expertise, specialized models & tools. In this study, effort has been made to automate the derivation of one of the important parameter in the drought studies viz Soil Moisture. Soil water balance bucket model is in vogue to arrive at soil moisture products, which is widely popular for its sensitivity to soil conditions and rainfall parameters. This model has been encoded into "Fish-Bone" architecture using COM technologies and Open Source libraries for best possible automation to fulfill the needs for a standard procedure of preparing input parameters and processing routines. The main aim of the system is to provide operational environment for generation of soil moisture products by facilitating users to concentrate on further enhancements and implementation of these parameters in related areas of research, without re-discovering the established models. Emphasis of the architecture is mainly based on available open source libraries for GIS and Raster IO operations for different file formats to ensure that the products can be widely distributed without the burden of any commercial dependencies. Further the system is automated to the extent of user free operations if required with inbuilt chain processing for every day generation of products at specified intervals. Operational software has inbuilt capabilities to automatically download requisite input parameters like rainfall, Potential Evapotranspiration (PET) from respective servers. It can import file formats like .grd, .hdf, .img, generic binary etc, perform geometric correction and re-project the files to native projection system. The software takes into account the weather, crop and soil parameters to run the designed soil water balance model. The software also has additional features like time compositing of outputs to generate weekly, fortnightly profiles for further analysis. Other tools to generate "Area Favorable for Crop Sowing" using the daily soil moisture with highly customizable parameters interface has been provided. A whole India analysis would now take a mere 20 seconds for generation of soil moisture products which would normally take one hour per day using commercial software.

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.

Investigation on the dominant factors controlling the spatio-temporal distribution of soil moisture in experimental grasslands

NASA Astrophysics Data System (ADS)

Schwichtenberg, G.; Hildebrandt, A.; Samaniego-Eguiguren, L.; Kreutziger, Y.; Attinger, S.

2009-04-01

The spatio-temporal distribution of soil moisture in the unsaturated zone influences the vegetation growth, governs the runoff generation processes as well as the energy balance at the interface between biosphere and the atmosphere, by influencing evapotranspiration. A better understanding of the spatio-temporal variability and dependence of soil moisture on living versus abiotic environment would lead to an improved representation of the soil-vegetation-atmosphere processes in hydrological and climate models. The Jena Experiment site (Germany) was established October 2001 in order to analyse the interaction between plant diversity and ecosystem processes. The main experiment covers 92 plots of 20 x 20 m arranged into a grid, on which a mixture of up to 60 grassland species and of one to four plant functional groups have been seeded. Each of these plots is equipped with at least one measurement tube for soil moisture. Measurements have been conducted weekly for four growing seasons (SSF). Here, we use geostatistical methods, like variograms and multivariate regressions, to investigate in how far abiotic environment and ecosystem explain the spatial and temporal variation of soil moisture at the Jena Experiment site. We test the influence of the soil environment, biodiversity, leaf area index and groundwater table. The poster will present the results of this analysis.

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.

Acceptability and efficacy of an emollient containing ceramide-precursor lipids and moisturizing factors for atopic dermatitis in pediatric patients.

PubMed

Hon, Kam Lun; Pong, Nga Hin; Wang, Shuxin Susan; Lee, Vivian W; Luk, Nai Ming; Leung, Ting Fan

2013-03-01

Atopic eczema or dermatitis (AD) is associated with atopy and is characterized by reduced skin hydration and an impaired skin barrier in the epidermis. We investigated the patient acceptability and efficacy of an emollient containing ceramide-precursor lipids and moisturizing factors (LMF) in AD. Consecutive AD patients were recruited. Swabs and cultures were obtained from the right antecubital fossa and the worst-affected eczematous area, and disease severity [according to the SCORing Atopic Dermatitis (SCORAD) Index], skin hydration, and transepidermal water loss (TEWL) were measured prior to and after 2 weeks' use of the LMF moisturizer. The general acceptability of treatment was documented as being 'very good', 'good', 'fair', or 'poor'. Twenty-four AD patients [mean age 13.8 (standard deviation 5.7) years] were recruited. Two thirds of the patients reported very good or good acceptability of the LMF moisturizer, whereas one third reported fair or poor acceptability. There were no inter-group differences in the pre-use clinical parameters of age, objective SCORAD score, pruritus score, sleep disturbance score, skin hydration, TEWL, topical corticosteroid use, oral antihistamine use, or acceptability of previously used proprietary emollients. However, patients in the fair/poor acceptability group were more likely to have Staphylococcus aureus colonization and to be female (odds ratio 13, 95 % confidence interval 1.7-99.4; p = 0.021). Following use of the LMF moisturizer, the objective SCORAD score, pruritus score, and sleep disturbance score were lower in the very good/good acceptability group than in the fair/poor acceptability group. The mean objective SCORAD score improved (from 31.5 to 25.7; p = 0.039) and skin hydration improved [from 30.7 arbitrary units (a.u.) to 36.0 a.u.; p = 0.021] in the very good/good acceptability group. When the data were analyzed for the strength of the agreement of the rating of acceptability, the κ values were 0.338 (fair) for use of body wash and 0.118 (poor) for use of emollients before and after the trial. The LMF moisturizer was considered acceptable by two thirds of the patients with AD. It seems that patients who found the moisturizer acceptable were less likely to be female or to be colonized by S. aureus before switching to the product, and they had less severe eczema, less pruritus, and less sleep disturbance after its use than patients who did not find the product acceptable. Gender and S. aureus colonization may have influenced the patient acceptability and clinical efficacy of the LMF moisturizer. The lack of agreement with regard to the acceptability of the moisturizer implies that there is room for parent/patient education to improve compliance.

Estimating Surface Soil Moisture in Simulated AVIRIS Spectra

NASA Technical Reports Server (NTRS)

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

2004-01-01

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

Spatial Scale Gap Filling Using an Unmanned Aerial System: A Statistical Downscaling Method for Applications in Precision Agriculture.

PubMed

Hassan-Esfahani, Leila; Ebtehaj, Ardeshir M; Torres-Rua, Alfonso; McKee, Mac

2017-09-14

Applications of satellite-borne observations in precision agriculture (PA) are often limited due to the coarse spatial resolution of satellite imagery. This paper uses high-resolution airborne observations to increase the spatial resolution of satellite data for related applications in PA. A new variational downscaling scheme is presented that uses coincident aerial imagery products from "AggieAir", an unmanned aerial system, to increase the spatial resolution of Landsat satellite data. This approach is primarily tested for downscaling individual band Landsat images that can be used to derive normalized difference vegetation index (NDVI) and surface soil moisture (SSM). Quantitative and qualitative results demonstrate promising capabilities of the downscaling approach enabling effective increase of the spatial resolution of Landsat imageries by orders of 2 to 4. Specifically, the downscaling scheme retrieved the missing high-resolution feature of the imageries and reduced the root mean squared error by 15, 11, and 10 percent in visual, near infrared, and thermal infrared bands, respectively. This metric is reduced by 9% in the derived NDVI and remains negligibly for the soil moisture products.

Spatial Scale Gap Filling Using an Unmanned Aerial System: A Statistical Downscaling Method for Applications in Precision Agriculture

PubMed Central

Hassan-Esfahani, Leila; Ebtehaj, Ardeshir M.; McKee, Mac

2017-01-01

Applications of satellite-borne observations in precision agriculture (PA) are often limited due to the coarse spatial resolution of satellite imagery. This paper uses high-resolution airborne observations to increase the spatial resolution of satellite data for related applications in PA. A new variational downscaling scheme is presented that uses coincident aerial imagery products from “AggieAir”, an unmanned aerial system, to increase the spatial resolution of Landsat satellite data. This approach is primarily tested for downscaling individual band Landsat images that can be used to derive normalized difference vegetation index (NDVI) and surface soil moisture (SSM). Quantitative and qualitative results demonstrate promising capabilities of the downscaling approach enabling effective increase of the spatial resolution of Landsat imageries by orders of 2 to 4. Specifically, the downscaling scheme retrieved the missing high-resolution feature of the imageries and reduced the root mean squared error by 15, 11, and 10 percent in visual, near infrared, and thermal infrared bands, respectively. This metric is reduced by 9% in the derived NDVI and remains negligibly for the soil moisture products. PMID:28906428

Soil Moisture Content Estimation Based on Sentinel-1 and Auxiliary Earth Observation Products. A Hydrological Approach

PubMed Central

Alexakis, Dimitrios D.; Mexis, Filippos-Dimitrios K.; Vozinaki, Anthi-Eirini K.; Daliakopoulos, Ioannis N.; Tsanis, Ioannis K.

2017-01-01

A methodology for elaborating multi-temporal Sentinel-1 and Landsat 8 satellite images for estimating topsoil Soil Moisture Content (SMC) to support hydrological simulation studies is proposed. After pre-processing the remote sensing data, backscattering coefficient, Normalized Difference Vegetation Index (NDVI), thermal infrared temperature and incidence angle parameters are assessed for their potential to infer ground measurements of SMC, collected at the top 5 cm. A non-linear approach using Artificial Neural Networks (ANNs) is tested. The methodology is applied in Western Crete, Greece, where a SMC gauge network was deployed during 2015. The performance of the proposed algorithm is evaluated using leave-one-out cross validation and sensitivity analysis. ANNs prove to be the most efficient in SMC estimation yielding R2 values between 0.7 and 0.9. The proposed methodology is used to support a hydrological simulation with the HEC-HMS model, applied at the Keramianos basin which is ungauged for SMC. Results and model sensitivity highlight the contribution of combining Sentinel-1 SAR and Landsat 8 images for improving SMC estimates and supporting hydrological studies. PMID:28635625

Soil Moisture Content Estimation Based on Sentinel-1 and Auxiliary Earth Observation Products. A Hydrological Approach.

PubMed

Alexakis, Dimitrios D; Mexis, Filippos-Dimitrios K; Vozinaki, Anthi-Eirini K; Daliakopoulos, Ioannis N; Tsanis, Ioannis K

2017-06-21

A methodology for elaborating multi-temporal Sentinel-1 and Landsat 8 satellite images for estimating topsoil Soil Moisture Content (SMC) to support hydrological simulation studies is proposed. After pre-processing the remote sensing data, backscattering coefficient, Normalized Difference Vegetation Index (NDVI), thermal infrared temperature and incidence angle parameters are assessed for their potential to infer ground measurements of SMC, collected at the top 5 cm. A non-linear approach using Artificial Neural Networks (ANNs) is tested. The methodology is applied in Western Crete, Greece, where a SMC gauge network was deployed during 2015. The performance of the proposed algorithm is evaluated using leave-one-out cross validation and sensitivity analysis. ANNs prove to be the most efficient in SMC estimation yielding R² values between 0.7 and 0.9. The proposed methodology is used to support a hydrological simulation with the HEC-HMS model, applied at the Keramianos basin which is ungauged for SMC. Results and model sensitivity highlight the contribution of combining Sentinel-1 SAR and Landsat 8 images for improving SMC estimates and supporting hydrological studies.

The correlation of Skylab L-band brightness temperatures with antecedent precipitation

NASA Technical Reports Server (NTRS)

Mcfarland, M. J.

1975-01-01

The S194 L-band radiometer flown on the Skylab mission measured terrestrial radiation at the microwave wavelength of 21.4 cm. The terrain emissivity at this wavelength is strongly dependent on the soil moisture content, which can be inferred from antecedent precipitation. For the Skylab data acquisition pass from the Oklahoma panhandle to southeastern Texas on 11 June 1973, the S194 brightness temperatures are highly correlated with antecedent precipitation from the preceding eleven day period, but very little correlation was apparent for the preceding five day period. The correlation coefficient between the averaged antecedent precipitation index values and the corresponding S194 brightness temperatures between 230 K and 270 K, the region of apparent response to soil moisture in the data, was -0.97. The equation of the linear least squares line fitted to the data was: API (cm) = 31.99 -0.114 TB (K), where API is the antecedent precipitation index and TB is the S194 brightness temperature.

Rainfall Intensity and Frequency Explain Production Basis Risk in Cumulative Rain Index Insurance

NASA Astrophysics Data System (ADS)

Muneepeerakul, Chitsomanus P.; Muneepeerakul, Rachata; Huffaker, Ray G.

2017-12-01

With minimal moral hazard and adverse selection, weather index insurance promises financial resilience to farmers struck by harsh weather conditions through swift compensation at affordable premium. Despite these advantages, the very nature of indexing gives rise to production basis risk as the selected weather indexes do not sufficiently correspond to actual damages. To address this problem, we develop a stochastic yield model, built upon a stochastic soil moisture model driven by marked Poisson rainfall. Our analysis shows that even under similar temperature and rainfall amount yields can differ significantly; this was empirically supported by a 2-year field experiment in which rain-fed maize was grown under very similar total rainfall. Here, the year with more intense, less-frequent rainfall produces a better yield—a rare counter evidence to most climate change projections. Through a stochastic yield model, we demonstrate the crucial roles of rainfall intensity and frequency in determining the yield. Importantly, the model allows us to compute rainfall pattern-related basis risk inherent in cumulative rain index insurance. The model results and a case study herein clearly show that total rainfall is a poor indicator of yield, imposing unnecessary production basis risk on farmers and false-positive payouts on insurers. Incorporating rainfall intensity and frequency in the design of rain index insurance can offer farmers better protection, while maintaining the attractive features of the weather index insurance and thus fulfilling its promise of financial resilience.

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

NASA Astrophysics Data System (ADS)

Cao, W.; Sheng, Y.

2017-12-01

The soil moisture movement is an important carrier of material cycle and energy flow among the various geo-spheres in the cold regions. It is very critical to protect the alpine ecology and hydrologic cycle in Qinghai-Tibet Plateau. Especially, it becomes one of the key problems to reveal the spatial-temporal variability of soil moisture movement and its main influence factors in earth system science. Thus, this research takes the north slope of Bayan Har Mountains in Qinghai-Tibet Plateau as a case study. The present study firstly investigates the change of permafrost moisture in different slope positions and depths. Based on this investigation, this article attempts to investigate the spatial variability of permafrost moisture and identifies the key influence factors in different terrain conditions. The method of classification and regression tree (CART) is adopted to identify the main controlling factors influencing the soil moisture movement. And the relationships between soil moisture and environmental factors are revealed by the use of the method of canonical correspondence analysis (CCA). The results show that: 1) the change of the soil moisture on the permafrost slope is divided into 4 stages, including the freezing stability phase, the rapid thawing phase, the thawing stability phase and the fast freezing phase; 2) this greatly enhances the horizontal flow in the freezing period due to the terrain slope and the freezing-thawing process. Vertical migration is the mainly form of the soil moisture movement. It leads to that the soil-moisture content in the up-slope is higher than that in the down-slope. On the contrary, the soil-moisture content in the up-slope is lower than that in the down-slope during the melting period; 3) the main environmental factors which affect the slope-permafrost soil-moisture are elevation, soil texture, soil temperature and vegetation coverage. But there are differences in the impact factors of the soil moisture in different freezing-thawing stages; 4) the main factors that affect the slope-permafrost soil-moisture at the shallow depth of 0-20cm are slope, elevation and vegetation coverage. And the main factors influencing the soil moisture at the middle and lower depth are complex.

[Position of Betula ermanii population ecotone in Changbai Mountains].

PubMed

Zou, Chunjing; Wang, Xiaochun; Han, Shijie

2004-12-01

The vegetation on the northern slope of Changbai Mountains forms a vertical zone due to the vertical differentiation of moisture and heat conditions. Ecotones are obviously existed between different vegetation zones, but it is difficult to decide their positions. In the area from 1400 m to 2200 m elevation, we adopted the methods of gradient sampling, fractal analysis, population pattern analysis, and interspecific competition index analysis to describe Betula ermanii population ecotone. The results showed that there was a forest ecotone between Betula ermanii and Picea-Abies forest near elevation 1650 m, and there was a forest line ecotone between Betula ermanii and alpine tundra near elevation 2080 m.

Changes of glacier, glacier-fed rivers and lakes in Altai Tavan Bogd National Park, Western Mongolia, based on multispectral satellite data from 1990 to 2017

NASA Astrophysics Data System (ADS)

Batsaikhan, B.; Lkhamjav, O.; Batsaikhan, N.

2017-12-01

Impacts on glaciers and water resource management have been altering through climate changes in Mongolia territory characterized by dry and semi-arid climate with low precipitation. Melting glaciers are early indicators of climate change unlike the response of the forests which is slower and takes place over a long period of time. Mountain glaciers are important environmental components of local, regional, and global hydrological cycles. The study calculates an overview of changes for glacier, glacier-fed rivers and lakes in Altai Tavan Bogd mountain, the Western Mongolia, based on the indexes of multispectral data and the methods typically applied in glacier studies. Were utilized an integrated approach of Normalized Difference Snow Index (NDSI) and Normalized Difference Water Index (NDWI) to combine Landsat, MODIS imagery and digital elevation model, to identify glacier cover are and quantify water storage change in lakes, and compared that with and climate parameters including precipitation, land surface temperature, evaporation, moisture. Our results show that melts of glacier at the study area has contributed to significantly increase of water storage of lakes in valley of The Altai Tavan Bogd mountain. There is hydrologic connection that lake basin is directly fed by glacier meltwater.

Experimental study of the moisture distribution on the wetting front during drainage and imbibition in a 2D sand chamber

NASA Astrophysics Data System (ADS)

Wei, Yunbo; Chen, Kouping; Wu, Jichun; Zhu, Xiaobin

2018-06-01

In the present study, the moisture distribution on the wetting front during drainage and imbibition in a 2D sand chamber is studied thoroughly. Based on the high-resolution data measured by light transmission method, the moisture distribution is observed and then analyzed quantitatively. During drainage and imbibition, different moisture distributions are observed: (a) during drainage, moisture contents fluctuate in a larger range and fingers can be seen on the wetting front; (b) while during imbibition, moisture contents fluctuate in a smaller range and the wetting front is more regular. The Hurst coefficients are successful in capturing different characteristics of the moisture distribution between drainage and imbibition. During imbibition, the Hurst coefficients are around 0.2 on the wetting front; while during drainage, the Hurst coefficients are around 0.5. As the porosity changes from 0.336 to 0.383, the moisture distribution in the sand chamber does not display obvious change. While as the imbibition rate increases from 5 ml/min to 400 ml/min, the moisture distribution on the wetting front becomes more uniform.

A new method to determine the water activity and the net isosteric heats of sorption for low moisture foods at elevated temperatures.

PubMed

Tadapaneni, Ravi Kiran; Yang, Ren; Carter, Brady; Tang, Juming

2017-12-01

In recent years, research studies have shown that the thermal resistance of foodborne pathogens in the low moisture foods is greatly influenced by the water activity (a w ) at temperatures relevant to thermal treatments for pathogen control. Yet, there has been a lack of an effective method for accurate measurement of a w at those temperatures. Thus, the main aim of this study was to evaluate a new method for measuring a w of food samples at elevated temperatures. An improved thermal cell with a relative humidity and temperature sensor was used to measure the a w of the three different food samples, namely, organic wheat flour, almond flour, and non-fat milk powder, over the temperature range between 20 and 80°C. For a constant moisture content, the a w data was used to estimate the net isosteric heat of sorption (q st ). The q st values were then used in the Clausius Clapeyron equation (CCE) equation to estimate the moisture sorption isotherm for all test food samples at different temperatures. For all the tested samples of any fixed moisture content, a w value generally increased with the temperature. The energy for sorption decreased with increasing moisture content. With the experimentally determined q st value, CCE describes well about the changes in a w of the food samples between 20 and 80°C. This study presents a method to obtain a w of a food sample for a specific moisture content at different temperatures which could be extended to obtain q st values for different moisture contents and hence, the moisture sorption isotherm of a food sample at different temperatures. Copyright © 2017 Elsevier Ltd. All rights reserved.

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...

Using Landsat data to estimate evapotranspiration of winter wheat

NASA Technical Reports Server (NTRS)

Kanemasu, E. T.; Heilman, J. L.; Bagley, J. O.; Powers, W. L.

1977-01-01

Results obtained from an evapotranspiration model as applied to Kansas winter wheatfields were compared with results determined by a weighing lysimeter, and the standard deviation was found to be less than 0.5 mm/day (however, the 95% confidence interval was between plus and minus 0.2 mm/day). Model inputs are solar radiation, temperature, precipitation, and leaf area index; an equation was developed to estimate the leaf area index from Landsat data. The model provides estimates of transpiration, evaporation, and soil moisture.

[Effects of nitrogen application rate on light interception and dry matter distribution at diffe-rent layers in wheat canopy under supplemental irrigation based on measuring soil moisture.

PubMed

Zheng, Xue Jiao; Yu, Zhen Wen; Zhang, Yong Li; Shi, Yu

2018-02-01

With the large-spike wheat cultivar Shannong 23 as test material,a field experiment was conducted by increasing the relative soil moisture content to 70% and 65% at jointing and anthesis stages. Four nitrogen levels,0 (N 0 ), 180 (N 1 ), 240 (N 2 ) and 300 kg·hm -2 (N 3 ), were designed to examine the effects of nitrogen application rates on the interception of photosynthetic active radiation (PAR) and dry matter distribution of wheat at different canopy layers. The results showed that the total stem number of wheat population at anthesis stage, the leaf area index at 10, 20 and 30 days after anthesis, PAR capture ratio at upper and middle layers and total PAR capture ratio in wheat canopy on day 20 after anthesis of treatment N 2 were significantly higher than those in the treatments of both N 0 and N 1 . Those indexes showed no significant increase when the application rate increased to 300 kg·hm -2 (N 3 ). The vegetative organ dry matter accumulation of all layers at maturity stage of treatment N 2 were significantly higher than N 0 and N 1 . Compared with treatment N 0 and N 1 , N 2 increased the grain and total dry matter accumulation by 36.7% and 35.4%, 9.5% and 10.2%, respectively, but had no significant difference with treatment N 3 . The vegetative organ dry matter accumulation at all layers, grain and total dry matter accumulation were significantly and positively correlated with PAR capture ratio at upper and middle layers, and had no significant correlation with that at lower layer. The vegetative organ dry matter accumulation at all layers was significantly and positively correlated with grain dry matter accumulation. The application rate at 240 kg·hm -2 (N 2 ) would be the optimum treatment under the present experimental condition.

Electromagnetic characterization of white spruce at different moisture contents using synthetic aperture radar imaging

NASA Astrophysics Data System (ADS)

Ingemi, Christopher M.; Owusu Twumasi, Jones; Yu, Tzuyang

2018-03-01

Detection and quantification of moisture content inside wood (timber) is key to ensuring safety and reliability of timber structures. Moisture inside wood attracts insects and fosters the development of fungi to attack the timber, causing significant damages and reducing the load bearing capacity during their design life. The use of non-destructive evaluation (NDE) techniques (e.g., microwave/radar, ultrasonic, stress wave, and X-ray) for condition assessment of timber structures is a good choice. NDE techniques provide information about the level of deterioration and material properties of timber structures without obstructing their functionality. In this study, microwave/radar NDE technique was selected for the characterization of wood at different moisture contents. A 12 in-by-3.5 in-by-1.5 in. white spruce specimen (picea glauca) was imaged at different moisture contents using a 10 GHz synthetic aperture radar (SAR) sensor inside an anechoic chamber. The presence of moisture was found to increase the SAR image amplitude as expected. Additionally, integrated SAR amplitude was found beneficial in modeling the moisture content inside the wood specimen.

Integration of Satellite, Global Reanalysis Data and Macroscale Hydrological Model for Drought Assessment in Sub-Tropical Region of India

NASA Astrophysics Data System (ADS)

Pandey, V.; Srivastava, P. K.

2018-04-01

Change in soil moisture regime is highly relevant for agricultural drought, which can be best analyzed in terms of Soil Moisture Deficit Index (SMDI). A macroscale hydrological model Variable Infiltration Capacity (VIC) was used to simulate the hydro-climatological fluxes including evapotranspiration, runoff, and soil moisture storage to reconstruct the severity and duration of agricultural drought over semi-arid region of India. The simulations in VIC were performed at 0.25° spatial resolution by using a set of meteorological forcing data, soil parameters and Land Use Land Cover (LULC) and vegetation parameters. For calibration and validation, soil parameters obtained from National Bureau of Soil Survey and Land Use Planning (NBSSLUP) and ESA's Climate Change Initiative soil moisture (CCI-SM) data respectively. The analysis of results demonstrates that most of the study regions (> 80 %) especially for central northern part are affected by drought condition. The year 2001, 2002, 2007, 2008 and 2009 was highly affected by agricultural drought. Due to high average and maximum temperature, we observed higher soil evaporation that reduces the surface soil moisture significantly as well as the high topographic variations; coarse soil texture and moderate to high wind speed enhanced the drying upper soil moisture layer that incorporate higher negative SMDI over the study area. These findings can also facilitate the archetype in terms of daily time step data, lengths of the simulation period, various hydro-climatological outputs and use of reasonable hydrological model.

Moisture effects in heat transfer through clothing systems for wildland firefighters.

PubMed

Lawson, Lelia K; Crown, Elizabeth M; Ackerman, Mark Y; Dale, J Douglas

2004-01-01

Wildland firefighters work in unfavourable environments involving both heat and moisture. Moisture in clothing systems worn by wildland firefighters may increase or decrease heat transfer, depending on its source and location in the clothing system, location on the body, timing of application and degree of sorption. In this experiment, 4 outerwear/underwear combinations were exposed to 1 of 5 different conditions varying on amount and location of moisture. The fabric systems were then exposed to either a high-heat-flux flame exposure (83 kW/m(2)) or a low-heat-flux radiant exposure (10 kW/m(2)). Under high-heat-flux flame exposures, external moisture tended to decrease heat transfer through the fabric systems, while internal moisture tended to increase heat transfer. Under low-heat-flux radiant exposures, internal moisture decreased heat transfer through the fabric systems. The nature and extent of such differences was fabric dependent. Implications for test protocol development are discussed.

Varying hydric conditions during incubation influence egg water exchange and hatchling phenotype in the red-eared slider turtle.

PubMed

Delmas, Virginie; Bonnet, Xavier; Girondot, Marc; Prévot-Julliard, Anne-Caroline

2008-01-01

Environmental conditions within the nest, notably temperature and moisture of substrate, exert a powerful influence during embryogenesis in oviparous reptiles. The influence of fluctuating nest temperatures has been experimentally examined in different reptile species; however, similar experiments using moisture as the key variable are lacking. In this article, we examine the effect of various substrate moisture regimes during incubation on different traits (egg mass, incubation length, and hatchling mass) in a chelonian species with flexible-shelled eggs, the red-eared slider turtle (Trachemys scripta elegans). Our results show that the rate of water uptake by the eggs was higher in wet than in dry substrate and varied across development. More important, during the first third of development, the egg mass changes were relatively independent of the soil moisture level; they became very sensitive to moisture levels during the other two-thirds. Moreover, hydric conditions exerted a strong influence on the eggs' long-term sensitivity to the moisture of the substrate. Even short-term episodes of high or low levels of moisture modified permanently their water sensitivity, notably through modification of eggshell shape and volume, and in turn entailed significant effects on hatchling mass (and hence offspring quality). Such complex influences of fluctuating moisture levels at various incubation stages on hatchling phenotype better reflect the natural situation, compared to experiments based on stable, albeit different, moisture levels.

Soil Moisture as an Estimator for Crop Yield in Germany

NASA Astrophysics Data System (ADS)

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

2015-04-01

Annual crop yield depends on various factors such as soil properties, management decisions, and meteorological conditions. Unfavorable weather conditions, e.g. droughts, have the potential to drastically diminish crop yield in rain-fed agriculture. For example, the drought in 2003 caused direct losses of 1.5 billion EUR only in Germany. Predicting crop yields allows to mitigate negative effects of weather extremes which are assumed to occur more often in the future due to climate change. A standard approach in economics is to predict the impact of climate change on agriculture as a function of temperature and precipitation. This approach has been developed further using concepts like growing degree days. Other econometric models use nonlinear functions of heat or vapor pressure deficit. However, none of these approaches uses soil moisture to predict crop yield. We hypothesize that soil moisture is a better indicator to explain stress on plant growth than estimations based on precipitation and temperature. This is the case because the latter variables do not explicitly account for the available water content in the root zone, which is the primary source of water supply for plant growth. In this study, a reduced form panel approach is applied to estimate a multivariate econometric production function for the years 1999 to 2010. Annual crop yield data of various crops on the administrative district level serve as depending variables. The explanatory variable of major interest is the Soil Moisture Index (SMI), which quantifies anomalies in root zone soil moisture. The SMI is computed by the mesoscale Hydrological Model (mHM, www.ufz.de/mhm). The index represents the monthly soil water quantile at a 4 km2 grid resolution covering entire Germany. A reduced model approach is suitable because the SMI is the result of a stochastic weather process and therefore can be considered exogenous. For the ease of interpretation a linear functionality is preferred. Meteorological, phenological, geological, agronomic, and socio-economic variables are also considered to extend the model in order to reveal the proper causal relation. First results show that dry as well as wet extremes of SMI have a negative impact on crop yield for winter wheat. This indicates that soil moisture has at least a limiting affect on crop production.

Assessment of Evapotranspiration and Soil Moisture Content Across Different Scales of Observation

PubMed Central

Verstraeten, Willem W.; Veroustraete, Frank; Feyen, Jan

2008-01-01

The proper assessment of evapotranspiration and soil moisture content are fundamental in food security research, land management, pollution detection, nutrient flows, (wild-) fire detection, (desert) locust, carbon balance as well as hydrological modelling; etc. This paper takes an extensive, though not exhaustive sample of international scientific literature to discuss different approaches to estimate land surface and ecosystem related evapotranspiration and soil moisture content. This review presents: (i)a summary of the generally accepted cohesion theory of plant water uptake and transport including a shortlist of meteorological and plant factors influencing plant transpiration;(ii)a summary on evapotranspiration assessment at different scales of observation (sap-flow, porometer, lysimeter, field and catchment water balance, Bowen ratio, scintillometer, eddy correlation, Penman-Monteith and related approaches);(iii)a summary on data assimilation schemes conceived to estimate evapotranspiration using optical and thermal remote sensing; and(iv)for soil moisture content, a summary on soil moisture retrieval techniques at different spatial and temporal scales is presented. Concluding remarks on the best available approaches to assess evapotranspiration and soil moisture content with and emphasis on remote sensing data assimilation, are provided. PMID:27879697

Efficacy of Metarhizium anisopliae isolate MAX-2 from Shangri-la, China under desiccation stress

PubMed Central

2014-01-01

Background Metarhizium anisopliae, a soil-borne entomopathogen found worldwide, is an interesting fungus for biological control. However, its efficacy in the fields is significantly affected by environmental conditions, particularly moisture. To overcome the weakness of Metarhizium and determine its isolates with antistress capacity, the efficacies of four M. anisopliae isolates, which were collected from arid regions of Yunnan Province in China during the dry season, were determined at different moisture levels, and the efficacy of the isolate MAX-2 from Shangri-la under desiccation stress was evaluated at low moisture level. Results M. anisopliae isolates MAX-2, MAC-6, MAL-1, and MAQ-28 showed gradient descent efficacies against sterile Tenebrio molitor larvae, and gradient descent capacities against desiccation with the decrease in moisture levels. The efficacy of MAX-2 showed no significant differences at 35% moisture level than those of the other isolates. However, significant differences were found at 8% to 30% moisture levels. The efficacies of all isolates decreased with the decrease in moisture levels. MAX-2 was relatively less affected by desiccation stress. Its efficacy was almost unaffected by the decrease at moisture levels > 25%, but slowly decreased at moisture levels < 25%. By contrast, the efficacies of other isolates rapidly decreased with the decrease in moisture levels. MAX-2 caused different infection characteristics on T. molitor larvae under desiccation stress and in wet microhabitat. Local black patches were found on the cuticles of the insects, and the cadavers dried without fungal growth under desiccation stress. However, dark black internodes and fungal growth were found after death of the insects in the wet microhabitat. Conclusions MAX-2 showed significantly higher efficacy and superior antistress capacity than the other isolates under desiccation stress. The infection of sterile T. molitor larvae at low moisture level constituted a valid laboratory bioassay system in evaluating M. anisopliae efficacy under desiccation stress. PMID:24383424

Efficacy of Metarhizium anisopliae isolate MAX-2 from Shangri-la, China under desiccation stress.

PubMed

Chen, Zi-Hong; Xu, Ling; Yang, Feng-lian; Ji, Guang-Hai; Yang, Jing; Wang, Jian-Yun

2014-01-03

Metarhizium anisopliae, a soil-borne entomopathogen found worldwide, is an interesting fungus for biological control. However, its efficacy in the fields is significantly affected by environmental conditions, particularly moisture. To overcome the weakness of Metarhizium and determine its isolates with antistress capacity, the efficacies of four M. anisopliae isolates, which were collected from arid regions of Yunnan Province in China during the dry season, were determined at different moisture levels, and the efficacy of the isolate MAX-2 from Shangri-la under desiccation stress was evaluated at low moisture level. M. anisopliae isolates MAX-2, MAC-6, MAL-1, and MAQ-28 showed gradient descent efficacies against sterile Tenebrio molitor larvae, and gradient descent capacities against desiccation with the decrease in moisture levels. The efficacy of MAX-2 showed no significant differences at 35% moisture level than those of the other isolates. However, significant differences were found at 8% to 30% moisture levels. The efficacies of all isolates decreased with the decrease in moisture levels. MAX-2 was relatively less affected by desiccation stress. Its efficacy was almost unaffected by the decrease at moisture levels > 25%, but slowly decreased at moisture levels < 25%. By contrast, the efficacies of other isolates rapidly decreased with the decrease in moisture levels. MAX-2 caused different infection characteristics on T. molitor larvae under desiccation stress and in wet microhabitat. Local black patches were found on the cuticles of the insects, and the cadavers dried without fungal growth under desiccation stress. However, dark black internodes and fungal growth were found after death of the insects in the wet microhabitat. MAX-2 showed significantly higher efficacy and superior antistress capacity than the other isolates under desiccation stress. The infection of sterile T. molitor larvae at low moisture level constituted a valid laboratory bioassay system in evaluating M. anisopliae efficacy under desiccation stress.

Modeling soil moisture memory in savanna ecosystems

NASA Astrophysics Data System (ADS)

Gou, S.; Miller, G. R.

2011-12-01

Antecedent soil conditions create an ecosystem's "memory" of past rainfall events. Such soil moisture memory effects may be observed over a range of timescales, from daily to yearly, and lead to feedbacks between hydrological and ecosystem processes. In this study, we modeled the soil moisture memory effect on savanna ecosystems in California, Arizona, and Africa, using a system dynamics model created to simulate the ecohydrological processes at the plot-scale. The model was carefully calibrated using soil moisture and evapotranspiration data collected at three study sites. The model was then used to simulate scenarios with various initial soil moisture conditions and antecedent precipitation regimes, in order to study the soil moisture memory effects on the evapotranspiration of understory and overstory species. Based on the model results, soil texture and antecedent precipitation regime impact the redistribution of water within soil layers, potentially causing deeper soil layers to influence the ecosystem for a longer time. Of all the study areas modeled, soil moisture memory of California savanna ecosystem site is replenished and dries out most rapidly. Thus soil moisture memory could not maintain the high rate evapotranspiration for more than a few days without incoming rainfall event. On the contrary, soil moisture memory of Arizona savanna ecosystem site lasts the longest time. The plants with different root depths respond to different memory effects; shallow-rooted species mainly respond to the soil moisture memory in the shallow soil. The growing season of grass is largely depended on the soil moisture memory of the top 25cm soil layer. Grass transpiration is sensitive to the antecedent precipitation events within daily to weekly timescale. Deep-rooted plants have different responses since these species can access to the deeper soil moisture memory with longer time duration Soil moisture memory does not have obvious impacts on the phenology of woody plants, as these can maintain transpiration for a longer time even through the top soil layer dries out.

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

USDA-ARS?s Scientific Manuscript database

The Soil Moisture and Ocean Salinity (SMOS) Earth observation satellite was launched in November 2009 to provide global soil moisture and ocean salinity measurements based on L-Band passive microwave measurements. Since its launch, different versions of SMOS soil moisture products processors have be...

Detecting moisture status of pecan orchards and the potential of remotely-sensed surface reflectance data

NASA Astrophysics Data System (ADS)

Othman, Yahia Abdelrahman

Demand for New Mexico's limited water resources coupled with periodic drought has increased the need to schedule irrigation of pecan orchards based on tree water status. The overall goal of this research was to develop advanced tree water status sensing techniques to optimize irrigation scheduling of pecan orchards. To achieve this goal, I conducted three studies in the La Mancha and Leyendecker orchards, both mature pecan orchards located in the Mesilla Valley, New Mexico. In the first study, I screened leaf-level physiological changes that occurred during cyclic irrigation to determine parameters that best represented changes in plant moisture status. Then, I linked plant physiological changes to remotely-sensed surface reflectance data derived from Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+). In the second study, I assessed the impact of water deficits that developed during the flood irrigation dry-down cycles on photosynthesis (A) and gas exchange and established preliminary water deficit thresholds of midday stem water potential (Psi smd) critical to A and gas exchange of pecans. In a third study, I investigated whether hyperspectral data obtained from a handheld spectroradiometer and multispectral remotely-sensed data derived from Landsat 7 ETM+ and Landsat 8 Operational Land Imager (OLI) could detect moisture status in pecans during cyclic flood irrigations. I conducted the first study simultaneously in both orchards. Leaf-level physiological responses and remotely-sensed surface reflectance data were collected from trees that were either well watered or in water deficit. Midday stem water potential was the best leaf-level physiological response to detect moisture status in pecans. Multiple linear regression between Psismd and vegetation indices revealed a significant relationship (R 2 = 0.54) in both orchards. Accordingly, I concluded that remotely-sensed multispectral data form Landsat TMETM+ holds promise for detecting the moisture status of pecans. I conducted the second study simultaneously on the same mature pecan orchards that were used in the first study. Photosynthesis and gas exchange were assessed at Psismd of -0.4 to -2.0 MPa. This study established preliminary values of Psismd that significantly impacted A and gas exchange of field-grown pecans. I recommended that pecan orchards be maintained at Psismd that ranged between -0.80 to -0.90 MPa to prevent significant reductions in A and gas exchange. Broken-line analysis revealed that A remained relatively constant when Psismd was above -0.65 MPa. Conversely, there was linear positive relationship between Psi smd and A when Psismd was less than -0.65 MPa. In the third study, again conducted on both orchards, leaf-level physiological measurements and remotely-sensed data were taken at Psismd levels of -0.40 to -0.85 MPa, -0.95 to -1.45 MPa , and -1.5 to -2.0 MPa. Hyperspectral reflectance indices (from handheld spectroradiometer) detected moisture status in pecan trees better than multispectral reflectance indices (from Landsat ETM+OLI). Vegetation moisture index-I (VMI-I) and vegetation moisture index-II (VMI-II) significantly correlated with Psismd (VMI-I, 0.88 > r > 0.87; VMI-II, -0.68 > r > -0.65). Vegetation moisture index-I Boxplot analysis did not clearly separate moderate water status (-0.95 to -1.45 MPa) at La Mancha, but did so at Leyendecker. However, multispectral reflectance indices had a limited capacity to precisely detect the moderate water status at both orchards (the time when A declined by 15 - 40 %). Given that Psi smd of-0.90 to -1.45 MPa is a critical range for irrigating pecans, I concluded that vegetation indices derived only from hyperspectral reflectance data could be used to detect plant physiological responses that are related to plant water status.

Remote Sensing to study soil-management systems in Itaí-SP

NASA Astrophysics Data System (ADS)

Soares da Silva, Natália; Máximo Sánchez-Román, Rodrigo; Marchamalo Sacristán, Miguel; Rodríguez-Sinobas, Leonor

2017-04-01

Nowadays, there is a worldwide concern to develop sustainable technologies for agriculture and a correct soil management is one of the principles toward the ecological production of crops. Soil covering is one of the most important tecniques to reduce erosion because the barrier on the surface prevents the direct impact of the rain drops. This technique improves soil fertility, keeps the soil moisture, reduces the evaporation losses and reduces the need of irrigation by 20%. The species used to cover the soil depends on the aim of the work, but is always important to know previously the availability of the material in the area and the possibility to use material of previous crops. In São Paulo State some studies are trying undertand how different soil-covering-systems affect plant production, especially for common bean, very important nutritionally and economically in Brazil. Nowadays, remote sensing could is used to study spatial dynamics, and to understand data in any place on the globe easily. For that, images of Earth freely obtained on the Internet are analyzed and interpreted to understand the dinamic of a specific local by the interaction between an electromagnetic radiation and different covering-vegetation. The aim of this study was monitoring by remote sensing an area of bean production with straw-covered-soil and straw-incorporated in the soil. The experimental site is in Itaí, São Paulo, Brazil, irrigated by central pivot. Images of different satellites (Landsat 7 and Landsat 8) were downloaded and analyzed by determining the soil moisture index (IUS) as a function of the normalized difference vegetation index (NDVI) for both straw-systems. There was correlation between IUS and NDVI data, and the highest value obtained was 0.98 for both systems and the lower one was 0.59 in the straw-covering system and 0.61 in the straw-incoporated system. Thus, the sensors were not sensitive to detect differences between the systems, and further studies are needed to identify which management system is better for soil physics, water holding and plant development.

The use of remotely-sensed snow, soil moisture and vegetation indices to develop resilience to climate change in Kazakhstan

NASA Astrophysics Data System (ADS)

Saidaliyeva, Zarina; Davenport, Ian; Nobakht, Mohamad; White, Kevin; Shahgedanova, Maria

2017-04-01

Kazakhstan is a major producer of grain. Large scale grain production dominates in the north, making Kazakhstan one of the largest exporters of grain in the world. Agricultural production accounts for 9% of the national GDP, providing 25% of national employment. The south relies on grain production from household farms for subsistence, and has low resilience, so is vulnerable to reductions in output. Yields in the south depend on snowmelt and glacier runoff. The major limit to production is water supply, which is affected by glacier retreat and frequent droughts. Climate change is likely to impact all climate drivers negatively, leading to a decrease in crop yield, which will impact Kazakhstan and countries dependent on importing its produce. This work makes initial steps in modelling the impact of climate change on crop yield, by identifying the links between snowfall, soil moisture and agricultural productivity. Several remotely-sensed data sources are being used. The availability of snowmelt water over the period 2010-2014 is estimated by extracting the annual maximum snow water equivalent (SWE) from the Globsnow dataset, which assimilates satellite microwave observations with field observations to produce a spatial map. Soil moisture over the period 2010-2016 is provided by the ESA Soil Moisture and Ocean Salinity (SMOS) mission. Vegetation density is approximated by the Normalised Difference Vegetation Index (NDVI) produced from NASA's MODIS instruments. Statistical information on crop yields is provided by the Ministry of National Economy of the Republic of Kazakhstan Committee on Statistics. Demonstrating the link between snowmelt yield and agricultural productivity depends on showing the impact of snow mass during winter on remotely-sensed soil moisture, the link between soil moisture and vegetation density, and finally the link between vegetation density and crop yield. Soil moisture maps were extracted from SMOS observations, and resampled onto a 40km x 40km grid, and analysed to produce monthly averages. The monthly maximum snow water equivalent estimates for March were resampled onto the same grid, to approximate the total snow contributing to snowmelt. The MODIS MOD13A2 1km 16-day NDVI product was resampled onto the same 40km grid, and aggregated into 32-day averages. Annual crop yield is available in terms of kg of yield per hectare for each region in Kazakhstan between 2004 and 2015. To show the connection between the snowmelt and soil moisture, the cells within the snow and soil moisture grids were compared to calculate correlation. Data were aggregated per region. Regions in northern Kazakhstan showed the strongest correlations, because more of the soil water supply is derived from snowmelt than rain, and the southern regions showed poor correlation because of the greater influence of rainfall and irrigation. Correlations between soil moisture and vegetation density, and crop yield are ongoing, and results will be presented. It is envisaged that this research will assist the Kazakh farming community, providing real-time soil moisture data from SMOS.

Investigating the hydrological significance of stalagmite geochemistry (Mg, Sr) using Sr isotope and particulate element records across the Late Glacial-to-Holocene transition

NASA Astrophysics Data System (ADS)

Belli, R.; Borsato, A.; Frisia, S.; Drysdale, R.; Maas, R.; Greig, A.

2017-02-01

The trace element and Sr isotope records in two coeval stalagmites characterized by different growth rates and flow regimes at Savi cave (Grotta Savi, NE Italy) reveal different sources and incorporation mechanisms for Mg and Sr. Mg is sourced primarily from dissolved cave host rock while particulate Mg derived from soil plays a subordinate role. The presence of particulate-borne Mg is inferred from the co-variation of Mg and particle-associated elements (Th, Al and Mn) which are preferentially concentrated in open columnar calcite layers. Variation in Mg concentrations corrected for particle-influenced components, the Mgc parameter, is controlled by water-rock interaction, with higher and lower Mgc during dry and wet phases, respectively. This is thought to reflect incongruent dissolution of Mg-rich phases. Correction of Sr concentrations for contributions from airborne exogenic Sr, based on 87Sr/86Sr ratios, yields the bedrock-only contribution (Src). Src variation in stalagmite calcite is influenced by speleothem growth rate and by variation of the calcite-water Sr partitioning in wet and dry phases, and only to a minor extent by incongruent dissolution of Mg-rich phases. Concentration profiles for Mgc and Srcg (corrected for growth rate effects) show inverse correlations and are inferred to show hydrological significance which is captured in a hydrological index, HI. We suggest HI provides robust information on water-rock interaction related to hydrological changes and can be utilized in both wet and semi-arid environments, provided the corrections for soil Mg and exogenic Sr can be applied with confidence. Application of the HI index allows correction of Grotta Savi oxygen isotope data, to yield a δ18Oc time series that shows when changes in moisture sources and atmospheric reorganization, or changes in moisture amount, were significant. This is especially evident during the Younger Dryas (YD). The Savi record supports the concept of a two-phase YD, marked by an increase of moisture and stronger impact of Adriatic and Mediterranean Sea influences over the northern Adriatic region from 12.3 ka onwards. Then, a large-scale atmospheric reorganization and gradual northward shift of the Polar Front caused a progressive reduction of sea influence over the region from 12.1 ka, supporting the concept of a hemispheric change.

Comparative analysis of different underlying surfaces using a high-resolution assimilation dataset in semi-arid areas in China

NASA Astrophysics Data System (ADS)

Ruan, Jinshuai; Wen, Xiaohang; Fan, Guangzhou; Li, Deqin; Hua, Wei; Wang, Bingyun; Zhang, Yi; Zhang, Mingjun; Wang, Chao; Wang, Lei

2017-11-01

To study the land surface and atmospheric meteorological characteristics of non-uniform underlying surfaces in the semi-arid area of Northeast China, we use a "High-Resolution Assimilation Dataset of the water-energy cycle in China (HRADC)". The grid points of three different underlying surfaces were selected, and their meteorological elements were averaged for each type (i.e., mixed forest, grassland, and cropland). For 2009, we compared and analyzed the different components of leaf area index (LAI), soil temperature and moisture, surface albedo, precipitation, and surface energy for various underlying surfaces in Northeast China. The results indicated that the LAI of mixed forest and cropland during the summer is greater than 5 m2 m-2 and below 2.5 m2 m-2 for grassland; in the winter and spring seasons, the Green Vegetation Fraction (GVF) is below 30%. The soil temperature and moisture both vary greatly. Throughout the year, the mixed forest is dominated by latent heat evaporation; in grasslands and croplands, the sensible heat flux and the latent heat flux are approximately equal, and the GVF contributed more to latent heat flux than sensible heat flux in the summer. This study compares meteorological characteristics between three different underlying surfaces of the semi-arid area of Northeast China and makes up for the insufficiency of purely using observations for the study. This research is important for understanding the water-energy cycle and transport in the semi-arid area.

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.

Correlated variation of floral and leaf traits along a moisture availability gradient.

PubMed

Lambrecht, Susan C; Dawson, Todd E

2007-04-01

Variation in flower size is an important aspect of a plant's life history, yet few studies have shown how flower size varies with environmental conditions and to what extent foliar responses to the environment are correlated with flower size. The objectives of this study were to (1) develop a theoretical framework for linking flower size and leaf size to their costs and benefits, as assessed using foliar stable carbon isotope ratio (delta(13)C) under varying degrees of water limitation, and then (2) examine how variation in flower size within and among species growing along a naturally occurring moisture availability gradient correlates with variation in delta(13)C and leaf size. Five plant species were examined at three sites in Oregon. Intra- and inter-specific patterns of flower size in relation to moisture availability were the same: the ratios of the area of flower display to total leaf area and of individual flower area to leaf area were greater at sites with more soil moisture compared to those sites with less soil moisture. The increase in flower area per unit increase in leaf area was greater at sites with more soil moisture than at sites where water deficit can occur. Values of delta(13)C, an index of water-use efficiency, were greater for plants with larger floral size. The patterns we observed generalize across species, irrespective of overall plant morphology or pollination system. These correlations between flower size, moisture availability, and delta(13)C suggest that water loss from flowers can influence leaf responses to the environment, which in turn may indirectly mediate an effect on flower size.

40 CFR 63.1104 - Process vents from continuous unit operations: applicability assessment procedures and methods.

Code of Federal Regulations, 2014 CFR

2014-07-01

... permit limit applicable to the process vent. (iv) Design analysis based on accepted chemical engineering... rates, halogenated process vent determinations, process vent TRE index values, and engineering... corrected to 2.3 percent moisture; or (2) The engineering assessment procedures in paragraph (k) of this...

40 CFR 63.1104 - Process vents from continuous unit operations: applicability assessment procedures and methods.

Code of Federal Regulations, 2013 CFR

2013-07-01

... permit limit applicable to the process vent. (iv) Design analysis based on accepted chemical engineering... rates, halogenated process vent determinations, process vent TRE index values, and engineering... corrected to 2.3 percent moisture; or (2) The engineering assessment procedures in paragraph (k) of this...

40 CFR 63.1104 - Process vents from continuous unit operations: applicability assessment procedures and methods.

Code of Federal Regulations, 2011 CFR

2011-07-01

... permit limit applicable to the process vent. (iv) Design analysis based on accepted chemical engineering... rates, halogenated process vent determinations, process vent TRE index values, and engineering... corrected to 2.3 percent moisture; or (2) The engineering assessment procedures in paragraph (k) of this...

40 CFR 63.1104 - Process vents from continuous unit operations: applicability assessment procedures and methods.

Code of Federal Regulations, 2012 CFR

2012-07-01

... permit limit applicable to the process vent. (iv) Design analysis based on accepted chemical engineering... rates, halogenated process vent determinations, process vent TRE index values, and engineering... corrected to 2.3 percent moisture; or (2) The engineering assessment procedures in paragraph (k) of this...

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.

[The stratification of moisture content and its dynamics in co-composting of sewage sludge and pig manure].

PubMed

Luo, Wei; Chen, Tong-bin; Gao, Ding; Zheng, Yu-qi; Zheng, Guo-di

2004-03-01

The experiment of co-composting of sewage sludge and pig manure was studied. The moisture contents were 50.82%-60.87% at the stage of temperature rising and 38.7%-52.17% at the stage of thermophilic fermentation, and the stratification of moisture content were not obvious for both stages because the door, the internal wall and the depth of the composting bay had little effect on the stratification. At the stage of cooling, the moisture content was 24.54%-49.39%, and the stratification of moisture content was remarkable as the door, the internal wall and the depth of the composting bay had great influence on it. At the stage of maturity, the moisture content was 19.18%-49.34%, and the stratification of moisture weakened, for which the door and the internal wall were mainly responsible. At the different composting stage, the degree of difference of moisture content on the profiles of the pile was of the order: maturity stage > cooling stage > thermophilic stage = temperature rising stage, and the moisture content in the pile was as follows: the lower > the middle > the upper. The relation between moisture content and composting time meeted with two-order kinetics equation.

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

NASA Astrophysics Data System (ADS)

Varikoden, Hamza; Revadekar, J. V.

2018-03-01

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

Multi-site assimilation of a terrestrial biosphere model (BETHY) using satellite derived soil moisture data

NASA Astrophysics Data System (ADS)

Wu, Mousong; Sholze, Marko

2017-04-01

We investigated the importance of soil moisture data on assimilation of a terrestrial biosphere model (BETHY) for a long time period from 2010 to 2015. Totally, 101 parameters related to carbon turnover, soil respiration, as well as soil texture were selected for optimization within a carbon cycle data assimilation system (CCDAS). Soil moisture data from Soil Moisture and Ocean Salinity (SMOS) product was derived for 10 sites representing different plant function types (PFTs) as well as different climate zones. Uncertainty of SMOS soil moisture data was also estimated using triple collocation analysis (TCA) method by comparing with ASCAT dataset and BETHY forward simulation results. Assimilation of soil moisture to the system improved soil moisture as well as net primary productivity(NPP) and net ecosystem productivity (NEP) when compared with soil moisture derived from in-situ measurements and fluxnet datasets. Parameter uncertainties were largely reduced relatively to prior values. Using SMOS soil moisture data for assimilation of a terrestrial biosphere model proved to be an efficient approach in reducing uncertainty in ecosystem fluxes simulation. It could be further used in regional an global assimilation work to constrain carbon dioxide concentration simulation by combining with other sources of measurements.

Soil Moisture under Different Vegetation cover in response to Precipitation

NASA Astrophysics Data System (ADS)

Liang, Z.; Zhang, J.; Guo, B.; Ma, J.; Wu, Y.

2016-12-01

The response study of soil moisture to different precipitation and landcover is significant in the field of Hydropedology. The influence of precipitation to soil moisture is obvious in addition to individual stable aquifer. With data of Hillsborough County, Florida, USA, the alluvial wetland forest and ungrazed Bahia grass that under wet and dry periods were chosen as the research objects, respectively. HYDRUS-3D numerical simulation method was used to simulate soil moisture dynamics in the root zone (10-50 cm) of those vegetation. The soil moisture response to precipitation was analyzed. The results showed that the simulation results of alluvial wetland forest by HYDRUS-3D were better than that of the Bahia grass, and for the same vegetation, the simulation results of soil moisture under dry period were better. Precipitation was more in June, 2003, the soil moisture change of alluvial wetland forest in 10-30 cm soil layer and Bahia grass in 10 cm soil layer were consistent with the precipitation change conspicuously. The alluvial wetland forest soil moisture declined faster than Bahia grass under dry period, which demonstrated that Bahia grass had strong ability to hold water. Key words: alluvial wetland forest; Bahia grass; soil moisture; HYDRUS-3D; precipitation

The effect of moisture on the shear bond strength of gold alloy rods bonded to enamel with a self-adhesive and a hydrophobic resin cement.

PubMed

Dursun, Elisabeth; Wiechmann, Dirk; Attal, Jean-Pierre

2010-06-01

The aim of this in vitro study was to investigate the influence of enamel moisture on the shear bond strength (SBS) of a hydrophobic resin cement, Maximum Cure (MC), and a self-adhesive resin cement, Multilink Sprint (MLS), after etching of the enamel. Forty cylindrical gold alloy rods were used to simulate the Incognito lingual bracket system. They were bonded to the enamel of 40 human teeth embedded in self-cured acrylic resin. Twenty were bonded with MC (10 on dry and 10 on wet enamel) and 20 with MLS (10 on dry and 10 on wet enamel). The SBS of MC and MLS was determined in a universal testing machine and the site of bond failure was defined by the adhesive remnant index (ARI). A Kruskal-Wallis test was performed followed by Games-Howell post hoc pairwise comparison tests on the SBS results (P < 0.05) and a chi-square test was used for the analysis of ARI scores (P < 0.05). On dry enamel, no significant differences between MC (58 +/- 5 MPa) and MLS (64 +/- 13 MPa) were noted. On wet enamel, the adherence of MC (6 +/- 8 MPa) and MLS (37 +/- 13 MPa) significantly decreased but to a lesser extent for MLS. The ARI scores corroborated these results. In conclusion, MC did not tolerate moisture. MLS was also affected but maintained sufficient adherence.

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

NASA Astrophysics Data System (ADS)

Singh, Gurjeet; Panda, Rabindra K.; Mohanty, Binayak P.; Jana, Raghavendra B.

2016-05-01

Strategic ground-based sampling of soil moisture across multiple scales is necessary to validate remotely sensed quantities such as NASA's Soil Moisture Active Passive (SMAP) product. In the present study, in-situ soil moisture data were collected at two nested scale extents (0.5 km and 3 km) to understand the trend of soil moisture variability across these scales. This ground-based soil moisture sampling was conducted in the 500 km2 Rana watershed situated in eastern India. The study area is characterized as sub-humid, sub-tropical climate with average annual rainfall of about 1456 mm. Three 3x3 km square grids were sampled intensively once a day at 49 locations each, at a spacing of 0.5 km. These intensive sampling locations were selected on the basis of different topography, soil properties and vegetation characteristics. In addition, measurements were also made at 9 locations around each intensive sampling grid at 3 km spacing to cover a 9x9 km square grid. Intensive fine scale soil moisture sampling as well as coarser scale samplings were made using both impedance probes and gravimetric analyses in the study watershed. The ground-based soil moisture samplings were conducted during the day, concurrent with the SMAP descending overpass. Analysis of soil moisture spatial variability in terms of areal mean soil moisture and the statistics of higher-order moments, i.e., the standard deviation, and the coefficient of variation are presented. Results showed that the standard deviation and coefficient of variation of measured soil moisture decreased with extent scale by increasing mean soil moisture.

Rainfall estimation by inverting SMOS soil moisture estimates: a comparison of different methods over Australia

USDA-ARS?s Scientific Manuscript database

Remote sensing of soil moisture has reached a level of maturity and accuracy for which the retrieved products can be used to improve hydrological and meteorological applications. In this study, the soil moisture product from the European Space Agency’s Soil Moisture and Ocean Salinity (SMOS) is used...

Predicting the potential moisture ingress characteristics of polyisobutylene based edge seals (Conference Presentation)

NASA Astrophysics Data System (ADS)

Kempe, Michael D.

2016-09-01

Photovoltaic devices are often sensitive to moisture and must be packaged in such a way as to limit moisture ingress for 25 years or more. Typically, this is accomplished through the use of impermeable front and backsheets (e.g., glass sheets or metal foils). However, this will still allow moisture ingress between the sheets from the edges. Attempts to hermetically seal with a glass frit or similarly welded bonds at the edge have had problems with costs and mechanical strength. Because of this, low diffusivity polyisobutylene materials filled with desiccant are typically used. Although it is well known that these materials will substantially delay moisture ingress, correlating that to outdoor exposure has been difficult. Here, we use moisture ingress measurements at different temperatures and relative humidities to find fit parameters for a moisture ingress model for an edge-seal material. Then, using meteorological data, a finite element model is used to predict the moisture ingress profiles for hypothetical modules deployed in different climates and mounting conditions, assuming no change in properties of the edge-seal as a function of aging.

A new simple compact refractometer applied to measurements of air density fluctuations

NASA Astrophysics Data System (ADS)

Fang, H.; Juncar, P.

1999-07-01

We describe a new simple, compact refractometer for air refractive index measurements. It consists of a double plane-plane Fabry Perot interferometer. Both interferometers consisting of Zerodur spacers of thickness of 1 and 100 mm are illuminated independently by the same single mode laser diode. The shorter cavity allows unambiguous identification of the transmission peak of the longer one to which the laser frequency is servo-locked. The refractive index of air is obtained via a heterodyne comparison with a second laser locked to a hyperfine component of the rubidium D2 line. We obtain a resolution of order 10-10 and accuracy of a few times 10-8. The metrological characteristics of the interferometer in vacuum are presented. Initial results for refractive index measurements agree with values calculated using the revised Edlen formulas. We also describe how this refractometer is used to measure variations of the density of air and their correlation with changes of refractive index of air. The density of air is used to make buoyancy corrections when comparing mass standards of different volume. Our preliminary results indicate that the values of air density determined by refractometry agree with those calculated using the Comité International des Poids et Mesures formula, which is based on measurements of temperature, pressure, moisture content, and CO2 concentration.

Response of deep soil moisture to land use and afforestation in the semi-arid Loess Plateau, China

NASA Astrophysics Data System (ADS)

Yang, Lei; Wei, Wei; Chen, Liding; Mo, Baoru

2012-12-01

SummarySoil moisture is an effective water source for plant growth in the semi-arid Loess Plateau of China. Characterizing the response of deep soil moisture to land use and afforestation is important for the sustainability of vegetation restoration in this region. In this paper, the dynamics of soil moisture were quantified to evaluate the effect of land use on soil moisture at a depth of 2 m. Specifically, the gravimetric soil moisture content was measured in the soil layer between 0 and 8 m for five land use types in the Longtan catchment of the western Loess Plateau. The land use types included traditional farmland, native grassland, and lands converted from traditional farmland (pasture grassland, shrubland and forestland). Results indicate that the deep soil moisture content decreased more than 35% after land use conversion, and a soil moisture deficit appeared in all types of land with introduced vegetation. The introduced vegetation decreased the soil moisture content to levels lower than the reference value representing no human impact in the entire 0-8 m soil profile. No significant differences appeared between different land use types and introduced vegetation covers, especially in deeper soil layers, regardless of which plant species were introduced. High planting density was found to be the main reason for the severe deficit of soil moisture. Landscape management activities such as tillage activities, micro-topography reconstruction, and fallowed farmland affected soil moisture in both shallow and deep soil layers. Tillage and micro-topography reconstruction can be used as effective countermeasures to reduce the soil moisture deficit due to their ability to increase soil moisture content. For sustainable vegetation restoration in a vulnerable semi-arid region, the plant density should be optimized with local soil moisture conditions and appropriate landscape management practices.

Complex linkage between soil, soil water, atmosphere and Eucalyptus Plantations

NASA Astrophysics Data System (ADS)

Shukla, C.; Tiwari, K. N.

2017-12-01

Eucalyptus is most widely planted genus grown in waste land of eastern region of India to meet the pulp industry requirements. Sustainability of these plantations is of concern because in spite of higher demand water and nutrients of plantations, they are mostly planted on low-fertility soils. This study has been conducted to quantify effect of 25 years old, a fully established eucalyptus plantations on i.) Alteration in physico-chemical and hydrological properties of soil of eucalyptus plantation in comparison to soil of natural grassland and ii.) Spatio-temporal variation in soil moisture under eucalyptus plantations. Soil physico-chemical properties of two adjacent plots covered with eucatuptus and natural grasses were analyzed for three consecutive depths (i.e. 0-30 cm, 30-60 cm and 60-90 cm) with five replications in each plot. Soil infiltration rate and saturated hydraulic conductivity (Ks) were measured in-situ to incorporate the influence of macro porosity caused due to roots of plantations. Daily soil moisture at an interval of 10 cm upto 160 cm depth with 3 replications and Leaf Area Index (LAI) at an interval of 15 days with 5 replications were recorded over the year. Significant variations found at level of 0.05 between soil properties of eucalyptus and natural grass land confirm the effect of plantations on soil properties. Comparative results of soil properties show significant alteration in soil texture such as percent of sand, organic matter and Ks found more by 20%, 9% and 22% respectively in eucalyptus plot as compare to natural grass land. Available soil moisture (ASM) was found constantly minimum in top soil excluding rainy season indicate upward movement of water and nutrients during dry season. Seasonal variation in temperature (T), relative humidity (RH) and leaf area index (LAI) influenced the soil moisture extraction phenomenon. This study clearly stated the impact of long term establishment of eucalyptus plantations make considerable alteration on soil texture and Ks. Also, relationship between T, RH, LAI and ASM developed can be used for soil moisture modelling for watersheds with eucalyptus plantations.

Optimum moisture levels for biodegradation of mortality composting envelope materials.

PubMed

Ahn, H K; Richard, T L; Glanville, T D

2008-01-01

Moisture affects the physical and biological properties of compost and other solid-state fermentation matrices. Aerobic microbial systems experience different respiration rates (oxygen uptake and CO2 evolution) as a function of moisture content and material type. In this study the microbial respiration rates of 12 mortality composting envelope materials were measured by a pressure sensor method at six different moisture levels. A wide range of respiration (1.6-94.2mg O2/g VS-day) rates were observed for different materials, with alfalfa hay, silage, oat straw, and turkey litter having the highest values. These four envelope materials may be particularly suitable for improving internal temperature and pathogen destruction rates for disease-related mortality composting. Optimum moisture content was determined based on measurements across a range that spans the maximum respiration rate. The optimum moisture content of each material was observed near water holding capacity, which ranged from near 60% to over 80% on a wet basis for all materials except a highly stabilized soil compost blend (optimum around 25% w.b.). The implications of the results for moisture management and process control strategies during mortality composting are discussed.

Study Variability of Seasonal Soil Moisture in Ensemble of CMIP5 Models Over South Asia During 1950-2005

NASA Astrophysics Data System (ADS)

Fahim, A. M.; Shen, R.; Yue, Z.; Di, W.; Mushtaq Shah, S.

2015-12-01

Moisture in the upper most layer of soil column from 14 different models under Coupled Model Intercomparison Project Phase-5 (CMIP5) project were analyzed for four seasons of the year. Aim of this study was to explore variability in soil moisture over south Asia using multi model ensemble and relationship between summer rainfall and soil moisture for spring and summer season. GLDAS (Global Land Data Assimilation System) dataset set was used for comparing CMIP5 ensemble mean soil moisture in different season. Ensemble mean represents soil moisture well in accordance with the geographical features; prominent arid regions are indicated profoundly. Empirical Orthogonal Function (EOF) analysis was applied to study the variability. First component of EOF explains 17%, 16%, 11% and 11% variability for spring, summer, autumn and winter season respectively. Analysis reveal increasing trend in soil moisture over most parts of Afghanistan, Central and north western parts of Pakistan, northern India and eastern to south eastern parts of China, in spring season. During summer, south western part of India exhibits highest negative trend while rest of the study area show minute trend (increasing or decreasing). In autumn, south west of India is under highest negative loadings. During winter season, north western parts of study area show decreasing trend. Summer rainfall has very week (negative or positive) spatial correlation, with spring soil moisture, while possess higher correlation with summer soil moisture. Our studies have significant contribution to understand complex nature of land - atmosphere interactions, as soil moisture prediction plays an important role in the cycle of sink and source of many air pollutants. Next level of research should be on filling the gaps between accurately measuring the soil moisture using satellite remote sensing and land surface modelling. Impact of soil moisture in tracking down different types of pollutant will also be studied.

The 100th Meridian Climate Divide & Its Present and Future Impact on the Human Geography of the American Great Plains

NASA Astrophysics Data System (ADS)

Feldman, J. R.; Seager, R.; Ting, M.; Lis, N.

2016-12-01

The 100th meridian has been viewed historically as a symbolic boundary between the more arid western plains in the Midwestern United States, and the more humid eastern half of the country. The purpose of this project is to evaluate the true climatic characteristics of this divide, and to determine its implications for landscape and land use, with a focus on agriculture. An aridity index is first defined as precipitation divided by the potential evapotranspiration, P/PET, where PET is calculated with the Penman-Monteith equation using data from the North American Land Data Assimilation System Phase 2 (NLDAS-2) for the period 1979-2015. The NLDAS-2 is a compilation of observed climate data and output from three land surface models: NOAH, VIC, and MOSAIC. The three models agreed on a clear west-east gradient in aridity, with a boundary dryland boundary at approximately the 100th meridian. The aridity index was then compared to the soil moisture from each model, to determine how it impacts water storage, and the soil moisture was consistent both annually and seasonally. Using USDA data from the 2012 census, the longitudinal distribution of agricultural variables, such as farm size and percent corn of total cropland, were examined. Clear differences were observed in these variables across the aridity boundary, especially in the Northern Plains. We performed regressions between these variables and the aridity index, and found a close relationship between the aridity index and the percent of corn and wheat grown, as well as farm size. To project the potential future changes in agricultural practices due to changes in aridity, we used CMIP5 projections of the aridity index changes over the plains in the period 2040-2060. In tandem with the regression relation, we were able to predict that the percent corn of total cropland may decrease by as much as 20% at all longitudes, and it may not even be feasible to grow east of the 100th meridian. Farm size is expected to increase across the plains. Thus, we began to explore how the farm economy may be impacted by the shifting aridity gradient due to climate change in the coming century.

Assimilation of Passive and Active Microwave Soil Moisture Retrievals

NASA Technical Reports Server (NTRS)

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

2012-01-01

Root-zone soil moisture is an important control over the partition of land surface energy and moisture, and the assimilation of remotely sensed near-surface soil moisture has been shown to improve model profile soil moisture [1]. To date, efforts to assimilate remotely sensed near-surface soil moisture at large scales have focused on soil moisture derived from the passive microwave Advanced Microwave Scanning Radiometer (AMSR-E) and the active Advanced Scatterometer (ASCAT; together with its predecessor on the European Remote Sensing satellites (ERS. The assimilation of passive and active microwave soil moisture observations has not yet been directly compared, and so this study compares the impact of assimilating ASCAT and AMSR-E soil moisture data, both separately and together. Since the soil moisture retrieval skill from active and passive microwave data is thought to differ according to surface characteristics [2], the impact of each assimilation on the model soil moisture skill is assessed according to land cover type, by comparison to in situ soil moisture observations.

Mass Conservation in Modeling Moisture Diffusion in Multi-Layer Carbon Composite Structures

NASA Technical Reports Server (NTRS)

Nurge, Mark A.; Youngquist, Robert C.; Starr, Stanley O.

2009-01-01

Moisture diffusion in multi-layer carbon composite structures is difficult to model using finite difference methods due to the discontinuity in concentrations between adjacent layers of differing materials. Applying a mass conserving approach at these boundaries proved to be effective at accurately predicting moisture uptake for a sample exposed to a fixed temperature and relative humidity. Details of the model developed are presented and compared with actual moisture uptake data gathered over 130 days from a graphite epoxy composite sandwich coupon with a Rohacell foam core.

Integrated method of RS and GPR for monitoring the changes in the soil moisture and groundwater environment due to underground coal mining

NASA Astrophysics Data System (ADS)

Bian, Zhengfu; Lei, Shaogang; Inyang, Hilary I.; Chang, Luqun; Zhang, Richen; Zhou, Chengjun; He, Xiao

2009-03-01

Mining affects the environment in different ways depending on the physical context in which the mining occurs. In mining areas with an arid environment, mining affects plants’ growth by changing the amount of available water. This paper discusses the effects of mining on two important determinants of plant growth—soil moisture and groundwater table (GWT)—which were investigated using an integrated approach involving a field sampling investigation with remote sensing (RS) and ground-penetrating radar (GPR). To calculate and map the distribution of soil moisture for a target area, we initially analyzed four models for regression analysis between soil moisture and apparent thermal inertia and finally selected a linear model for modeling the soil moisture at a depth 10 cm; the relative error of the modeled soil moisture was about 6.3% and correlation coefficient 0.7794. A comparison of mined and unmined areas based on the results of limited field sampling tests or RS monitoring of Landsat 5-thermatic mapping (TM) data indicated that soil moisture did not undergo remarkable changes following mining. This result indicates that mining does not have an effect on soil moisture in the Shendong coal mining area. The coverage of vegetation in 2005 was compared with that in 1995 by means of the normalized difference vegetation index (NDVI) deduced from TM data, and the results showed that the coverage of vegetation in Shendong coal mining area has improved greatly since 1995 because of policy input RMB¥0.4 per ton coal production by Shendong Coal Mining Company. The factor most affected by coal mining was GWT, which dropped from a depth of 35.41 m before mining to a depth of 43.38 m after mining at the Bulianta Coal Mine based on water well measurements. Ground-penetrating radar at frequencies of 25 and 50 MHz revealed that the deepest GWT was at about 43.4 m. There was a weak water linkage between the unsaturated zone and groundwater, and the decline of water table primarily resulted from the well pumping for mining safety rather than the movement of cracking strata. This result is in agreement with the measurements of the water wells. The roots of nine typical plants in the study area were investigated. Populus was found to have the deepest root system with a depth of about 26 m. Based on an assessment of plant growth demands and the effect of mining on environmental factors, we concluded that mining will have less of an effect on plant growth at those sites where the primary GWT depth before mining was deep enough to be unavailable to plants. If the primary GWT was available for plant growth before mining, especially to those plants with deeper roots, mining will have a significant effect on the growth of plants and the mechanism of this effect will include the loss of water to roots and damage to the root system.

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.

Capturing flood-to-drought transitions in regional climate model simulations

NASA Astrophysics Data System (ADS)

Anders, Ivonne; Haslinger, Klaus; Hofstätter, Michael; Salzmann, Manuela; Resch, Gernot

2017-04-01

In previous studies atmospheric cyclones have been investigated in terms of related precipitation extremes in Central Europe. Mediterranean (Vb-like) cyclones are of special relevance as they are frequently related to high atmospheric moisture fluxes leading to floods and landslides in the Alpine region. Another focus in this area is on droughts, affecting soil moisture and surface and sub-surface runoff as well. Such events develop differently depending on available pre-saturation of water in the soil. In a first step we investigated two time periods which encompass a flood event and a subsequent drought on very different time scales, one long lasting transition (2002/2003) and a rather short one between May and August 2013. In a second step we extended the investigation to the long time period 1950-2016. We focused on high spatial and temporal scales and assessed the currently achievable accuracy in the simulation of the Vb-events on one hand and following drought events on the other hand. The state-of-the-art regional climate model CCLM is applied in hindcast-mode simulating the single events described above, but also the time from 1948 to 2016 to evaluate the results from the short runs to be valid for the long time period. Besides the conventional forcing of the regional climate model at its lateral boundaries, a spectral nudging technique is applied. The simulations covering the European domain have been varied systematically different model parameters. The resulting precipitation amounts have been compared to E-OBS gridded European precipitation data set and a recent high spatially resolved precipitation data set for Austria (GPARD-6). For the drought events the Standardized Precipitation Evapotranspiration Index (SPEI), soil moisture and runoff has been investigated. Varying the spectral nudging setup helps us to understand the 3D-processes during these events, but also to identify model deficiencies. To improve the simulation of such events in the past, improves also the ability to assess a climate change signal in the recent and far future.

Stability and maturity of biowaste composts derived by small municipalities: Correlation among physical, chemical and biological indices.

PubMed

Oviedo-Ocaña, E R; Torres-Lozada, P; Marmolejo-Rebellon, L F; Hoyos, L V; Gonzales, S; Barrena, R; Komilis, D; Sanchez, A

2015-10-01

Stability and maturity are important criteria to guarantee the quality of a compost that is applied to agriculture or used as amendment in degraded soils. Although different techniques exist to evaluate stability and maturity, the application of laboratory tests in municipalities in developing countries can be limited due to cost and application complexities. In the composting facilities of such places, some classical low cost on-site tests to monitor the composting process are usually implemented; however, such tests do not necessarily clearly identify conditions of stability and maturity. In this article, we have applied and compared results of stability and maturity tests that can be easily employed on site (i.e. temperature, pH, moisture, electrical conductivity [EC], odor and color), and of tests that require more complex laboratory techniques (volatile solids, C/N ratio, self-heating, respirometric index, germination index [GI]). The evaluation of the above was performed in the field scale using 2 piles of biowaste applied compost. The monitoring period was from day 70 to day 190 of the process. Results showed that the low-cost tests traditionally employed to monitor the composting process on-site, such as temperature, color and moisture, do not provide consistent determinations with the more complex laboratory tests used to assess stability (e.g. respiration index, self-heating, volatile solids). In the case of maturity tests (GI, pH, EC), both the on-site tests (pH, EC) and the laboratory test (GI) provided consistent results. Although, stability was indicated for most of the samples, the maturity tests indicated that products were consistently immature. Thus, a stable product is not necessarily mature. Conclusively, the decision on the quality of the compost in the installations located in developing countries requires the simultaneous use of a combination of tests that are performed both in the laboratory and on-site. Copyright © 2015 Elsevier Ltd. All rights reserved.

Using Haines Index coupled with fire weather model predicted from high resolution LAM forecasts to asses wildfire extreme behaviour in Southern Europe.

NASA Astrophysics Data System (ADS)

Gaetani, Francesco; Baptiste Filippi, Jean; Simeoni, Albert; D'Andrea, Mirko

2010-05-01

Haines Index (HI) was developed by USDA Forest Service to measure the atmosphere's contribution to the growth potential of a wildfire. The Haines Index combines two atmospheric factors that are known to have an effect on wildfires: Stability and Dryness. As operational tools, HI proved its ability to predict plume dominated high intensity wildfires. However, since HI does not take into account the fuel continuity, composition and moisture conditions and the effects of wind and topography on fire behaviour, its use as forecasting tool should be carefully considered. In this work we propose the use of HI, predicted from HR Limited Area Model forecasts, coupled with a Fire Weather model (i.e., RISICO system) fully operational in Italy since 2003. RISICO is based on dynamic models able to represent in space and in time the effects that environment and vegetal physiology have on fuels and, in turn, on the potential behaviour of wildfires. The system automatically acquires from remote databases a thorough data-set of input information both of in situ and spatial nature. Meteorological observations, radar data, Limited Area Model weather forecasts, EO data, and fuel data are managed by a Unified Interface able to process a wide set of different data. Specific semi-physical models are used in the system to simulate the dynamics of the fuels (load and moisture contents of dead and live fuel) and the potential fire behaviour (rate of spread and linear intensity). A preliminary validation of this approach will be provided with reference to Sardinia and Corsica Islands, two major islands of the Mediterranean See frequently affected by extreme plume dominated wildfires. A time series of about 3000 wildfires burnt in Sardinia and Corsica in 2007 and 2008 will be used to evaluate the capability of HI coupled with the outputs of the Fire Weather model to forecast the actual risk in time and in space.

Influence of Vegetation Cover on Rain Pulse Responses in Semi-Arid Savannas in Central Texas

NASA Astrophysics Data System (ADS)

Litvak, M.; Heilman, J.; McInnes, K.; Thijs, A.; Kjelgaard, J.

2007-12-01

Savannas in central Texas are dominated by live oak (Quercus virginiana) and Ashe juniper (Juniperus asheii) underlain by perennial, C3/C4 grasslands, and are increasingly becoming juniper and mesquite dominated due to overgrazing and suppression of wildfires. Since 2004, we have been investigating how carbon, water and energy exchange in these rain-limited savannas respond to rainfall variability and this observed vegetation change. In semi-arid regions, rainfall pulses provide inputs of soil moisture and trigger biotic activity in the form of plant gas exchange and microbial metabolism as well as water dependent physical processes in the soil. Each of these components has a different characteristic response curve to soil moisture and integrates soil water content over a different range of depths. Here we focus on examining how the observed increase of woody species in central Texas savannas alters the response of net ecosystem exchange and its components, ecosystem respiration and gross ecosystem exchange, to rain pulses. Using data we have collected over the last three years from three Ameriflux tower sites at Freeman Ranch near San Marcos, TX (C3/C4 grassland, juniper/mesquite savanna with 50 percent woody cover, and oak/juniper woodland), we quantify the responses of both ecosystem respiration and daily carbon uptake to rainfall pulses throughout the year. Specifically, we look at the enhancement and persistence of ecosystem respiration and carbon uptake responses following a pulse, and isolate the main controlling factors on the observed response: seasonality, antecedent soil moisture and temperature, or previous pulses. In all three land covers, the general response to precipitation pulses is a respiration pulse followed by an increase in total carbon uptake. Differences in pulse responses observed at the savanna site compared to the grassland and woodland sites can be explained, in part, by the observed differences in rooting structure and photosynthetic capacity due to differences in plant functional groups and leaf area index. The woodland site is most sensitive to winter pulses in terms of enhanced sink strength following pulses and is dependent on both temperature and pulse size. Both the grassland and shrubland sites show greater sink strength following summer pulses, rather than winter pulses. Both the ecosystem respiration and net uptake responses in all three sites are dependent upon whether there was shallow versus deep soil moisture recharge following pulses. Implications for the influence of future climate change on carbon dynamics in these savanna ecosystems will be discussed.

Dynamic analysis of temporal moisture profiles in heatset printing studied with near-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Tåg, C.-M.; Toiviainen, M.; Juuti, M.; Gane, P. A. C.

2010-10-01

Dynamic analysis of the water transfer onto coated paper, and its permeation and absorption into the porous structure were studied online in a full-scale heatset web offset printing environment. The moisture content of the paper was investigated at five different positions during the printing process. Changes in the moisture content of the paper were studied as a function of the web temperature, printing speed and silicone application in the folding unit positioned after the hot air drying oven. Additionally, the influence of fountain solution composition on the pick-up by the paper was investigated. The water content of the fountain solution transferred to the paper from the printing units was observed as changes in near-infrared absorbance. A calibration data set enabled the subsequent quantification of the dynamic moisture content of the paper at the studied locations. An increase in the printing speed reduced the water transfer to the paper and an increase in web temperature resulted in a reduction in the moisture content. An increase in the dosage level of the water-silicone mixture was observed as a re-moistening effect of the paper. Differences in the drying strategy resulted in different moisture profiles depending on the type of fountain solution used. As a conclusion, the near-infrared signal provides an effective way to characterize the moisture dynamics online at different press units.

Screening variability and change of soil moisture under wide-ranging climate conditions: Snow dynamics effects.

PubMed

Verrot, Lucile; Destouni, Georgia

2015-01-01

Soil moisture influences and is influenced by water, climate, and ecosystem conditions, affecting associated ecosystem services in the landscape. This paper couples snow storage-melting dynamics with an analytical modeling approach to screening basin-scale, long-term soil moisture variability and change in a changing climate. This coupling enables assessment of both spatial differences and temporal changes across a wide range of hydro-climatic conditions. Model application is exemplified for two major Swedish hydrological basins, Norrström and Piteälven. These are located along a steep temperature gradient and have experienced different hydro-climatic changes over the time period of study, 1950-2009. Spatially, average intra-annual variability of soil moisture differs considerably between the basins due to their temperature-related differences in snow dynamics. With regard to temporal change, the long-term average state and intra-annual variability of soil moisture have not changed much, while inter-annual variability has changed considerably in response to hydro-climatic changes experienced so far in each basin.

Influence of land-atmosphere feedbacks on temperature and precipitation extremes in the GLACE-CMIP5 ensemble

NASA Astrophysics Data System (ADS)

Lorenz, Ruth; Argüeso, Daniel; Donat, Markus G.; Pitman, Andrew J.; van den Hurk, Bart; Berg, Alexis; Lawrence, David M.; Chéruy, Frédérique; Ducharne, Agnès.; Hagemann, Stefan; Meier, Arndt; Milly, P. C. D.; Seneviratne, Sonia I.

2016-01-01

We examine how soil moisture variability and trends affect the simulation of temperature and precipitation extremes in six global climate models using the experimental protocol of the Global Land-Atmosphere Coupling Experiment of the Coupled Model Intercomparison Project, Phase 5 (GLACE-CMIP5). This protocol enables separate examinations of the influences of soil moisture variability and trends on the intensity, frequency, and duration of climate extremes by the end of the 21st century under a business-as-usual (Representative Concentration Pathway 8.5) emission scenario. Removing soil moisture variability significantly reduces temperature extremes over most continental surfaces, while wet precipitation extremes are enhanced in the tropics. Projected drying trends in soil moisture lead to increases in intensity, frequency, and duration of temperature extremes by the end of the 21st century. Wet precipitation extremes are decreased in the tropics with soil moisture trends in the simulations, while dry extremes are enhanced in some regions, in particular the Mediterranean and Australia. However, the ensemble results mask considerable differences in the soil moisture trends simulated by the six climate models. We find that the large differences between the models in soil moisture trends, which are related to an unknown combination of differences in atmospheric forcing (precipitation, net radiation), flux partitioning at the land surface, and how soil moisture is parameterized, imply considerable uncertainty in future changes in climate extremes.

A procedure for calculating daily moisture stress and its utility in regressions of growth and weather

Treesearch

Robert Zahner; Albert R. Stage

1966-01-01

A method is described for computing daily values of moisture stress on forest vegetation, or water deficits, based on the differences between Thornthwaite's potential evapotranspiration and computed soil-moisture depletion. More realistic functions are used for soil-moisture depletion on specific soil types than have been customary. These functions relate daily...

An inverse moisture diffusion algorithm for the determination of diffusion coefficient

Treesearch

Jen Y. Liu; William T. Simpson; Steve P. Verrill

2000-01-01

The finite difference approximation is applied to estimate the moisture-dependent diffusion coefficient by utilizing test data of isothermal moisture desorption in northern red oak (Quercus rubra). The test data contain moisture distributions at discrete locations across the thickness of specimens, which coincides with the radial direction of northern red oak, and at...

An inverse moisture diffusion algorithm for the determination of diffusion coefficient

Treesearch

Jen Y. Liu; William T. Simpson; Steve P. Verrill

2001-01-01

The finite difference approximation is applied to estimate the moisture-dependent diffusion coefficient by utilizing test data of isothermal moisture desorption in northern red oak (Quercus rubra). The test data contain moisture distributions at discrete locations across the thickness of specimens, which coincides with the radial direction of northern red oak, and at...

Use of modeled and satelite soil moisture to estimate soil erosion in central and southern Italy.

NASA Astrophysics Data System (ADS)

Termite, Loris Francesco; Massari, Christian; Todisco, Francesca; Brocca, Luca; Ferro, Vito; Bagarello, Vincenzo; Pampalone, Vincenzo; Wagner, Wolfgang

2016-04-01

This study presents an accurate comparison between two different approaches aimed to enhance accuracy of the Universal Soil Loss Equation (USLE) in estimating the soil loss at the single event time scale. Indeed it is well known that including the observed event runoff in the USLE improves its soil loss estimation ability at the event scale. In particular, the USLE-M and USLE-MM models use the observed runoff coefficient to correct the rainfall erosivity factor. In the first case, the soil loss is linearly dependent on rainfall erosivity, in the second case soil loss and erosivity are related by a power law. However, the measurement of the event runoff is not straightforward or, in some cases, possible. For this reason, the first approach used in this study is the use of Soil Moisture For Erosion (SM4E), a recent USLE-derived model in which the event runoff is replaced by the antecedent soil moisture. Three kinds of soil moisture datasets have been separately used: the ERA-Interim/Land reanalysis data of the European Centre for Medium-range Weather Forecasts (ECMWF); satellite retrievals from the European Space Agency - Climate Change Initiative (ESA-CCI); modeled data using a Soil Water Balance Model (SWBM). The second approach is the use of an estimated runoff rather than the observed. Specifically, the Simplified Continuous Rainfall-Runoff Model (SCRRM) is used to derive the runoff estimates. SCRMM requires soil moisture data as input and at this aim the same three soil moisture datasets used for the SM4E have been separately used. All the examined models have been calibrated and tested at the plot scale, using data from the experimental stations for the monitoring of the erosive processes "Masse" (Central Italy) and "Sparacia" (Southern Italy). Climatic data and runoff and soil loss measures at the event time scale are available for the period 2008-2013 at Masse and for the period 2002-2013 at Sparacia. The results show that both the approaches can provide better results than the USLE. Specifically, the SM4E model has proven to be particularly effective at Masse, providing the best soil loss estimations, especially when the modeled soil moisture is used. In this case, the RSR index (ratio between the Root Mean Square Error and the Observed Standard deviation) is equal to 0.94. Instead, the SCRRM is able to better estimate the event runoff at Sparacia than at Masse, thus resulting in good performances of the USLE-derived models using the estimated runoff; however, even at Sparacia the SM4E with modeled soil moisture gives the better soil loss estimates, with RSR = 0.54. These results open an interesting scenario in the use of empirical models to determine soil loss at a large scale, since soil moisture is a not only a simple in situ measurement, but only a widely available information on a global scale from remote sensing.

Effect of process variables on the quality attributes of briquettes from wheat, oat, canola and barley

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

Jaya Shankar Tumuluru

2011-08-01

Effect of process variables on the quality attributes of briquettes from wheat, oat, canola and barley straw Jaya Shankar Tumuluru*, L. G. Tabil, Y. Song, K. L. Iroba and V. Meda Biomass is a renewable energy source and environmentally friendly substitute for fossil fuels such as coal and petroleum products. Major limitation of biomass for successful energy application is its low bulk density, which makes it very difficult and costly to transport and handle. To overcome this limitation, biomass has to be densified. The commonly used technologies for densification of biomass are pelletization and briquetting. Briquetting offers many advantages atmore » it can densify larger particles sizes of biomass at higher moisture contents. Briquetting is influenced by a number of feedstock and process variables such as moisture content, particle size distribution, and some operating variables such as temperature and densification pressure. In the present study, experiments were designed and conducted based on Box-Behnken design to produce briquettes using barley, wheat, canola and barley straws. A laboratory scale hydraulic briquette press was used for the present study. The experimental process variables and their levels used in the present study were pressure levels (7.5, 10, 12.5 MPa), three levels of temperature (90, 110, 130 C), at three moisture content levels (9, 12, 15% w.b.), and three levels of particle size (19.1, 25.04, 31.75 mm). The quality variables studied includes moisture content, initial density and final briquette density after two weeks of storage, size distribution index and durability. The raw biomass was initially chopped and size reduced using a hammer mill. The ground biomass was conditioned at different moisture contents and was further densified using laboratory hydraulic press. For each treatment combination, ten briquettes were manufactured at a residence time of about 30 s after compression pressure setpoint was achieved. After compression, the initial dimensions and the final dimensions after 2 weeks of storage in controlled environment of all the samples were measured. Durability, dimensional stability, and moisture content tests were conducted after two weeks of storage of the briquettes produced. Initial results indicated that moisture content played a significant role on briquettes durability, stability, and density. Low moisture content of the straws (7-12%) gave more durable briquettes. Briquette density increased with increasing pressure depending on the moisture content value. The axial expansion was more significant than the lateral expansion, which in some cases tended to be nil depending on the material and operating variables. Further data analysis is in progress in order to understand the significance of the process variables based on ANOVA. Regression models were developed to predict the changes in quality of briquettes with respect of the process variables under study. Keywords: Herbaceous biomass, densification, briquettes, density, durability, dimensional stability, ANOVA and regression equations« less

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;

Inter-Comparison of SMAP, SMOS and GCOM-W Soil Moisture Products

NASA Astrophysics Data System (ADS)

Bindlish, R.; Jackson, T. J.; Chan, S.; Burgin, M. S.; Colliander, A.; Cosh, M. H.

2016-12-01

The Soil Moisture Active Passive (SMAP) mission was launched on Jan 31, 2015. The goal of the SMAP mission is to produce soil moisture with accuracy better than 0.04 m3/m3 with a revisit frequency of 2-3 days. The validated standard SMAP passive soil moisture product (L2SMP) with a spatial resolution of 36 km was released in May 2016. Soil moisture observations from in situ sensors are typically used to validate the satellite estimates. But, in situ observations provide ground truth for limited amount of landcover and climatic conditions. Although each mission will have its own issues, observations by other satellite instruments can be play a role in the calibration and validation of SMAP. SMAP, SMOS and GCOM-W missions share some commonnalities because they are currently providing operational brightness temperature and soil moisture products. SMAP and SMOS operate at L-band but GCOM-W uses X-band observations for soil moisture estimation. All these missions use different ancillary data sources, parameterization and algorithm to retrieve soil moisture. Therefore, it is important to validate and to compare the consistency of these products. Soil moisture products from the different missions will be compared with the in situ observations. SMAP soil moisture products will be inter-compared at global scales with SMOS and GCOM-W soil moisture products. The major contribution of satellite product inter-comparison is that it allows the assessment of the quality of the products over wider geographical and climate domains. Rigorous assessment will lead to a more reliable and accurate soil moisture product from all the missions.

Fuel moisture content estimation: a land-surface modelling approach applied to African savannas

NASA Astrophysics Data System (ADS)

Ghent, D.; Spessa, A.; Kaduk, J.; Balzter, H.

2009-04-01

Despite the importance of fire to the global climate system, in terms of emissions from biomass burning, ecosystem structure and function, and changes to surface albedo, current land-surface models do not adequately estimate key variables affecting fire ignition and propagation. Fuel moisture content (FMC) is considered one of the most important of these variables (Chuvieco et al., 2004). Biophysical models, with appropriate plant functional type parameterisations, are the most viable option to adequately predict FMC over continental scales at high temporal resolution. However, the complexity of plant-water interactions, and the variability associated with short-term climate changes, means it is one of the most difficult fire variables to quantify and predict. Our work attempts to resolve this issue using a combination of satellite data and biophysical modelling applied to Africa. The approach we take is to represent live FMC as a surface dryness index; expressed as the ratio between the Normalised Difference Vegetation Index (NDVI) and land-surface temperature (LST). It has been argued in previous studies (Sandholt et al., 2002; Snyder et al., 2006), that this ratio displays a statistically stronger correlation to FMC than either of the variables, considered separately. In this study, simulated FMC is constrained through the assimilation of remotely sensed LST and NDVI data into the land-surface model JULES (Joint-UK Land Environment Simulator). Previous modelling studies of fire activity in Africa savannas, such as Lehsten et al. (2008), have reported significant levels of uncertainty associated with the simulations. This uncertainty is important because African savannas are among some of the most frequently burnt ecosystems and are a major source of greenhouse trace gases and aerosol emissions (Scholes et al., 1996). Furthermore, regional climate model studies indicate that many parts of the African savannas will experience drier and warmer conditions in future (IPCC 2007). The simulation of realistic fire disturbance regimes with biophysical and biogeochemical models is a prerequisite for reducing the uncertainty of the African carbon cycle, and the feedbacks associated with this cycle and the global climate system. Using multi-temporal modelling analysis techniques, we present preliminary results that provide a more robust estimation of live FMC. References Chuvieco, E., Aguado, I. and Dimitrakopoulos, A. P. (2004) Conversion of fuel moisture content values to ignition potential for integrated fire danger assessment. Canadian Journal of Forest Research-Revue Canadienne De Recherche Forestiere 34(11): 2284-2293. IPCC (2007) 'Climate Change 2007: Synthesis Report. Contribution of Working Groups I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, Pachauri, R.K and Reisinger, A. (eds.)].' IPCC, (Geneva, Switzerland). Lehsten, V., Tansey, K. J., Balzter, H, Thonicke, K., Spessa, A., Weber, U., Smith, B., and Arneth, A. (2008). Estimating carbon emissions from African wildfires. Accepted Biogeosciences. Sandholt, I., Rasmussen, K. & Andersen, J. (2002) A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status. Remote Sensing of Environment 79(2-3): 213-224. Scholes, R. J., Ward, D. E. and Justice, C. O. (1996) Emissions of trace gases and aerosol particles due to vegetation burning in southern hemisphere Africa. Journal of Geophysical Research-Atmospheres 101(D19): 23677-23682. Snyder, R. L., Spano, D., Duce, P., Baldocchi, D., Xu, L. K. & Kyaw, T. P. U. (2006) A fuel dryness index for grassland fire-danger assessment. Agricultural and Forest Meteorology 139(1-2): 1-11.

Toxicity interaction between chlorpyrifos, mancozeb and soil moisture to the terrestrial isopod Porcellionides pruinosus.

PubMed

Morgado, Rui G; Gomes, Pedro A D; Ferreira, Nuno G C; Cardoso, Diogo N; Santos, Miguel J G; Soares, Amadeu M V M; Loureiro, Susana

2016-02-01

A main source of uncertainty currently associated with environmental risk assessment of chemicals is the poor understanding of the influence of environmental factors on the toxicity of xenobiotics. Aiming to reduce this uncertainty, here we evaluate the joint-effects of two pesticides (chlorpyrifos and mancozeb) on the terrestrial isopod Porcellionides pruinosus under different soil moisture regimes. A full factorial design, including three treatments of each pesticide and an untreated control, were performed under different soil moisture regimes: 25%, 50%, and 75% WHC. Our results showed that soil moisture had no effects on isopods survival, at the levels assessed in this experiment, neither regarding single pesticides nor mixture treatments. Additivity was always the most parsimonious result when both pesticides were present. Oppositely, both feeding activity and biomass change showed a higher sensitivity to soil moisture, with isopods generally showing worse performance when exposed to pesticides and dry or moist conditions. Most of the significant differences between soil moisture regimes were found in single pesticide treatments, yet different responses to mixtures could still be distinguished depending on the soil moisture assessed. This study shows that while soil moisture has the potential to influence the effects of the pesticide mixture itself, such effects might become less important in a context of complex combinations of stressors, as the major contribution comes from its individual interaction with each pesticide. Finally, the implications of our results are discussed in light of the current state of environmental risk assessment procedures and some future perspectives are advanced. Copyright © 2015 Elsevier Ltd. All rights reserved.

Design, development and method validation of a novel multi-resonance microwave sensor for moisture measurement.

PubMed

Peters, Johanna; Taute, Wolfgang; Bartscher, Kathrin; Döscher, Claas; Höft, Michael; Knöchel, Reinhard; Breitkreutz, Jörg

2017-04-08

Microwave sensor systems using resonance technology at a single resonance in the range of 2-3 GHz have been shown to be a rapid and reliable tool for moisture determination in solid materials including pharmaceutical granules. So far, their application is limited to lower moisture ranges or limitations above certain moisture contents had to be accepted. Aim of the present study was to develop a novel multi-resonance sensor system in order to expand the measurement range. Therefore, a novel sensor using additional resonances over a wide frequency band was designed and used to investigate inherent limitations of first generation sensor systems and material-related limits. Using granule samples with different moisture contents, an experimental protocol for calibration and validation of the method was established. Pursuant to this protocol, a multiple linear regression (MLR) prediction model built by correlating microwave moisture values to the moisture determined by Karl Fischer titration was chosen and rated using conventional criteria such as coefficient of determination (R 2 ) and root mean square error of calibration (RMSEC). Using different operators, different analysis dates and different ambient conditions the method was fully validated following the guidance of ICH Q2(R1). The study clearly showed explanations for measurement uncertainties of first generation sensor systems which confirmed the approach to overcome these by using additional resonances. The established prediction model could be validated in the range of 7.6-19.6%, demonstrating its fit for its future purpose, the moisture content determination during wet granulations. Copyright © 2017 Elsevier B.V. All rights reserved.

Root Water Uptake and Soil Moisture Pattern Dynamics - Capturing Connections, Controls and Causalities

NASA Astrophysics Data System (ADS)

Blume, T.; Heidbuechel, I.; Hassler, S. K.; Simard, S.; Guntner, A.; Stewart, R. D.; Weiler, M.

2015-12-01

We hypothesize that there is a shift in controls on landscape scale soil moisture patterns when plants become active during the growing season. Especially during the summer soil moisture patterns are not only controlled by soils, topography and related abiotic site characteristics but also by root water uptake. Root water uptake influences soil moisture patterns both in the lateral and vertical direction. Plant water uptake from different soil depths is estimated based on diurnal fluctuations in soil moisture content and was investigated with a unique setup of 46 field sites in Luxemburg and 15 field sites in Germany. These sites cover a range of geologies, soils, topographic positions and types of vegetation. Vegetation types include pasture, pine forest (young and old) and different deciduous forest stands. Available data at all sites includes information at high temporal resolution from 3-5 soil moisture and soil temperature profiles, matrix potential, piezometers and sapflow sensors as well as standard climate data. At sites with access to a stream, discharge or water level is also recorded. The analysis of soil moisture patterns over time indicates a shift in regime depending on season. Depth profiles of root water uptake show strong differences between different forest stands, with maximum depths ranging between 50 and 200 cm. Temporal dynamics of signal strength within the profile furthermore suggest a locally shifting spatial distribution of root water uptake depending on water availability. We will investigate temporal thresholds (under which conditions spatial patterns of root water uptake become most distinct) as well as landscape controls on soil moisture and root water uptake dynamics.

Moisturizers for Acne

PubMed Central

Chularojanamontri, Leena; Tuchinda, Papapit; Kulthanan, Kanokvalai

2014-01-01

Acne is a chronic inflammatory disease of the pilosebaceous unit that affects almost all teenagers. Different treatments offer different modes of action, but aim to target acne pathology. Topical therapies, such as benzoyl peroxide, retinoids, antibiotics with alcohol-based preparations, and salicylic acid, can cause skin irritation resulting in a lack of patient adherence. Some physicians recommend patients use moisturizers as adjunctive treatment of acne, especially when either topical benzoyl peroxide or a retinoid is prescribed. Furthermore, some evidence shows that moisturizers can contribute independently to improve signs and symptoms of acne. Moisturizers contain three main properties, which are occlusive, humectant, and emollient effects. Currently, many moisturizers claim to be suitable for acne treatment. This article aims to provide a review of the active ingredients and properties of those moisturizers. Fifty-two moisturizers for acne were included for analysis. Most of the products (92%) have anti-inflammatory properties apart from occlusive, humectant, and emollient effects. Anti-acne medications, including salicylic acid, benzoyl peroxide, and retinol, were found respectively in 35, 10, and 8 percent of the moisturizer products containing anti-inflammatory properties. More than half of the products contain dimethicone and/or glycerin for its moisturizer property. Aloe vera and witch hazel are botanical anti-inflammatories that were commonly found in this study. Scientific data regarding some ingredients are discussed to provide a guide for physicians in selecting moisturizers for acne patients. PMID:24847408

An evaluation of various forms of VAS retrievals in the analysis of a preconvective environment

NASA Technical Reports Server (NTRS)

Petersen, R. A.; Keyser, D. A.

1987-01-01

VISSR Atmospheric Sounder (VAS) radiance data obtained over the continental United States on July 20, 1981 are used to evaluate a variety of VAS retrieval procedures and parameters in the qualitative analysis and forecasting of severe weather events. The particular case analyzed contains two significantly different mesoscale convective events in the central plains. Retrievals of temperature, dewpoint temperature, equivalent potential temperature, total column precipitable water, and lifted index are shown to be physically consistent in space and time and to compare well with available radiosonde data. The analysis of the VAS retrievals identified significant spatial gradients and temporal changes in the thermal and moisture fields, including times and locations between radiosonde observations.

Land-atmosphere coupling and soil moisture memory contribute to long-term agricultural drought

NASA Astrophysics Data System (ADS)

Kumar, S.; Newman, M.; Lawrence, D. M.; Livneh, B.; Lombardozzi, D. L.

2017-12-01

We assessed the contribution of land-atmosphere coupling and soil moisture memory on long-term agricultural droughts in the US. We performed an ensemble of climate model simulations to study soil moisture dynamics under two atmospheric forcing scenarios: active and muted land-atmosphere coupling. Land-atmosphere coupling contributes to a 12% increase and 36% decrease in the decorrelation time scale of soil moisture anomalies in the US Great Plains and the Southwest, respectively. These differences in soil moisture memory affect the length and severity of modeled drought. Consequently, long-term droughts are 10% longer and 3% more severe in the Great Plains, and 15% shorter and 21% less severe in the Southwest. An analysis of Coupled Model Intercomparsion Project phase 5 data shows four fold uncertainty in soil moisture memory across models that strongly affects simulated long-term droughts and is potentially attributable to the differences in soil water storage capacity across models.

Moisture sorption by cellulose powders of varying crystallinity.

PubMed

Mihranyan, Albert; Llagostera, Assumpcio Piñas; Karmhag, Richard; Strømme, Maria; Ek, Ragnar

2004-01-28

Moisture in microcrystalline cellulose may cause stability problems for moisture sensitive drugs. The aim of this study was to investigate the influence of crystallinity and surface area on the uptake of moisture in cellulose powders. Powders of varying crystallinity were manufactured, and the uptake of moisture was investigated at different relative humidities. The structure of the cellulose powders was characterized by X-ray diffraction, BET surface area analysis, and scanning electron microscopy. Moisture uptake was directly related to the cellulose crystallinity and pore volume: Cellulose powders with higher crystallinity showed lower moisture uptake at relative humidities below 75%, while at higher humidities the moisture uptake could be associated with filling of the large pore volume of the cellulose powder of highest crystallinity. In conclusion, the structure of cellulose should be thoroughly considered when manufacturing low moisture grades of MCC.

Atherogenicity index and health-related fatty acids in different stages of lactation from Friesian, Jersey and Friesian×Jersey cross cow milk under a pasture-based dairy system.

PubMed

Nantapo, C T W; Muchenje, V; Hugo, A

2014-03-01

The objective of the study was to investigate the effect of stage of lactation on the fatty acid profiles of milk from Friesian, Jersey and Friesian×Jersey cows. Linoleic acid in pastures was highest in the second phase which coincided with mid-lactation days (p<0.05). Highest milk moisture content and lowest fat free dry matter content was seen in early lactation (p<0.05). Higher fat content was observed in late lactation than early lactation. Highest butyric, caproic, linoleic, omega-6 and polyunsaturated fatty acids were observed for milk from Friesian cows. Highest conjugated fatty acids, α-linolenic acid, linoleic acid, saturated fatty acids, polyunsaturated fatty acids, omega-6, and omega-3 were observed in early lactation. Atherogenicity index and desaturase activity indices were highest in late lactation. In conclusion, stage of lactation and genotype affected milk health-related fatty acid profiles. Copyright © 2013 Elsevier Ltd. All rights reserved.

Low-Temperature Plasma-Assisted Atomic Layer Deposition of Silicon Nitride Moisture Permeation Barrier Layers.

PubMed

Andringa, Anne-Marije; Perrotta, Alberto; de Peuter, Koen; Knoops, Harm C M; Kessels, Wilhelmus M M; Creatore, Mariadriana

2015-10-14

Encapsulation of organic (opto-)electronic devices, such as organic light-emitting diodes (OLEDs), photovoltaic cells, and field-effect transistors, is required to minimize device degradation induced by moisture and oxygen ingress. SiNx moisture permeation barriers have been fabricated using a very recently developed low-temperature plasma-assisted atomic layer deposition (ALD) approach, consisting of half-reactions of the substrate with the precursor SiH2(NH(t)Bu)2 and with N2-fed plasma. The deposited films have been characterized in terms of their refractive index and chemical composition by spectroscopic ellipsometry (SE), X-ray photoelectron spectroscopy (XPS), and Fourier-transform infrared spectroscopy (FTIR). The SiNx thin-film refractive index ranges from 1.80 to 1.90 for films deposited at 80 °C up to 200 °C, respectively, and the C, O, and H impurity levels decrease when the deposition temperature increases. The relative open porosity content of the layers has been studied by means of multisolvent ellipsometric porosimetry (EP), adopting three solvents with different kinetic diameters: water (∼0.3 nm), ethanol (∼0.4 nm), and toluene (∼0.6 nm). Irrespective of the deposition temperature, and hence the impurity content in the SiNx films, no uptake of any adsorptive has been observed, pointing to the absence of open pores larger than 0.3 nm in diameter. Instead, multilayer development has been observed, leading to type II isotherms that, according to the IUPAC classification, are characteristic of nonporous layers. The calcium test has been performed in a climate chamber at 20 °C and 50% relative humidity to determine the intrinsic water vapor transmission rate (WVTR) of SiNx barriers deposited at 120 °C. Intrinsic WVTR values in the range of 10(-6) g/m2/day indicate excellent barrier properties for ALD SiNx layers as thin as 10 nm, competing with that of state-of-the-art plasma-enhanced chemical vapor-deposited SiNx layers of a few hundred nanometers in thickness.

Canopy openness, understory light environments, and oak regeneration

Treesearch

Brian C. McCarthy; Scott A. Robison

2003-01-01

Understory light environments were evaluated in four mixed-oak forests in southern Ohio using hemispherical photography. Within each forest, plots were divided into nine treatment combinations based on three pretreatment fire categories and three Integrated Moisture Index (IMI) categories. For each of 108 photographs we determined the percentage of open sky, direct...

Predicting redwood productivity using biophysical data, spatial statistics and site quality indices

Treesearch

John-Pascal Berrill; Kevin L. O’Hara; Shawn Headley

2017-01-01

Coast redwood (Sequoia sempervirens (D. Don) Endl.) height growth and basal area growth are sensitive to variations in site quality. Site factors known to be correlated with redwood stand growth and yield include topographic variables such as position on slope, exposure, and the composite variable: topographic relative moisture index. Species...

Topography-mediated controls on local vegetation phenology estimated from MODIS vegetation index

Treesearch

Taehee Hwang; Conghe Song; James Vose; Lawrence Band

2011-01-01

Forest canopy phenology is an important constraint on annual water and carbon budgets, and responds to regional interannual climate variation. In steep terrain, there are complex spatial variations in phenology due to topographic influences on microclimate, community composition, and available soil moisture. In this study, we investigate spatial patterns of phenology...

Predicting Southern Appalachian overstory vegetation with digital terrain data

Treesearch

Paul V. Bolstad; Wayne Swank; James Vose

1998-01-01

Vegetation in mountainous regions responds to small-scale variation in terrain, largely due to effects on both temperature and soil moisture. However, there are few studies of quantitative, terrain-based methods for predicting vegetation composition. This study investigated relationships between forest composition, elevation, and a derived index of terrain shape, and...

A method for ensemble wildland fire simulation

Treesearch

Mark A. Finney; Isaac C. Grenfell; Charles W. McHugh; Robert C. Seli; Diane Trethewey; Richard D. Stratton; Stuart Brittain

2011-01-01

An ensemble simulation system that accounts for uncertainty in long-range weather conditions and two-dimensional wildland fire spread is described. Fuel moisture is expressed based on the energy release component, a US fire danger rating index, and its variation throughout the fire season is modeled using time series analysis of historical weather data. This analysis...

Prediction of villages at risk for filariasis transmission in the Nile Delta using remote sensing and geographic information system technologies.

PubMed

Hassan, A N; Beck, L R; Dister, S

1998-04-01

Remote sensing and geographic information system (GIS) technologies were used to discriminate between 130 villages, in the Nile Delta, at high and low risk for filariasis, as defined by microfilarial prevalence. Landsat Thematic Mapper (TM) data were digitally processed to generate a map of landcover as well as spectral indices such as NDVI and moisture index. A Tasseled Cap transformation was also carried out on the TM data which produced three more indices: brightness, greenness and wetness. GIS functions were used to extract information on landcover and spectral indices within one km buffers around the study villages. The relationship between satellite data and prevalence was investigated using discriminant analysis. The analysis indicated that the most important landscape elements associated with prevalence were water and marginal vegetation, while wetness and moisture index were the most important indices. Discriminant functions generated for these variables were able to correctly predict 80% and 74% of high and low prevalence villages, respectively, with an overall accuracy of 77%. The present approach provides a promising tool for regional filariasis surveillance and helps direct control efforts.

Effects of different storage time on hatching results and some egg quality characteristics of rock partridge (A. graeca) (management and production).

PubMed

Günhan, S; Kirikçi, K

2017-06-01

In this research, partridge eggs were stored during zero to 7, 8 to 14, 15 to 21, 22 to 28, 29 to 35 and 36 to 42 d, respectively. The effect of different egg storage periods on egg protein and moisture rates, mineral contents, and some egg quality and hatching characteristics were investigated. The extension of egg storage times didn't affect the external quality features like shell weight, shell thickness, and albumen rate, but it affected the yolk weight, yolk index, albumen index, and Haugh unit (P < 0.05). Yolk weight was increased and yolk index, albumen index, and Haugh unit values were decreased with the extension of storage time. Different storage times of partridge eggs did not have important effects on the protein rates. Protein and humidity rate of the eggs were 14.21 and 67.64%, respectively. There were some elements such as S, P, Na, K, and Ca, but Al, Cd, Co, Mo, and Pb could not be found in the partridge eggs. There is no effect of the storage time on the mineral content of the egg. Storage time had negative effect on fertility and hatchability after 21 d of storage d, but no effect on hatchability of fertile eggs. As this study showed, partridge eggs are resistant to long storage times, as partridge egg proteins can resist degradation in the optimum storage times. To determine egg degradation, the study should be focused on partridge eggshell features, which are responsible for degradation. As a result of this research, partridge eggs can be stored for 21 d under optimum storage conditions without any negative hatchability results. © 2017 Poultry Science Association Inc.

Correlation between ERMI values and other Moisture and Mold Assessments of Homes in the American Healthy Home Survey

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

Vesper, Sephen J.; McKinstry, Craig A.; Cox, David J.

2009-11-30

Objective: The objective of this study was to determine the correlation between ERMI values in the HUD American Healthy Home Survey (AHHS) homes and either inspector reports or occupant assessments of mold and moisture. Methods: In the AHHS, moisture and mold were assessed by a pair of inspectors and with an occupant questionnaire. These results were compared to the results of the Environmental Relative Moldiness Index (ERMI) values for each home. Results: Homes in the highest ERMI quartile were most often in agreement with visual inspection and/or occupant assessment. However, in 52% of the fourth quartile ERMI homes, the inspectormore » and occupant assessment did not indicate water or mold problems. Yet the concentrations of each ERMI panel mold species detected in all fourth quartile homes were statistically indistinguishable. Conclusions: About 50% of water-damaged, moldy homes were not detected by inspection or questioning of the occupant about water and mold.« less

Global Analysis of Empirical Relationships Between Annual Climate and Seasonality of NDVI

NASA Technical Reports Server (NTRS)

Potter, C. S.; Brooks, V.

1997-01-01

This paper describes the use of satellite data to calibrate a new climate-vegetation greenness relationship for global change studies. We examined statistical relationships between annual climate indexes (temperature, precipitation, and surface radiation) and seasonal attributes If the AVHRR Normalized Difference Vegetation Index (NDVI) time series for the mid-1980's in order to refine our understanding of intra-annual patterns and global abiotic controls on natural vegetation dynamics. Multiple linear regression results using global 1o gridded data sets suggest that three climate indexes: degree days (growing/chilling), annual precipitation total, and an annual moisture index together can account to 70-80 percent of the geographic variation in the NDVI seasonal extremes (maximum and minimum values) for the calibration year 1984. Inclusion of the same annual climate index values from the previous year explains no substantial additional portion of the global scale variation in NDVI seasonal extremes. The monthly timing of NDVI extremes is closely associated with seasonal patterns in maximum and minimum temperature and rainfall, with lag times of 1 to 2 months. We separated well-drained areas from lo grid cells mapped as greater than 25 percent inundated coverage for estimation of both the magnitude and timing of seasonal NDVI maximum values. Predicted monthly NDVI, derived from our climate-based regression equations and Fourier smoothing algorithms, shows good agreement with observed NDVI for several different years at a series of ecosystem test locations from around the globe. Regions in which NDVI seasonal extremes are not accurately predicted are mainly high latitude zones, mixed and disturbed vegetation types, and other remote locations where climate station data are sparse.

Searching regional rainfall homogeneity using atmospheric fields

NASA Astrophysics Data System (ADS)

Gabriele, Salvatore; Chiaravalloti, Francesco

2013-03-01

The correct identification of homogeneous areas in regional rainfall frequency analysis is fundamental to ensure the best selection of the probability distribution and the regional model which produce low bias and low root mean square error of quantiles estimation. In an attempt at rainfall spatial homogeneity, the paper explores a new approach that is based on meteo-climatic information. The results are verified ex-post using standard homogeneity tests applied to the annual maximum daily rainfall series. The first step of the proposed procedure selects two different types of homogeneous large regions: convective macro-regions, which contain high values of the Convective Available Potential Energy index, normally associated with convective rainfall events, and stratiform macro-regions, which are characterized by low values of the Q vector Divergence index, associated with dynamic instability and stratiform precipitation. These macro-regions are identified using Hot Spot Analysis to emphasize clusters of extreme values of the indexes. In the second step, inside each identified macro-region, homogeneous sub-regions are found using kriging interpolation on the mean direction of the Vertically Integrated Moisture Flux. To check the proposed procedure, two detailed examples of homogeneous sub-regions are examined.

Understanding the bias between moisture content by oven drying and water content by Karl Fischer titration at moisture equilibrium

USDA-ARS?s Scientific Manuscript database

Multiple causes of the difference between equilibrium moisture and water content have been found. The errors or biases were traced to the oven drying procedure to determine moisture content. The present paper explains the nature of the biases in oven drying and how it is possible to suppress one ...

A comparison of two methods for estimating conifer live foliar moisture content

Treesearch

W. Matt Jolly; Ann M. Hadlow

2012-01-01

Foliar moisture content is an important factor regulating how wildland fires ignite in and spread through live fuels but moisture content determination methods are rarely standardised between studies. One such difference lies between the uses of rapid moisture analysers or drying ovens. Both of these methods are commonly used in live fuel research but they have never...

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...

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.

Can we quantify the variability of soil moisture across scales using Electromagnetic Induction ?

NASA Astrophysics Data System (ADS)

Robinet, Jérémy; von Hebel, Christian; van der Kruk, Jan; Govers, Gerard; Vanderborght, Jan

2017-04-01

Soil moisture is a key variable in many natural processes. Therefore, technological and methodological advancements are of primary importance to provide accurate measurements of spatial and temporal variability of soil moisture. In that context, ElectroMagnetic Induction (EMI) instruments are often cited as a hydrogeophysical method with a large potential, through the measurement of the soil apparent electrical conductivity (ECa). To our knowledge, no studies have evaluated the potential of EMI to characterize variability of soil moisture on both agricultural and forested land covers in a (sub-) tropical environment. These differences in land use could be critical as differences in temperature, transpiration and root water uptake can have significant effect, notably on the electrical conductivity of the pore water. In this study, we used an EMI instrument to carry out a first assessment of the impact of deforestation and agriculture on soil moisture in a subtropical region in the south of Brazil. We selected slopes of different topographies (gentle vs. steep) and contrasting land uses (natural forest vs. agriculture) within two nearby catchments. At selected locations on the slopes, we measured simultaneously ECa using EMI and a depth-weighted average of the soil moisture using TDR probes installed within soil pits. We found that the temporal variability of the soil moisture could not be measured accurately with EMI, probably because of important temporal variations of the pore water electrical conductivity and the relatively small temporal variations in soil moisture content. However, we found that its spatial variability could be effectively quantified using a non-linear relationship, for both intra- and inter-slopes variations. Within slopes, the ECa could explained between 67 and 90% of the variability of the soil moisture, while a single non-linear model for all the slopes could explain 55% of the soil moisture variability. We eventually showed that combining a specific relationship for the most degraded slope (steep slope under agriculture) and a single relationship for all the other slopes, both non-linear relations, yielded the best results with an overall explained variance of 90%. We applied the latter model to measurements of the ECa along transects at the different slopes, which allowed us to highlight the strong control of topography on the soil moisture content. We also observed a significant impact of the land use with higher moisture content on the agricultural slopes, probably due to a reduced evapotranspiration.