Mechanisms of deterioration of intermediate moisture food systems
NASA Technical Reports Server (NTRS)
Labuza, T. P.
1972-01-01
A study of shelf stability in intermediate moisture foods was made. Major efforts were made to control lipid oxidation and nonenzymatic browning. In order to determine means of preventing these reactions, model systems were developed having the same water activity content relationship of intermediate moisture foods. Models were based on a cellulose-lipid and protein-lipid system with glycerol added as the humectant. Experiments with both systems indicate that lipid oxidation is promoted significantly in the intermediate moisture range. The effect appeared to be related to increased mobility of either reactants or catalysts, since when the amount of water in the system reached a level where capillary condensation occurred and thus free water was present, the rates of oxidation increased. With added glycerol, which is water soluble and thus increases the amount of mobile phase, the increase in oxidation rate occurs at a lower relative humidity. The rates of oxidation were maximized at 61% RH and decreased again at 75% RH probably due to dilution. No significant non-enzymatic browning occurred in the protein-lipid systems. Prevention of oxidation by the use of metal chelating agents was enhanced in the cellulose system, whereas, with protein present, the lipid soluble chain terminating antioxidants (such as BHA) worked equally as well. Preliminary studies of foods adjusted to the intermediate moisture range bear out the results of oxidation in model systems. It can be concluded that for most fat containing intermediate moisture foods, rancidity will be the reaction most limiting stability.
Storage stability and improvement of intermediate moisture foods
NASA Technical Reports Server (NTRS)
Labuza, T. P.
1973-01-01
The rates of chemical reactions which deteriorate foods prepared to an intermediate moisture content and water activity (A sub w 0.6 to 0.9) were studied. The phenomenon of sorption hysteresis was used to prepare model systems and foods to similar A sub w's but different moisture levels so that the separate effects of water binding and water content could be elucidated. It was found that water content is the controlling factor for lipid oxidation in model systems comprised of a solid support and an oxidizable liquid. It was proposed that metal chelating agents like EDTA should give good protection to oxidation. EDTA exhibited the highest efficacy, about 10-15 times better than BHA which is a radical scavenger when studied in the model systems.
Ambebe, Titus F; Dang, Qing-Lai
2009-11-01
White birch (Betula papyrifera Marsh.) seedlings were grown under two carbon dioxide concentrations (ambient: 360 micromol mol(-1) and elevated: 720 micromol mol(-1)), three soil temperatures (5, 15 and 25 degrees C initially, increased to 7, 17 and 27 degrees C, respectively, 1 month later) and three moisture regimes (low: 30-40%; intermediate: 45-55% and high: 60-70% field water capacity) in greenhouses. In situ gas exchange and chlorophyll fluorescence were measured after 2 months of treatments. Net photosynthetic rate (A(n)) of seedlings grown under the intermediate and high moisture regimes increased from low to intermediate T(soil) and then decreased to high T(soil). There were no significant differences between the low and high T(soil), with the exception that A(n) was significantly higher under high than low T(soil) at the high moisture regime. No significant T(soil) effect on A(n) was observed at the low moisture regime. The intermediate T(soil) increased stomatal conductance (g(s)) only at intermediate and high but not at low moisture regime, whereas there were no significant differences between the low and high T(soil) treatments. Furthermore, the difference in g(s) between the intermediate and high T(soil) at high moisture regime was not statistically significant. The low moisture regime significantly reduced the internal to ambient CO2 concentration ratio at all T(soil). There were no significant individual or interactive effects of treatment on maximum carboxylation rate of Rubisco, light-saturated electron transport rate, triose phosphate utilization or potential photochemical efficiency of photosystem II. The results of this study suggest that soil moisture condition should be taken into account when predicting the responses of white birch to soil warming.
Pan, Hongyang; Jiang, Bo; Chen, Jie; Jin, Zhengyu
2014-11-04
Multi-component substances made through direct blending or blending with co-drying can form films on the surfaces of intermediate moisture foods (IMFs), which help retain moisture and protect food texture and flavor. An IMF film system based on pullulan, with glycerol serving as the plasticizer, was studied using alginate and four different types of polysaccharides (propyleneglycol alginate, pectin, carrageenan, and aloe polysaccharide) as the blend-modified substances. The physical, mechanical, color, transparency, and moisture-retention properties of the co-blended films with the polysaccharides were assessed. A new formula was established for the average moisture retention property, water barrier, tensile strength, elongation at break, and oxygen barrier property of the ternary co-blended films using the Design Expert software. The new model established for moisture content measurement used an indirect method of film formation on food surfaces by humectants, which should expedite model validation and allow a better comprehension of moisture transfer through edible films. Copyright © 2014 Elsevier Ltd. All rights reserved.
The deterioration of intermediate moisture foods
NASA Technical Reports Server (NTRS)
Labruza, T. P.
1971-01-01
Deteriorative reactions are low and food quality high if intermediate moisture content of a food is held at a water activity of 0.6 to 0.75. Information is of interest to food processing and packaging industry.
Control of nonenzymatic browning in intermediate-moisture foods
NASA Technical Reports Server (NTRS)
Buckle, K. A.; Labruza, T. P.; Warmbier, H. C.
1975-01-01
Series of compounds called humectants were found to decrease rate of browning when added to intermediate-moisture foods. Twenty percent level of humectant can increase shelf life of foods by factor of 5 or 6.
Continuous data assimilation for downscaling large-footprint soil moisture retrievals
NASA Astrophysics Data System (ADS)
Altaf, Muhammad U.; Jana, Raghavendra B.; Hoteit, Ibrahim; McCabe, Matthew F.
2016-10-01
Soil moisture is a key component of the hydrologic cycle, influencing processes leading to runoff generation, infiltration and groundwater recharge, evaporation and transpiration. Generally, the measurement scale for soil moisture is found to be different from the modeling scales for these processes. Reducing this mismatch between observation and model scales in necessary for improved hydrological modeling. An innovative approach to downscaling coarse resolution soil moisture data by combining continuous data assimilation and physically based modeling is presented. In this approach, we exploit the features of Continuous Data Assimilation (CDA) which was initially designed for general dissipative dynamical systems and later tested numerically on the incompressible Navier-Stokes equation, and the Benard equation. A nudging term, estimated as the misfit between interpolants of the assimilated coarse grid measurements and the fine grid model solution, is added to the model equations to constrain the model's large scale variability by available measurements. Soil moisture fields generated at a fine resolution by a physically-based vadose zone model (HYDRUS) are subjected to data assimilation conditioned upon coarse resolution observations. This enables nudging of the model outputs towards values that honor the coarse resolution dynamics while still being generated at the fine scale. Results show that the approach is feasible to generate fine scale soil moisture fields across large extents, based on coarse scale observations. Application of this approach is likely in generating fine and intermediate resolution soil moisture fields conditioned on the radiometerbased, coarse resolution products from remote sensing satellites.
Lavelli, Vera; Corey, Mark; Kerr, William; Vantaggi, Claudia
2011-07-15
Intermediate moisture products made from blanched apple flesh and green tea extract (about 6mg of monomeric flavan 3-ols added per g of dry apple) or blanched apple flesh (control) were produced, and their quality attributes were investigated over storage for two months at water activity (a(w)) levels of 0.55 and 0.75, at 30°C. Products were evaluated for colour (L(∗), a(∗), and b(∗) Hunter's parameters), phytochemical contents (flavan 3-ols, chlorogenic acid, dihydrochalcones, ascorbic acid and total polyphenols), ferric reducing antioxidant potential, 2,2-diphenyl-1-(2,4,6-trinitrophenyl)hydrazyl radical-scavenging activity and ability to inhibit formation of fructose-induced advanced glycation end-products. During storage of the fortified and unfortified intermediate moisture apples, water availability was sufficient to support various chemical reactions involving phytochemicals, which degraded at different rates: ascorbic acid>flavan 3-ols>dihydrochalcones and chlorogenic acid. Colour variations occurred at slightly slower rates after green tea addition. In the intermediate moisture apple, antioxidant and anti-glycoxidative properties decreased at similar rates (half-life was about 80d at a(w) of 0.75, 30°C). In the green tea-fortified intermediate moisture apple, the antioxidant activity decreased at a slow rate (half-life was 165d at a(w) of 0.75, 30°C) and the anti-glycoxidative properties did not change, indicating that flavan 3-ol degradation involved the formation of derivatives that retained the properties of their parent compounds. Since these properties are linked to oxidative- and advanced glycation end-product-related diseases, these results suggest that green tea fortification of intermediate moisture apple products could be a valuable means of product innovation, to address consumers' nutritional needs. Copyright © 2011 Elsevier Ltd. All rights reserved.
Validation of soil moisture ocean salinity (SMOS) satellite soil moisture products
USDA-ARS?s Scientific Manuscript database
The surface soil moisture state controls the partitioning of precipitation into infiltration and runoff. High-resolution observations of soil moisture will lead to improved flood forecasts, especially for intermediate to large watersheds where most flood damage occurs. Soil moisture is also key in d...
Huang, Yang; Wilson, Mark; Chapman, Belinda; Hocking, Ailsa D
2010-02-01
The potential efficacy of four weak acids as preservatives in low-acid intermediate moisture foods was assessed using a glycerol based agar medium. The minimum inhibitory concentrations (MIC, % wt./wt.) of each acid was determined at two pH values (pH 5.0, pH 6.0) and two a(w) values (0.85, 0.90) for five food spoilage fungi, Eurotium herbariorum, Eurotium rubrum, Aspergillus niger, Aspergillus flavus and Penicillium roqueforti. Sorbic acid, a preservative commonly used to control fungal growth in low-acid intermediate moisture foods, was included as a reference. The MIC values of the four acids were lower at pH 5.0 than pH 6.0 at equivalent a(w) values, and lower at 0.85 a(w) than 0.90 a(w) at equivalent pH values. By comparison with the MIC values of sorbic acid, those of caprylic acid and dehydroacetic acid were generally lower, whereas those for caproic acid were generally higher. No general observation could be made in the case of capric acid. The antifungal activities of all five weak acids appeared related not only to the undissociated form, but also the dissociated form, of each acid.
Optimization of the secondary drying step in freeze drying using TDLAS technology.
Schneid, Stefan C; Gieseler, Henning; Kessler, William J; Luthra, Suman A; Pikal, Michael J
2011-03-01
The secondary drying phase in freeze drying is mostly developed on a trial-and-error basis due to the lack of appropriate noninvasive process analyzers. This study describes for the first time the application of Tunable Diode Laser Absorption Spectroscopy, a spectroscopic and noninvasive sensor for monitoring secondary drying in laboratory-scale freeze drying with the overall purpose of targeting intermediate moisture contents in the product. Bovine serum albumin/sucrose mixtures were used as a model system to imitate high concentrated antibody formulations. First, the rate of water desorption during secondary drying at constant product temperatures (-22 °C, -10 °C, and 0 °C) was investigated for three different shelf temperatures. Residual moisture contents of sampled vials were determined by Karl Fischer titration. An equilibration step was implemented to ensure homogeneous distribution of moisture (within 1%) in all vials. The residual moisture revealed a linear relationship to the water desorption rate for different temperatures, allowing the evaluation of an anchor point from noninvasive flow rate measurements without removal of samples from the freeze dryer. The accuracy of mass flow integration from this anchor point was found to be about 0.5%. In a second step, the concept was successfully tested in a confirmation experiment. Here, good agreement was found for the initial moisture content (anchor point) and the subsequent monitoring and targeting of intermediate moisture contents. The present approach for monitoring secondary drying indicated great potential to find wider application in sterile operations on production scale in pharmaceutical freeze drying. © 2011 American Association of Pharmaceutical Scientists
Winds and Weather, Teacher's Edition. Probing the Natural World/3.
ERIC Educational Resources Information Center
Florida State Univ., Tallahassee. Dept. of Science Education.
The teacher's edtion for the Intermediate Science Curriculum Study Level III unit entitled "Winds and Weather" provides instructions for teachers for examining some principles underlying thermal convention, weather observation, closed systems, moisture and cloud formation, the heated-air model, and fronts. A brief introduction dealing…
NASA Astrophysics Data System (ADS)
Wiß, Felix; Stacke, Tobias; Hagemann, Stefan
2014-05-01
Soil moisture and its memory can have a strong impact on near surface temperature and precipitation and have the potential to promote severe heat waves, dry spells and floods. To analyze how soil moisture is simulated in recent general circulation models (GCMs), soil moisture data from a 23 model ensemble of Atmospheric Model Intercomparison Project (AMIP) type simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) are examined for the period 1979 to 2008 with regard to parameterization and statistical characteristics. With respect to soil moisture processes, the models vary in their maximum soil and root depth, the number of soil layers, the water-holding capacity, and the ability to simulate freezing which all together leads to very different soil moisture characteristics. Differences in the water-holding capacity are resulting in deviations in the global median soil moisture of more than one order of magnitude between the models. In contrast, the variance shows similar absolute values when comparing the models to each other. Thus, the input and output rates by precipitation and evapotranspiration, which are computed by the atmospheric component of the models, have to be in the same range. Most models simulate great variances in the monsoon areas of the tropics and north western U.S., intermediate variances in Europe and eastern U.S., and low variances in the Sahara, continental Asia, and central and western Australia. In general, the variance decreases with latitude over the high northern latitudes. As soil moisture trends in the models were found to be negligible, the soil moisture anomalies were calculated by subtracting the 30 year monthly climatology from the data. The length of the memory is determined from the soil moisture anomalies by calculating the first insignificant autocorrelation for ascending monthly lags (insignificant autocorrelation folding time). The models show a great spread of autocorrelation length from a few months in the tropics, north western Canada, eastern U.S. and northern Europe up to few years in the Sahara, the Arabian Peninsula, continental Eurasia and central U.S. Some models simulate very long memory all over the globe. This behavior is associated with differences between the models in the maximum root and soil depth. Models with shallow roots and deep soils exhibit longer memories than models with similar soil and root depths. Further analysis will be conducted to clearly divide models into groups based on their inter-model spatial correlation of simulated soil moisture characteristics.
NASA Technical Reports Server (NTRS)
Orehotsky, J.
1985-01-01
Moisture transport and dielectric breakdown of polyvinyl butyral (PVB), Tedlar, and PVB/Tedlar composites were addressed. Data for the temperature range between 20 and 80 C showed that the moisture flux through the composite is governed by the slower material; and that the composite permeability is intermediate to those of the component material, as predicted by theory. Data for Tedlar at 71 C, showing the dependence of moisture flux on relative humidity, was also presented. Dielectric breakdown data were less precise and less conclusive. The generally applied theoretical model does not match the experimental data. The PVB/Tedlar composite exhibited greater voltage breakdown resistance than either component. Testing of EVA and EVA/Tedlar composites is underway.
Wang, Tie Cheng; Qu, Guangzhou; Li, Jie; Liang, Dongli
2014-01-15
A novel approach, named multi-channel pulsed corona discharge in soil, was developed for remediating organic pollutants contaminated soil, with p-nitrophenol (PNP) as the model pollutant. The feasibility of PNP degradation in soil was explored by evaluating effects of pulse discharge voltage, air flow rate and soil moisture on PNP degradation. Based on roles of chemically active species and evolution of degradation intermediates, PNP degradation processes were discussed. Experimental results showed that about 89.4% of PNP was smoothly degraded within 60min of discharge treatment at pulse discharge voltage 27kV, soil moisture 5% and air flow rate 0.8Lmin(-1), and the degradation process fitted the first-order kinetic model. Increasing pulse discharge voltage was found to be favorable for PNP degradation, but not for energy yield. There existed appropriate air flow rate and soil moisture for obtaining gratifying PNP degradation efficacy. Roles of radical scavenger and measurement of active species suggested that ozone, H2O2, and OH radicals played very important roles in PNP degradation. CN bond in PNP molecule was cleaved, and the main intermediate products such as hydroquinone, benzoquinone, catechol, phenol, acetic acid, formic acid, oxalic acid, NO2(-) and NO3(-) were identified. Possible pathway of PNP degradation in soil in such a system was proposed. Copyright © 2013 Elsevier B.V. All rights reserved.
Use of Edible Laminate Layers in Intermediate Moisture Food Rations to Inhibit Moisture Migration
2016-04-29
methylcellulose, propylene glycol, citric acid, modified starch , white beeswax Water resistant coating on one side Watson, Inc. Dual-sided HPMC moisture...barrier film Hydroxypropyl methylcellulose, propylene glycol, citric acid, modified starch , white beeswax Water resistant coating on both sides...Moisture Barrier (BWMB) film #1 Pullulan*, beeswax, glycerin, propylene glycol, starch , polysorbate 80 Water soluble Watson, Inc. Pullulan BWMB film
NASA Astrophysics Data System (ADS)
Illangasekare, T. H.; Smits, K. M.; Trautz, A.; Rice, A. K.; Cihan, A.; Davarzani, H.
2013-12-01
SSoil moisture processes in the subsurface/near-land-surface, play a crucial role in the hydrologic cycle and global water budget. This zone is subject to both natural and human induced disturbances, resulting in continually changing soil structure and hydraulic, thermal, and mechanical properties. Understanding of the dynamics of soil moisture distribution in this zone is of interest in various applications in hydrology such as land-atmospheric interaction, soil evaporation and evapotranspiration, as well as emerging problems on assessing the risk of leakage of sequestrated CO2 from deep geologic formations to the shallow subsurface, and potential leakage of methane to the atmosphere in shale gas development that contributes to global warming. Shallow subsurface soil moisture is highly influenced by diurnal temperature variations, evaporation/condensation, precipitation and liquid water and water vapor flow, all of which are strongly coupled. Modeling studies, have shown that soil moisture in this zone is highly sensitive to the heat and mass flux boundary conditions at the land surface. Hence, approximation of these boundary conditions without properly incorporating complex feedback between the land and the atmospheric boundary layer are expected to result in significant errors. Even though considerable knowledge exists on how soil moisture changes in response to the flux and energy boundary conditions, emerging problems involving land atmospheric interactions require the quantification of soil moisture variability at higher spatial and temporal resolutions than what is needed in traditional applications in soil physics and vadose zone hydrology. These factors lead to many modeling challenges, primarily of which is the issue of up-scaling. It is our contention that knowledge that will contribute to both improving our understanding of the fundamental processes and practical problem solutions cannot be obtained using only field data. Basic to this limitation is the inability to make field measurements at very fine scales at high temporal resolutions. Also, as the natural boundary conditions at the land/atmospheric interface are not controllable in the field, even in pilot scale studies, the developed theories and models cannot be validated for a diversity of conditions that could be expected. As an alternative, we propose an innovative testing approach that couples a low velocity boundary layer climate wind tunnel to intermediate scale porous media tanks. Intermediate scale testing using soil tanks packed to represent different heterogeneous test configurations provides an attractive and cost effective alternative to investigate a class of problems involving the shallow unsaturated zone. In this talk, we will present examples of studies we have conducted in a hierarchy of test systems, including the intermediate scale. The advantages and limitations of testing at this scale are discussed using these examples. The features and capabilities of newly developed test systems are presented with the goal of exploring opportunities to use them to study some of the challenging multi-scale problems in the near surface unsaturated zone.
Retrieval of Soil Moisture and Roughness from the Polarimetric Radar Response
NASA Technical Reports Server (NTRS)
Sarabandi, Kamal; Ulaby, Fawwaz T.
1997-01-01
The main objective of this investigation was the characterization of soil moisture using imaging radars. In order to accomplish this task, a number of intermediate steps had to be undertaken. In this proposal, the theoretical, numerical, and experimental aspects of electromagnetic scattering from natural surfaces was considered with emphasis on remote sensing of soil moisture. In the general case, the microwave backscatter from natural surfaces is mainly influenced by three major factors: (1) the roughness statistics of the soil surface, (2) soil moisture content, and (3) soil surface cover. First the scattering problem from bare-soil surfaces was considered and a hybrid model that relates the radar backscattering coefficient to soil moisture and surface roughness was developed. This model is based on extensive experimental measurements of the radar polarimetric backscatter response of bare soil surfaces at microwave frequencies over a wide range of moisture conditions and roughness scales in conjunction with existing theoretical surface scattering models in limiting cases (small perturbation, physical optics, and geometrical optics models). Also a simple inversion algorithm capable of providing accurate estimates of soil moisture content and surface rms height from single-frequency multi-polarization radar observations was developed. The accuracy of the model and its inversion algorithm is demonstrated using independent data sets. Next the hybrid model for bare-soil surfaces is made fully polarimetric by incorporating the parameters of the co- and cross-polarized phase difference into the model. Experimental data in conjunction with numerical simulations are used to relate the soil moisture content and surface roughness to the phase difference statistics. For this purpose, a novel numerical scattering simulation for inhomogeneous dielectric random surfaces was developed. Finally the scattering problem of short vegetation cover above a rough soil surface was considered. A general scattering model for grass-blades of arbitrary cross section was developed and incorporated in a first order random media model. The vegetation model and the bare-soil model are combined and the accuracy of the combined model is evaluated against experimental observations from a wheat field over the entire growing season. A complete set of ground-truth data and polarimetric backscatter data were collected. Also an inversion algorithm for estimating soil moisture and surface roughness from multi-polarized multi-frequency observations of vegetation-covered ground is developed.
USDA-ARS?s Scientific Manuscript database
This study demonstrated a new method for mapping high-resolution (spatial: 1 m, and temporal: 1 h) soil moisture by assimilating distributed temperature sensing (DTS) observed soil temperatures at intermediate scales. In order to provide robust soil moisture and property estimates, we first proposed...
USDA-ARS?s Scientific Manuscript database
Soil moisture dynamics reflect the complex interactions of meteorological conditions with soil, vegetation and terrain properties. In this study, intermediate-scale soil moisture estimates from the cosmic-ray neutron sensing (CRNS) method are evaluated for two semiarid ecosystems in the southwestern...
Projecting the Hydrologic Impacts of Climate Change on Montane Wetlands.
Lee, Se-Yeun; Ryan, Maureen E; Hamlet, Alan F; Palen, Wendy J; Lawler, Joshua J; Halabisky, Meghan
2015-01-01
Wetlands are globally important ecosystems that provide critical services for natural communities and human society. Montane wetland ecosystems are expected to be among the most sensitive to changing climate, as their persistence depends on factors directly influenced by climate (e.g. precipitation, snowpack, evaporation). Despite their importance and climate sensitivity, wetlands tend to be understudied due to a lack of tools and data relative to what is available for other ecosystem types. Here, we develop and demonstrate a new method for projecting climate-induced hydrologic changes in montane wetlands. Using observed wetland water levels and soil moisture simulated by the physically based Variable Infiltration Capacity (VIC) hydrologic model, we developed site-specific regression models relating soil moisture to observed wetland water levels to simulate the hydrologic behavior of four types of montane wetlands (ephemeral, intermediate, perennial, permanent wetlands) in the U. S. Pacific Northwest. The hybrid models captured observed wetland dynamics in many cases, though were less robust in others. We then used these models to a) hindcast historical wetland behavior in response to observed climate variability (1916-2010 or later) and classify wetland types, and b) project the impacts of climate change on montane wetlands using global climate model scenarios for the 2040s and 2080s (A1B emissions scenario). These future projections show that climate-induced changes to key driving variables (reduced snowpack, higher evapotranspiration, extended summer drought) will result in earlier and faster drawdown in Pacific Northwest montane wetlands, leading to systematic reductions in water levels, shortened wetland hydroperiods, and increased probability of drying. Intermediate hydroperiod wetlands are projected to experience the greatest changes. For the 2080s scenario, widespread conversion of intermediate wetlands to fast-drying ephemeral wetlands will likely reduce wetland habitat availability for many species.
Projecting the Hydrologic Impacts of Climate Change on Montane Wetlands
Hamlet, Alan F.; Palen, Wendy J.; Lawler, Joshua J.; Halabisky, Meghan
2015-01-01
Wetlands are globally important ecosystems that provide critical services for natural communities and human society. Montane wetland ecosystems are expected to be among the most sensitive to changing climate, as their persistence depends on factors directly influenced by climate (e.g. precipitation, snowpack, evaporation). Despite their importance and climate sensitivity, wetlands tend to be understudied due to a lack of tools and data relative to what is available for other ecosystem types. Here, we develop and demonstrate a new method for projecting climate-induced hydrologic changes in montane wetlands. Using observed wetland water levels and soil moisture simulated by the physically based Variable Infiltration Capacity (VIC) hydrologic model, we developed site-specific regression models relating soil moisture to observed wetland water levels to simulate the hydrologic behavior of four types of montane wetlands (ephemeral, intermediate, perennial, permanent wetlands) in the U. S. Pacific Northwest. The hybrid models captured observed wetland dynamics in many cases, though were less robust in others. We then used these models to a) hindcast historical wetland behavior in response to observed climate variability (1916–2010 or later) and classify wetland types, and b) project the impacts of climate change on montane wetlands using global climate model scenarios for the 2040s and 2080s (A1B emissions scenario). These future projections show that climate-induced changes to key driving variables (reduced snowpack, higher evapotranspiration, extended summer drought) will result in earlier and faster drawdown in Pacific Northwest montane wetlands, leading to systematic reductions in water levels, shortened wetland hydroperiods, and increased probability of drying. Intermediate hydroperiod wetlands are projected to experience the greatest changes. For the 2080s scenario, widespread conversion of intermediate wetlands to fast-drying ephemeral wetlands will likely reduce wetland habitat availability for many species. PMID:26331850
Use of Ultrasonic Technology for Soil Moisture Measurement
NASA Technical Reports Server (NTRS)
Choi, J.; Metzl, R.; Aggarwal, M. D.; Belisle, W.; Coleman, T.
1997-01-01
In an effort to improve existing soil moisture measurement techniques or find new techniques using physics principles, a new technique is presented in this paper using ultrasonic techniques. It has been found that ultrasonic velocity changes as the moisture content changes. Preliminary values of velocities are 676.1 m/s in dry soil and 356.8 m/s in 100% moist soils. Intermediate values can be calibrated to give exact values for the moisture content in an unknown sample.
Sheng, Zhanwu; Gu, Mantun; Hao, Wangjun; Shen, Yixiao; Zhang, Weimin; Zheng, Lili; Ai, Binling; Zheng, Xiaoyan; Xu, Zhimin
2016-06-22
An intermediate-moisture food (IMF) model consisting of whey protein isolate and glucose and an IMF model fortified with resveratrol were used to study the effect of resveratrol on physicochemical changes and glycation of protein-sugar-rich foods during storage. The water activity (aw) of the storage was controlled at 0.75 or 0.56. The browning rate or hardness of fortified IMFs was significantly lower than that of IMFs after 45-day storage. The rate of Maillard reaction in the samples stored at aw 0.56 was higher than that of samples stored at aw 0.75. The fortified IMFs had lower levels of AGEs (advanced glycation end products), CML (N(ε)-(carboxymethyl)-l-lysine), and insoluble protein during storage. The inhibition capability of resveratrol against glycation was also confirmed by using sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE), liquid chromatography mass spectrometry (LC-MS), and Fourier transform infrared spectroscopy (FTIR) analysis to monitor glycated proteins and protein aggregation in the samples. The results of this study suggested that resveratrol could be used as an inhibitor to reduce the formation of undesirable AGEs and other Maillard reaction products in foods during storage.
Sensitivity of Land Surface Parameters on Thunderstorm Simulation through HRLDAS-WRF Coupling Mode
NASA Astrophysics Data System (ADS)
Kumar, Dinesh; Kumar, Krishan; Mohanty, U. C.; Kisore Osuri, Krishna
2016-07-01
Land surface characteristics play an important role in large scale, regional and mesoscale atmospheric process. Representation of land surface characteristics can be improved through coupling of mesoscale atmospheric models with land surface models. Mesoscale atmospheric models depend on Land Surface Models (LSM) to provide land surface variables such as fluxes of heat, moisture, and momentum for lower boundary layer evolution. Studies have shown that land surface properties such as soil moisture, soil temperature, soil roughness, vegetation cover, have considerable effect on lower boundary layer. Although, the necessity to initialize soil moisture accurately in NWP models is widely acknowledged, monitoring soil moisture at regional and global scale is a very tough task due to high spatial and temporal variability. As a result, the available observation network is unable to provide the required spatial and temporal data for the most part of the globe. Therefore, model for land surface initializations rely on updated land surface properties from LSM. The solution for NWP land-state initialization can be found by combining data assimilation techniques, satellite-derived soil data, and land surface models. Further, it requires an intermediate step to use observed rainfall, satellite derived surface insolation, and meteorological analyses to run an uncoupled (offline) integration of LSM, so that the evolution of modeled soil moisture can be forced by observed forcing conditions. Therefore, for accurate land-state initialization, high resolution land data assimilation system (HRLDAS) is used to provide the essential land surface parameters. Offline-coupling of HRLDAS-WRF has shown much improved results over Delhi, India for four thunder storm events. The evolution of land surface variables particularly soil moisture, soil temperature and surface fluxes have provided more realistic condition. Results have shown that most of domain part became wetter and warmer after assimilation of soil moisture and soil temperature at the initial condition which helped to improve the exchange fluxes at lower atmospheric level. Mixing ratio were increased along with elevated theta-e at lower level giving a signature of improvement in LDAS experiment leading to a suitable condition for convection. In the analysis, moisture convergence, mixing ratio and vertical velocities have improved significantly in terms of intensity and time lag. Surface variables like soil moisture, soil temperature, sensible heat flux and latent heat flux have progressed in a possible realistic pattern. Above discussion suggests that assimilation of soil moisture and soil temperature improves the overall simulations significantly.
NASA Astrophysics Data System (ADS)
Hosseini, Seiyed Mossa; Ataie-Ashtiani, Behzad; Simmons, Craig T.
2017-09-01
A simple conceptual rainfall-runoff model is proposed for the estimation of groundwater balance components in complex karst aquifers. In the proposed model the effects of memory length of different karst flow systems of base-flow, intermediate-flow, and quick-flow and also time variation of recharge area (RA) during a hydrological year were investigated. The model consists of three sub-models: soil moisture balance (SMB), epikarst balance (EPB), and groundwater balance (GWB) to simulate the daily spring discharge. The SMB and EPB sub-models utilize the mass conservation equation to compute the variation of moisture storages in the soil cover and epikarst, respectively. The GWB sub-model computes the spring discharge hydrograph through three parallel linear reservoirs for base-flow, intermediate-flow, and quick-flow. Three antecedent recharge indices are defined and embedded in the model structure to deal with the memory effect of three karst flow systems to antecedent recharge flow. The Sasan Karst aquifer located in the semi-arid region of south-west Iran with a continuous long-term (21-years) daily meteorological and discharge data are considered to describe model calibration and validation procedures. The effects of temporal variations of RA of karst formations during the hydrological year namely invariant RA, two RA (winter and summer), four RA (seasonal), and twelve RA (monthly) are assessed to determine their impact on the model efficiency. Results indicated that the proposed model with monthly-variant RA is able to reproduce acceptable simulation results based on modified Kling-Gupta efficiency (KGE = -0.83). The results of density-based global sensitivity analysis for dry (June to September) and a wet (October to May) period reveal the dominant influence of RA (with sensitivity indices equal to 0.89 and 0.93, respectively) in spring discharge simulation. The sensitivity of simulated spring discharge to memory effect of different karst formations during the dry period is greater than the wet period. In addition, the results reveal the important role of intermediate-flow system in the hydrological modeling of karst systems during the wet period. Precise estimation of groundwater budgets for a better decision making regarding water supplies from complex karst systems with long memory effect can considerably be improved by use of the proposed model.
Temporal and spatial variabilities in the surface moisture content of a fine-grained beach
NASA Astrophysics Data System (ADS)
Namikas, S. L.; Edwards, B. L.; Bitton, M. C. A.; Booth, J. L.; Zhu, Y.
2010-01-01
This study examined spatial and temporal variations in the surface moisture content of a fine-grained beach at Padre Island, Texas, USA. Surface moisture measurements were collected on a 27 × 24 m grid that extended from the dune toe to the upper foreshore. The grid was surveyed at 2 to 4 h intervals for two tidal cycles, generating 17 maps of the spatial distribution of surface moisture. Simultaneous measurements of air temperature and humidity, wind speed and direction, tidal elevation, and water table elevation were used to interpret observed changes in surface moisture. It was found that the spatial distribution of surface moisture was broadly characterized by a cross-shore gradient of high to low content moving landward from the swash zone. The distribution of surface moisture was conceptualized in terms of three zones: saturated (> 25%), intermediate or transitional (5-25%), and dry (< 5%). The position of the saturated zone corresponded to the uppermost swash zone and therefore shifted in accordance with tidal elevation. Moisture contents in the intermediate and dry zones were primarily related to variation in water table depth (which was in turn controlled by tidal elevation) and to a lesser extent by evaporation. Signals associated with atmospheric processes such as evaporation were muted by the minimal degree of variation in atmospheric parameters experienced during most of the study period, but were apparent for the last few hours. The observed spatial and temporal variations in moisture content correspond reasonably well with observations of key controlling processes, but more work is needed to fully characterize this process suite.
Bernardo, R
1996-11-01
Best linear unbiased prediction (BLUP) has been found to be useful in maize (Zea mays L.) breeding. The advantage of including both testcross additive and dominance effects (Intralocus Model) in BLUP, rather than only testcross additive effects (Additive Model), has not been clearly demonstrated. The objective of this study was to compare the usefulness of Intralocus and Additive Models for BLUP of maize single-cross performance. Multilocation data from 1990 to 1995 were obtained from the hybrid testing program of Limagrain Genetics. Grain yield, moisture, stalk lodging, and root lodging of untested single crosses were predicted from (1) the performance of tested single crosses and (2) known genetic relationships among the parental inbreds. Correlations between predicted and observed performance were obtained with a delete-one cross-validation procedure. For the Intralocus Model, the correlations ranged from 0.50 to 0.66 for yield, 0.88 to 0.94 for moisture, 0.47 to 0.69 for stalk lodging, and 0.31 to 0.45 for root lodging. The BLUP procedure was consistently more effective with the Intralocus Model than with the Additive Model. When the Additive Model was used instead of the Intralocus Model, the reductions in the correlation were largest for root lodging (0.06-0.35), smallest for moisture (0.00-0.02), and intermediate for yield (0.02-0.06) and stalk lodging (0.02-0.08). The ratio of dominance variance (v D) to total genetic variance (v G) was highest for root lodging (0.47) and lowest for moisture (0.10). The Additive Model may be used if prior information indicates that VD for a given trait has little contribution to VG. Otherwise, the continued use of the Intralocus Model for BLUP of single-cross performance is recommended.
Improving UK Chalk hydrometeorology across spatial scales using a small hydrometeorological network
NASA Astrophysics Data System (ADS)
Rosolem, Rafael; Iwema, Joost; Rahman, Mostaquimur; Desilets, Darin; Koltermann da Silva, Juliana
2016-04-01
Chalk in the UK acts as a primary aquifer providing up to 80% of the public water supply locally. Chalk outcrops are located over most of southern and eastern England. Despite its importance, the characterization of Chalk in hydrometeorological models is still very limited. There is a need for a comprehensive and coherent integration of observations and modeling efforts across spatial scales for better understanding Chalk hydrometeorology. Here we introduce the "A MUlti-scale Soil moisture-Evapotranspiration Dynamics" (AMUSED) project. AMUSED goal is to better identify the key dominant processes controlling changes in soil moisture and surface fluxes (e.g., evapotranspiration) across spatial scales by combining ground-based observations with hydrometeorological models and satellite remote sensing products. The AMUSED observational platform consists of three sites located in Upper Chalk region of the Lambourn Catchment located in southern England covering approximately 2 square-km characterized by distinct combinations of soil and vegetation types. The network includes standard meteorological measurements, an eddy covariance system for turbulent fluxes and cosmic-ray neutron sensors for integrated soil moisture estimates at intermediate scales. Here we present our initial results from our three sites.
NASA Astrophysics Data System (ADS)
Meyer, N.; Welp, G.; Amelung, W.
2018-02-01
The temperature sensitivity of heterotrophic soil respiration is crucial for modeling carbon dynamics but it is variable. Presently, however, most models employ a fixed value of 1.5 or 2.0 for the increase of soil respiration per 10°C increase in temperature (Q10). Here we identified the variability of Q10 at a regional scale (Rur catchment, Germany/Belgium/Netherlands). We divided the study catchment into environmental soil classes (ESCs), which we define as unique combinations of land use, aggregated soil groups, and texture. We took nine soil samples from each ESC (108 samples) and incubated them at four soil moisture levels and five temperatures (5-25°C). We hypothesized that Q10 variability is controlled by soil organic carbon (SOC) degradability and soil moisture and that ESC can be used as a widely available proxy for Q10, owing to differences in SOC degradability. Measured Q10 values ranged from 1.2 to 2.8 and were correlated with indicators of SOC degradability (e.g., pH, r = -0.52). The effect of soil moisture on Q10 was variable: Q10 increased with moisture in croplands but decreased in forests. The ESC captured significant parts of Q10 variability under dry (R2 = 0.44) and intermediate (R2 = 0.36) moisture conditions, where Q10 increased in the order cropland
Estimation of effective soil hydraulic properties at field scale via ground albedo neutron sensing
NASA Astrophysics Data System (ADS)
Rivera Villarreyes, C. A.; Baroni, G.; Oswald, S. E.
2012-04-01
Upscaling of soil hydraulic parameters is a big challenge in hydrological research, especially in model applications of water and solute transport processes. In this contest, numerous attempts have been made to optimize soil hydraulic properties using observations of state variables such as soil moisture. However, in most of the cases the observations are limited at the point-scale and then transferred to the model scale. In this way inherent small-scale soil heterogeneities and non-linearity of dominate processes introduce sources of error that can produce significant misinterpretation of hydrological scenarios and unrealistic predictions. On the other hand, remote-sensed soil moisture over large areas is also a new promising approach to derive effective soil hydraulic properties over its observation footprint, but it is still limited to the soil surface. In this study we present a new methodology to derive soil moisture at the intermediate scale between point-scale observations and estimations at the remote-sensed scale. The data are then used for the estimation of effective soil hydraulic parameters. In particular, ground albedo neutron sensing (GANS) was used to derive non-invasive soil water content in a footprint of ca. 600 m diameter and a depth of few decimeters. This approach is based on the crucial role of hydrogen compared to other landscape materials as neutron moderator. As natural neutron measured aboveground depends on soil water content, the vertical footprint of the GANS method, i.e. its penetration depth, does also. Firstly, this study was designed to evaluate the dynamics of GANS vertical footprint and derive a mathematical model for its prediction. To test GANS-soil moisture and its penetration depth, it was accompanied by other soil moisture measurements (FDR) located at 5, 20 and 40 cm depths over the GANS horizontal footprint in a sunflower field (Brandenburg, Germany). Secondly, a HYDRUS-1D model was set up with monitored values of crop height and meteorological variables as input during a four-month period. Parameter estimation (PEST) software was coupled to HYDRUS-1D in order to calibrate soil hydraulic properties based on soil water content data. Thirdly, effective soil hydraulic properties were derived from GANS-soil moisture. Our observations show the potential of GANS to compensate the lack of information at the intermediate scale, soil water content estimation and effective soil properties. Despite measurement volumes, GANS-derived soil water content compared quantitatively to FDRs at several depths. For one-hour estimations, root mean square error was estimated as 0.019, 0.029 and 0.036 m3/m3 for 5 cm, 20 cm and 40 cm depths, respectively. In the context of soil hydraulic properties, this first application of GANS method succeed and its estimations were comparable to those derived by other approaches.
USDA-ARS?s Scientific Manuscript database
Soil moisture content on a horizontal scale of hectometers and at depths of decimeters can be inferred from measurements of low-energy cosmic-ray neutrons that are generated within soil, moderated mainly by hydrogen atoms, and diffused back to the atmosphere. These neutrons are sensitive to water co...
Storage stability and improvement of intermediate moisture foods, phase 2
NASA Technical Reports Server (NTRS)
Labuza, T. P.
1975-01-01
Methods for improvement of shelf-life stability of intermediate moisture foods are considered. It was found that vitamin C is the most limiting vitamin from a nutritional standpoint with its rate of destruction increasing with a sub w. Techniques for microbial challenge studies were developed. It was shown that organisms have a higher growth a sub w limit if the IMF is prepared by the adsorption process and long times are needed for challenge studies. Several alternative antimycotic systems were found. It was also found that the vegetative cells of pathogens have a maximum heat resistance in the IMF a sub w range. If glycols are in the formula, the IMF should have as high an a sub w as possible. The reverse is true if lipid oxidation occurs. In addition, to prevent rancidity, antioxidants and a low O2 atmosphere are necessary. The package also must be a good moisture barrier.
Evaluating soil moisture constraints on surface fluxes in land surface models globally
NASA Astrophysics Data System (ADS)
Harris, Phil; Gallego-Elvira, Belen; Taylor, Christopher; Folwell, Sonja; Ghent, Darren; Veal, Karen; Hagemann, Stefan
2016-04-01
Soil moisture availability exerts a strong control over land evaporation in many regions. However, global climate models (GCMs) disagree on when and where evaporation is limited by soil moisture. Evaluation of the relevant modelled processes has suffered from a lack of reliable, global observations of land evaporation at the GCM grid box scale. Satellite observations of land surface temperature (LST) offer spatially extensive but indirect information about the surface energy partition and, under certain conditions, about soil moisture availability on evaporation. Specifically, as soil moisture decreases during rain-free dry spells, evaporation may become limited leading to increases in LST and sensible heat flux. We use MODIS Terra and Aqua observations of LST at 1 km from 2000 to 2012 to assess changes in the surface energy partition during dry spells lasting 10 days or longer. The clear-sky LST data are aggregated to a global 0.5° grid before being composited as a function dry spell day across many events in a particular region and season. These composites are then used to calculate a Relative Warming Rate (RWR) between the land surface and near-surface air. This RWR can diagnose the typical strength of short term changes in surface heat fluxes and, by extension, changes in soil moisture limitation on evaporation. Offline land surface model (LSM) simulations offer a relatively inexpensive way to evaluate the surface processes of GCMs. They have the benefits that multiple models, and versions of models, can be compared on a common grid and using unbiased forcing. Here, we use the RWR diagnostic to assess global, offline simulations of several LSMs (e.g., JULES and JSBACH) driven by the WATCH Forcing Data-ERA Interim. Both the observed RWR and the LSMs use the same 0.5° grid, which allows the observed clear-sky sampling inherent in the underlying MODIS LST to be applied to the model outputs directly. This approach avoids some of the difficulties in analysing free-running simulations in which land and atmosphere are coupled and, as such, it provides a flexible intermediate step in the assessment of surface processes in GCMs.
NASA Astrophysics Data System (ADS)
Sellers, Piers J.; Heiser, Mark D.; Hall, Forrest G.; Verma, Shashi B.; Desjardins, Raymond L.; Schuepp, Peter M.; Ian MacPherson, J.
1997-03-01
It is commonly assumed that biophysically based soil-vegetation-atmosphere transfer (SVAT) models are scale-invariant with respect to the initial boundary conditions of topography, vegetation condition and soil moisture. In practice, SVAT models that have been developed and tested at the local scale (a few meters or a few tens of meters) are applied almost unmodified within general circulation models (GCMs) of the atmosphere, which have grid areas of 50-500 km 2. This study, which draws much of its substantive material from the papers of Sellers et al. (1992c, J. Geophys. Res., 97(D17): 19033-19060) and Sellers et al. (1995, J. Geophys. Res., 100(D12): 25607-25629), explores the validity of doing this. The work makes use of the FIFE-89 data set which was collected over a 2 km × 15 km grassland area in Kansas. The site was characterized by high variability in soil moisture and vegetation condition during the late growing season of 1989. The area also has moderate topography. The 2 km × 15 km 'testbed' area was divided into 68 × 501 pixels of 30 m × 30 m spatial resolution, each of which could be assigned topographic, vegetation condition and soil moisture parameters from satellite and in situ observations gathered in FIFE-89. One or more of these surface fields was area-averaged in a series of simulation runs to determine the impact of using large-area means of these initial or boundary conditions on the area-integrated (aggregated) surface fluxes. The results of the study can be summarized as follows: 1. analyses and some of the simulations indicated that the relationships describing the effects of moderate topography on the surface radiation budget are near-linear and thus largely scale-invariant. The relationships linking the simple ratio vegetation index ( SR), the canopy conductance parameter (▽ F) and the canopy transpiration flux are also near-linear and similarly scale-invariant to first order. Because of this, it appears that simple area-averaging operations can be applied to these fields with relatively little impact on the calculated surface heat flux. 2. The relationships linking surface and root-zone soil wetness to the soil surface and canopy transpiration rates are non-linear. However, simulation results and observations indicate that soil moisture variability decreases significantly as an area dries out, which partially cancels out the effects of these non-linear functions.In conclusion, it appears that simple averages of topographic slope and vegetation parameters can be used to calculate surface energy and heat fluxes over a wide range of spatial scales, from a few meters up to many kilometers at least for grassland sites and areas with moderate topography. Although the relationships between soil moisture and evapotranspiration are non-linear for intermediate soil wetnesses, the dynamics of soil drying act to progressively reduce soil moisture variability and thus the impacts of these non-linearities on the area-averaged surface fluxes. These findings indicate that we may be able to use mean values of topography, vegetation condition and soil moisture to calculate the surface-atmosphere fluxes of energy, heat and moisture at larger length scales, to within an acceptable accuracy for climate modeling work. However, further tests over areas with different vegetation types, soils and more extreme topography are required to improve our confidence in this approach.
[Intermediate moisture food for elder people based on a legume: soybeans, mixture with calcium].
Del Castillo, V C; Armada de Roman, M; s Gotiffredi, J C
2000-09-01
An intermediate moisture food (IMF), has been developed in our laboratory for elder people, over 60 years. The IMF is based on a cereal: legume mixture with calcium and flavour, it supplies proteins, carbohydrates and vegetable oils; as well as, high energetic density (3.22 cal/g) and covers up to 51% of calcium needed. It can be easily consumed as a tasty and soft food. It has a water activity of 0.80, for it can be stored at room conditions. It is very likely that IMF becomes a good alternative to improve and vary elder peoples diet.
Shelf life and safety concerns of bakery products--a review.
Smith, James P; Daifas, Daphne Phillips; El-Khoury, Wassim; Koukoutsis, John; El-Khoury, Anis
2004-01-01
Bakery products are an important part of a balanced diet and, today, a wide variety of such products can be found on supermarket shelves. This includes unsweetened goods (bread, rolls, buns, crumpets, muffins and bagels), sweet goods (pancakes, doughnuts, waffles and cookies) and filled goods (fruit and meat pies, sausage rolls, pastries, sandwiches, cream cakes, pizza and quiche). However, bakery products, like many processed foods, are subject to physical, chemical and microbiological spoilage. While physical and chemical spoilage limits the shelf life of low and intermediate moisture bakery products, microbiological spoilage by bacteria, yeast and molds is the concern in high moisture products i.e., products with a water activity (a(w)) > 0.85. Furthermore, several bakery products also have been implicated infoodborne illnesses involving Salmonella spp., Listeria monoctyogenes and Bacillus cereus, while Clostridium botulinum is a concern in high moisture bakery products packaged under modified atmospheres. This extensive review is divided into two parts. Part I focuses on the spoilage concerns of low, intermediate and high moisture bakery products while Part II focuses on the safety concerns of high moisture bakery products only. In both parts, traditional and novel methods of food preservation that can be used by the bakery industry to extend the shelf life and enhance the safety of products are discussed in detail.
Storage Stability and Improvement of Intermediate Moisture Foods, Phase 3
NASA Technical Reports Server (NTRS)
Labuza, T. P.
1975-01-01
Methods were determined for the improvement of shelf-life stability of intermediate moisture foods (IMF). Microbial challenge studies showed that protection against molds and Staphylococcus aureus could be achieved by a combination of antimicrobial agents, humectants and food acids. Potassium sorbate and propylene glycol gave the best results. It was also confirmed that the maximum in heat resistance shown by vegetative pathogens at intermediate water activities also occurred in a solid food. Glycols and sorbitol both achieve browning inhibition because of their action as a medium for reaction and effect on viscosity of the adsorbed phase. Chemical availability results showed rapid lysine loss before visual discoloration occurred. This is being confirmed with a biological test using Tetrahymena pyriformis W. Accelerated temperature tests show that effectiveness of food antioxidants against rancidity development can be predicted; however, the protection factor changes with temperature. BHA was found to be the best antioxidant for iron catalyzed oxidation.
Effect of water table dynamics on land surface hydrologic memory
NASA Astrophysics Data System (ADS)
Lo, Min-Hui; Famiglietti, James S.
2010-11-01
The representation of groundwater dynamics in land surface models has received considerable attention in recent years. Most studies have found that soil moisture increases after adding a groundwater component because of the additional supply of water to the root zone. However, the effect of groundwater on land surface hydrologic memory (persistence) has not been explored thoroughly. In this study we investigate the effect of water table dynamics on National Center for Atmospheric Research Community Land Model hydrologic simulations in terms of land surface hydrologic memory. Unlike soil water or evapotranspiration, results show that land surface hydrologic memory does not always increase after adding a groundwater component. In regions where the water table level is intermediate, land surface hydrologic memory can even decrease, which occurs when soil moisture and capillary rise from groundwater are not in phase with each other. Further, we explore the hypothesis that in addition to atmospheric forcing, groundwater variations may also play an important role in affecting land surface hydrologic memory. Analyses show that feedbacks of groundwater on land surface hydrologic memory can be positive, negative, or neutral, depending on water table dynamics. In regions where the water table is shallow, the damping process of soil moisture variations by groundwater is not significant, and soil moisture variations are mostly controlled by random noise from atmospheric forcing. In contrast, in regions where the water table is very deep, capillary fluxes from groundwater are small, having limited potential to affect soil moisture variations. Therefore, a positive feedback of groundwater to land surface hydrologic memory is observed in a transition zone between deep and shallow water tables, where capillary fluxes act as a buffer by reducing high-frequency soil moisture variations resulting in longer land surface hydrologic memory.
NASA Astrophysics Data System (ADS)
Zhu, Qing; Liao, Kaihua; Doolittle, James; Lin, Henry
2014-05-01
Hydropedological dynamics including soil moisture variation, subsurface flow, and spatial distributions of different soil properties are important parameters in ecological, environmental, hydrological, and agricultural modeling and applications. However, technical gap exists in mapping these dynamics at intermediate spatial scale (e.g., farm and catchment scales). At intermediate scales, in-situ monitoring provides detailed data, but is restricted in number and spatial coverage; while remote sensing provides more acceptable spatial coverage, but has comparatively low spatial resolution, limited observation depths, and is greatly influenced by the surface condition and climate. As a non-invasive, fast, and convenient geophysical tool, electromagnetic induction (EMI) measures soil apparent electrical conductivity (ECa) and has great potential to bridge this technical gap. In this presentation, principles of different EMI meters are briefly introduced. Then, case studies of using repeated EMI to detect spatial distributions of subsurface convergent flow, soil moisture dynamics, soil types and their transition zones, and different soil properties are presented. The suitability, effectiveness, and accuracy of EMI are evaluated for mapping different hydropedological dynamics. Lastly, contributions of different hydropedological and terrain properties on soil ECa are quantified under different wetness conditions, seasons, and land use types using Classification and Regression Tree model. Trend removal and residual analysis are then used for further mining of EMI survey data. Based on these analyses, proper EMI survey designs and data processing are proposed.
Development and Application of a Soil Moisture Downscaling Method for Mobility Assessment
2011-05-01
instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send...REPORT Development and Application of a Soil Moisture Downscaling Method for Mobility Assessment 14. ABSTRACT 16. SECURITY CLASSIFICATION OF: Soil...cells). Thus, a method is required to downscale intermediate-resolution patterns to finer resolutions. Fortunately, fine-resolution variations in
Composition and abundance of tree regeneration
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)...
NASA Astrophysics Data System (ADS)
Illangasekare, T. H.; Trautz, A. C.; Howington, S. E.; Cihan, A.
2017-12-01
It is a well-established fact that the land and atmosphere form a continuum in which the individual domains are coupled by heat and mass transfer processes such as bare-soil evaporation. Soil moisture dynamics can be simulated at the representative elementary volume (REV) scale using decoupled and fully coupled Darcy/Navier-Stokes models. Decoupled modeling is an asynchronous approach in which flow and transport in the soil and atmosphere is simulated independently; the two domains are coupled out of time-step via prescribed flux parameterizations. Fully coupled modeling in contrast, solves the governing equations for flow and transport in both domains simultaneously with the use of coupling interface boundary conditions. This latter approach, while being able to provide real-time two-dimensional feedbacks, is considerably more complex and computationally intensive. In this study, we investigate whether fully coupled models are necessary, or if the simpler decoupled models can sufficiently capture soil moisture dynamics under varying land preparations. A series of intermediate-scale physical and numerical experiments were conducted in which soil moisture distributions and evaporation estimates were monitored at high spatiotemporal resolutions for different heterogeneous packing and soil roughness scenarios. All experimentation was conducted at the newly developed Center for Experimental Study of Subsurface Environmental Processes (CESEP) wind tunnel-porous media user test-facility at the Colorado School of. Near-surface atmospheric measurements made during the experiments demonstrate that the land-atmosphere coupling was relatively weak and insensitive to the applied edaphic and surface conditions. Simulations with a decoupled multiphase heat and mass transfer model similarly show little sensitivity to local variations in atmospheric forcing; a single, simple flux parameterization can sufficiently capture the soil moisture dynamics (evaporation and redistribution) as long as the subsurface conditions (i.e., heterogeneity) are properly described. These findings suggest that significant improvements to simulations results should not be expected if fully coupled modeling were adopted in scenarios of weak land-atmosphere coupling in the context of bare soil evaporation.
NASA Astrophysics Data System (ADS)
Andreasen, M.; Looms, M. C.; Bogena, H. R.; Desilets, D.; Zreda, M. G.; Sonnenborg, T. O.; Jensen, K. H.
2014-12-01
The water stored in the various compartments of the terrestrial ecosystem (in snow, canopy interception, soil and litter) controls the exchange of the water and energy between the land surface and the atmosphere. Therefore, measurements of the water stored within these pools are critical for the prediction of e.g. evapotranspiration and groundwater recharge. The detection of cosmic-ray neutron intensity is a novel non-invasive method for the quantification of continuous intermediate-scale soil moisture. The footprint of the cosmic-ray neutron probe is a hemisphere of a few hectometers and subsurface depths of 10-70 cm depending on wetness. The cosmic-ray neutron method offers measurements at a scale between the point-scale measurements and large-scale satellite retrievals. The cosmic-ray neutron intensity is inversely correlated to the hydrogen stored within the footprint. Overall soil moisture represents the largest pool of hydrogen and changes in the soil moisture clearly affect the cosmic-ray neutron signal. However, the neutron intensity is also sensitive to variations of hydrogen in snow, canopy interception and biomass offering the potential to determine water content in such pools from the signal. In this study we tested the potential of determining canopy interception and biomass using cosmic-ray neutron intensity measurements within the framework of the Danish Hydrologic Observatory (HOBE) and the Terrestrial Environmental Observatories (TERENO). Continuous measurements at the ground and the canopy level, along with profile measurements were conducted at towers at forest field sites. Field experiments, including shielding the cosmic-ray neutron probes with cadmium foil (to remove lower-energy neutrons) and measuring reference intensity rates at complete water saturated conditions (on the sea close to the HOBE site), were further conducted to obtain an increased understanding of the physics controlling the cosmic-ray neutron transport and the equipment used. Additionally, neutron transport modeling, using the extended version of the Monte Carlo N-Particle Transport Code, was conducted. The responses of the reference condition, different amounts of biomass, soil moisture and canopy interception on the cosmic-ray neutron intensity were simulated and compared to the measurements.
Estimation of hectare-scale soil-moisture characteristics from aquifer-test data
Moench, A.F.
2003-01-01
Analysis of a 72-h, constant-rate aquifer test conducted in a coarse-grained and highly permeable, glacial outwash deposit on Cape Cod, Massachusetts revealed that drawdowns measured in 20 piezometers located at various depths below the water table and distances from the pumped well were significantly influenced by effects of drainage from the vadose zone. The influence was greatest in piezometers located close to the water table and diminished with increasing depth. The influence of the vadose zone was evident from a gap, in the intermediate-time zone, between measured drawdowns and drawdowns computed under the assumption that drainage from the vadose zone occurred instantaneously in response to a decline in the elevation of the water table. By means of an analytical model that was designed to account for time-varying drainage, simulated drawdowns could be closely fitted to measured drawdowns regardless of the piezometer locations. Because of the exceptional quality and quantity of the data and the relatively small aquifer heterogeneity, it was possible by inverse modeling to estimate all relevant aquifer parameters and a set of three empirical constants used in the upper-boundary condition to account for the dynamic drainage process. The empirical constants were used to define a one-dimensional (ID) drainage versus time curve that is assumed to be representative of the bulk material overlying the water table. The curve was inverted with a parameter estimation algorithm and a ID numerical model for variably saturated flow to obtain soil-moisture retention curves and unsaturated hydraulic conductivity relationships defined by the Brooks and Corey equations. Direct analysis of the aquifer-test data using a parameter estimation algorithm and a two-dimensional, axisymmetric numerical model for variably saturated flow yielded similar soil-moisture characteristics. Results suggest that hectare-scale soil-moisture characteristics are different from core-scale predictions and even relatively small amounts of fine-grained material and heterogeneity can dominate the large-scale soil-moisture characteristics and aquifer response. ?? 2003 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Quiquet, Aurélien; Roche, Didier M.
2017-04-01
Comprehensive fully coupled ice sheet - climate models allowing for multi-millenia transient simulations are becoming available. They represent powerful tools to investigate ice sheet - climate interactions during the repeated retreats and advances of continental ice sheets of the Pleistocene. However, in such models, most of the time, the spatial resolution of the ice sheet model is one order of magnitude lower than the one of the atmospheric model. As such, orography-induced precipitation is only poorly represented. In this work, we briefly present the most recent improvements of the ice sheet - climate coupling within the model of intermediate complexity iLOVECLIM. On the one hand, from the native atmospheric resolution (T21), we have included a dynamical downscaling of heat and moisture at the ice sheet model resolution (40 km x 40 km). This downscaling accounts for feedbacks of sub-grid precipitation on large scale energy and water budgets. From the sub-grid atmospheric variables, we compute an ice sheet surface mass balance required by the ice sheet model. On the other hand, we also explicitly use oceanic temperatures to compute sub-shelf melting at a given depth. Based on palaeo evidences for rate of change of eustatic sea level, we discuss the capability of our new model to correctly simulate the last glacial inception ( 116 kaBP) and the ice volume of the last glacial maximum ( 21 kaBP). We show that the model performs well in certain areas (e.g. Canadian archipelago) but some model biases are consistent over time periods (e.g. Kara-Barents sector). We explore various model sensitivities (e.g. initial state, vegetation, albedo) and we discuss the importance of the downscaling of precipitation for ice nucleation over elevated area and for the surface mass balance of larger ice sheets.
Yi, Shuhua; McGuire, A. David; Harden, Jennifer; Kasischke, Eric; Manies, Kristen L.; Hinzman, Larry; Liljedahl, Anna K.; Randerson, J.; Liu, Heping; Romanovsky, Vladimir E.; Marchenko, Sergey S.; Kim, Yongwon
2009-01-01
Soil temperature and moisture are important factors that control many ecosystem processes. However, interactions between soil thermal and hydrological processes are not adequately understood in cold regions, where the frozen soil, fire disturbance, and soil drainage play important roles in controlling interactions among these processes. These interactions were investigated with a new ecosystem model framework, the dynamic organic soil version of the Terrestrial Ecosystem Model, that incorporates an efficient and stable numerical scheme for simulating soil thermal and hydrological dynamics within soil profiles that contain a live moss horizon, fibrous and amorphous organic horizons, and mineral soil horizons. The performance of the model was evaluated for a tundra burn site that had both preburn and postburn measurements, two black spruce fire chronosequences (representing space-for-time substitutions in well and intermediately drained conditions), and a poorly drained black spruce site. Although space-for-time substitutions present challenges in model-data comparison, the model demonstrates substantial ability in simulating the dynamics of evapotranspiration, soil temperature, active layer depth, soil moisture, and water table depth in response to both climate variability and fire disturbance. Several differences between model simulations and field measurements identified key challenges for evaluating/improving model performance that include (1) proper representation of discrepancies between air temperature and ground surface temperature; (2) minimization of precipitation biases in the driving data sets; (3) improvement of the measurement accuracy of soil moisture in surface organic horizons; and (4) proper specification of organic horizon depth/properties, and soil thermal conductivity.
NASA Astrophysics Data System (ADS)
Pilli, Siva P.
Moisture plays a significant role in influencing the mechanical behavior and long-term durability of composites. The objective of this dissertation was to understand the basic concepts of moisture transport in polymeric composites. Humidity test chambers were used in combination with D2O water to characterize the diffusion of D2O using Nuclear Reaction Analysis (NRA). Moisture content was measured as a function of through-thickness depth using NRA. In this study a novel method to measure the orthotropic diffusivities of polymer matrix composites has been demonstrated. This was achieved by soaking the samples in D2O vapor and subsequently characterizing the diffusion of D2O at all edges of the coupon using NRA. The diffusivity through the surface was 3½ times higher than the diffusivity through the edges. A direct comparison of experimental data with models using orthotropic diffusivities was in relatively good agreement. Surface moisture content was also measured as a function of time using NRA. It was shown that the surface concentration reaches an intermediate value of 79% Mm very rapidly and is followed by a slow linear increase to the saturation level (Mm). This research also interrogates the effect of pressure on diffusion. Test chambers were built to maintain a constant relative humidity of 80% at 60°C at three different pressures (0.101 MPa, 0.517 MPa and 1.034 MPa) including a liquid water immersion test chamber at 60°C. In this study it was observed that the time to saturation increased with increasing chamber pressure. This was primarily due to the increased maximum moisture content at higher pressures. Liquid immersion of the test samples provided the upper bound for maximum moisture content and a lower bound for time to saturation. The effects of material systems and layups on humidity measurements were also studied using two different polymer composite material systems, Cycom and Toray. Diffusivity results were identical for different layups whereas differences were observed for different material systems. Finally three-dimensional numeric models were developed, using ANSYS, to compare with the measured moisture content. Models incorporating the time-dependent and 3-D diffusion have shown an improved correlation with experiments.
Madani, Nima; Kimball, John S.; Nazeri, Mona; Kumar, Lalit; Affleck, David L. R.
2016-01-01
Species distribution modeling has been widely used in studying habitat relationships and for conservation purposes. However, neglecting ecological knowledge about species, e.g. their seasonal movements, and ignoring the proper environmental factors that can explain key elements for species survival (shelter, food and water) increase model uncertainty. This study exemplifies how these ecological gaps in species distribution modeling can be addressed by modeling the distribution of the emu (Dromaius novaehollandiae) in Australia. Emus cover a large area during the austral winter. However, their habitat shrinks during the summer months. We show evidence of emu summer habitat shrinkage due to higher fire frequency, and low water and food availability in northern regions. Our findings indicate that emus prefer areas with higher vegetation productivity and low fire recurrence, while their distribution is linked to an optimal intermediate (~0.12 m3 m-3) soil moisture range. We propose that the application of three geospatial data products derived from satellite remote sensing, namely fire frequency, ecosystem productivity, and soil water content, provides an effective representation of emu general habitat requirements, and substantially improves species distribution modeling and representation of the species’ ecological habitat niche across Australia. PMID:26799732
Madani, Nima; Kimball, John S; Nazeri, Mona; Kumar, Lalit; Affleck, David L R
2016-01-01
Species distribution modeling has been widely used in studying habitat relationships and for conservation purposes. However, neglecting ecological knowledge about species, e.g. their seasonal movements, and ignoring the proper environmental factors that can explain key elements for species survival (shelter, food and water) increase model uncertainty. This study exemplifies how these ecological gaps in species distribution modeling can be addressed by modeling the distribution of the emu (Dromaius novaehollandiae) in Australia. Emus cover a large area during the austral winter. However, their habitat shrinks during the summer months. We show evidence of emu summer habitat shrinkage due to higher fire frequency, and low water and food availability in northern regions. Our findings indicate that emus prefer areas with higher vegetation productivity and low fire recurrence, while their distribution is linked to an optimal intermediate (~0.12 m3 m(-3)) soil moisture range. We propose that the application of three geospatial data products derived from satellite remote sensing, namely fire frequency, ecosystem productivity, and soil water content, provides an effective representation of emu general habitat requirements, and substantially improves species distribution modeling and representation of the species' ecological habitat niche across Australia.
Dehumidifier assisted drying of a model fruit pulp-based gel and sensory attributes.
Tiwari, Shipra; Ravi, Ramasamy; Bhattacharya, Suvendu
2012-07-01
Model fruit pulp-based gels were prepared by varying mango pulp (0% to 50%), sucrose (0% to 20%), and agar (1% to 3%) and according to a response surface experimental design followed by drying at a low temperature of 40 °C upto 15 h in a tray dryer assisted by a dehumidifier. The moisture content, shrinkage (SHR), and rheological parameters (failure strain, failure stress (FS), firmness, and energy for compression) were determined as a function of drying time. The composition of gel, particularly the agar content had a prominent effect on the characteristics of the dried gel. Detailed descriptive sensory analysis employing principle component analysis (PCA) biplot indicated two distinct groups of attributes; the first group comprised initial and final moisture contents, extent of moisture removal (EMR), and shrinkage. The fracture stress and energy formed the second group. The analysis of variance for failure stress showed that it depended only on the positive linear and quadratic effects of agar (significant at P ≤ 0.01 and 0.05, respectively). The theoretically predicted extent of moisture removal at 95.6% could be achieved when the level of agar was 1.2%; pulp and sucrose levels were also close to their lowest levels of 3.6% and 0.04%, respectively. Scope exists to develop gel-based fruit analogues wherein an appropriate hydrocolloid can be employed along with fruit juice/pulp. To provide a reasonable shelf-life of the developed intermediate moisture containing product, dehumidifier assisted drying is a pragmatic approach that affects sensory and rheological attributes of the dried fruit analogue. © 2012 Institute of Food Technologists®
Constraints on Cumulus Parameterization from Simulations of Observed MJO Events
NASA Technical Reports Server (NTRS)
Del Genio, Anthony; Wu, Jingbo; Wolf, Audrey B.; Chen, Yonghua; Yao, Mao-Sung; Kim, Daehyun
2015-01-01
Two recent activities offer an opportunity to test general circulation model (GCM) convection and its interaction with large-scale dynamics for observed Madden-Julian oscillation (MJO) events. This study evaluates the sensitivity of the Goddard Institute for Space Studies (GISS) GCM to entrainment, rain evaporation, downdrafts, and cold pools. Single Column Model versions that restrict weakly entraining convection produce the most realistic dependence of convection depth on column water vapor (CWV) during the Atmospheric Radiation Measurement MJO Investigation Experiment at Gan Island. Differences among models are primarily at intermediate CWV where the transition from shallow to deeper convection occurs. GCM 20-day hindcasts during the Year of Tropical Convection that best capture the shallow–deep transition also produce strong MJOs, with significant predictability compared to Tropical Rainfall Measuring Mission data. The dry anomaly east of the disturbance on hindcast day 1 is a good predictor of MJO onset and evolution. Initial CWV there is near the shallow–deep transition point, implicating premature onset of deep convection as a predictor of a poor MJO simulation. Convection weakly moistens the dry region in good MJO simulations in the first week; weakening of large-scale subsidence over this time may also affect MJO onset. Longwave radiation anomalies are weakest in the worst model version, consistent with previous analyses of cloud/moisture greenhouse enhancement as the primary MJO energy source. The authors’ results suggest that both cloud-/moisture-radiative interactions and convection–moisture sensitivity are required to produce a successful MJO simulation.
NASA Astrophysics Data System (ADS)
Huang, W.; Hall, S. J.
2016-12-01
Soil organic matter decomposition is widely thought to be constrained by reducing conditions in flooded wetland ecosystems. However, the potential impact of periodic reducing conditions on carbon (C) mineralization in terrestrial mineral soils that experience transient moisture saturation has received less attention. Here we incubated three Mollisols amended with C4 leaf litter at three different soil moisture levels (field capacity for the control, intermediate, and saturation) over three months in the laboratory. Soil CO2 and CH4 production and isotope ratios of CO2 (δ13CO2) were measured daily using a tunable diode laser for the first two weeks and weekly thereafter. Soil Eh dropped from 516 mV to -184 mV in the intermediate and saturated soils during the first seventeen days; iron (Fe) reduction occurred in both intermediate and saturated soils after the seventh day. Total CO2 production rate in the intermediate and saturated soils was initially lower than the control, but exceeded the control after the eleventh day. After three months, mean cumulative CO2 production was significantly higher in the intermediate soil moisture treatment (152 μmol CO2 g-1 soil, P < 0.01) and equivalent between the saturated and control soils (128 and 141 μmol CO2 g-1 soil, P = 0.11). The intermediate and saturated soils also induced substantial CH4 production. Differences in mean δ13CO2 (-14.0‰ for the control and -22.7‰ for the saturated soils) over the first two weeks (before CH4 production began) showed that CO2 production from the saturated soils was derived from different C source(s) compared to the control. These findings challenge traditional paradigms by showing that reducing conditions can enhance C mineralization, perhaps by facilitating microbial access to alternative or occluded C sources. We suggest that Fe reduction could be an important mechanism of C loss in mineral soils due to the release of adsorbed or co-precipitated organic matter during Fe solubilization.
Development of Fermented Taro as a Food Preservative Ingredient in Intermediate Moisture Products
2005-11-01
BACTERIOCINS TARO MOISTURE MICROBIOLOGY NISIN SHELF LIFE FOOD SPOILAGE RATIONS FOOD SAFETY FERMF.l’l TATION 16. SECURITY CLASSIFICATION OF: 17. LIMITATION...Antibacterial Potential of Fermented Taro and its Development as a Food Preservative". This report covers the second part of the microbiology and food ... safety aspects of the project, the development of fermented taro as a food preservative and its incorporation into a developmental military food
Kelly, Patrick; Mapes, Brian; Hu, I-Kuan; ...
2017-04-03
This study describes a new intermediate global atmosphere model in which synoptic and planetary dynamics including the advection of water vapor are explicit, the time mean flow is centered near a realistic state through the calibration of time-independent 3D forcings, and temporal anomalies of convective tendencies of heat and moisture in each column are represented as a linear matrix acting on the anomalous temperature and moisture profiles in the GCM. This matrix was devised from Kuang’s [2010] linear response function (LRF) of a cooled cyclic convection-permitting model (CCPM) with 256 km periodic domain and 1km mesh, measured around an equilibriummore » state with a mean rainrate of 3.5 mm/d. The goal of this effort was to cleanly test the role of convection’s free-tropospheric moisture sensitivity in tropical waves, without incurring large changes of mean climate that confuse the interpretation of experiments with entrainment rates in the convection schemes of full-physics GCMs. As the sensitivity to free tropospheric moisture (columns 12-20 of the matrix, representing sensitivity to humidity above 900 hPa altitude) is multiplied by a factor ranging from 0 to 2, the model’s variability ranges from: (1) moderately strong convectively coupled waves with speeds near 20 m s -1; to (0) weak waves, but still slowed by convective coupling; to (2) wave variability that is greater in amplitude as the water vapor field plays an increasingly important role. Longitudinal structure in the model’s time-mean tropical flow is not fully realistic, and does change significantly with matrix edits, disappointing initial hopes that the Madden-Julian oscillation would be well simulated in the control and could be convincingly decomposed, but further work could improve this class of models.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kelly, Patrick; Mapes, Brian; Hu, I-Kuan
This study describes a new intermediate global atmosphere model in which synoptic and planetary dynamics including the advection of water vapor are explicit, the time mean flow is centered near a realistic state through the calibration of time-independent 3D forcings, and temporal anomalies of convective tendencies of heat and moisture in each column are represented as a linear matrix acting on the anomalous temperature and moisture profiles in the GCM. This matrix was devised from Kuang’s [2010] linear response function (LRF) of a cooled cyclic convection-permitting model (CCPM) with 256 km periodic domain and 1km mesh, measured around an equilibriummore » state with a mean rainrate of 3.5 mm/d. The goal of this effort was to cleanly test the role of convection’s free-tropospheric moisture sensitivity in tropical waves, without incurring large changes of mean climate that confuse the interpretation of experiments with entrainment rates in the convection schemes of full-physics GCMs. As the sensitivity to free tropospheric moisture (columns 12-20 of the matrix, representing sensitivity to humidity above 900 hPa altitude) is multiplied by a factor ranging from 0 to 2, the model’s variability ranges from: (1) moderately strong convectively coupled waves with speeds near 20 m s -1; to (0) weak waves, but still slowed by convective coupling; to (2) wave variability that is greater in amplitude as the water vapor field plays an increasingly important role. Longitudinal structure in the model’s time-mean tropical flow is not fully realistic, and does change significantly with matrix edits, disappointing initial hopes that the Madden-Julian oscillation would be well simulated in the control and could be convincingly decomposed, but further work could improve this class of models.« less
Potential for wind extraction from 4D-Var assimilation of aerosols and moisture
NASA Astrophysics Data System (ADS)
Zaplotnik, Žiga; Žagar, Nedjeljka
2017-04-01
We discuss the potential of the four-dimensional variational data assimilation (4D-Var) to retrieve the unobserved wind field from observations of atmospheric tracers and the mass field through internal model dynamics and the multivariate relationships in the background-error term for 4D-Var. The presence of non-linear moist dynamics makes the wind retrieval from tracers very difficult. On the other hand, it has been shown that moisture observations strongly influence both tropical and mid-latitude wind field in 4D-Var. We present an intermediate complexity model that describes nonlinear interactions between the wind, temperature, aerosols and moisture including their sinks and sources in the framework of the so-called first baroclinic mode atmosphere envisaged by A. Gill. Aerosol physical processes, which are included in the model, are the non-linear advection, diffusion and sources and sinks that exist as dry and wet deposition and diffusion. Precipitation is parametrized according to the Betts-Miller scheme. The control vector for 4D-Var includes aerosols, moisture and the three dynamical variables. The former is analysed univariately whereas wind field and mass field are analysed in a multivariate fashion taking into account quasi-geostrophic and unbalanced dynamics. The OSSE type of studies are performed for the tropical region to assess the ability of 4D-Var to extract wind-field information from the time series of observations of tracers as a function of the flow nonlinearity, the observations density and the length of the assimilation window (12 hours and 24 hours), in dry and moist environment. Results show that the 4D-Var assimilation of aerosols and temperature data is beneficial for the wind analysis with analysis errors strongly dependent on the moist processes and reliable background-error covariances.
Prediction of frozen food properties during freezing using product composition.
Boonsupthip, W; Heldman, D R
2007-06-01
Frozen water fraction (FWF), as a function of temperature, is an important parameter for use in the design of food freezing processes. An FWF-prediction model, based on concentrations and molecular weights of specific product components, has been developed. Published food composition data were used to determine the identity and composition of key components. The model proposed in this investigation had been verified using published experimental FWF data and initial freezing temperature data, and by comparison to outputs from previously published models. It was found that specific food components with significant influence on freezing temperature depression of food products included low molecular weight water-soluble compounds with molality of 50 micromol per 100 g food or higher. Based on an analysis of 200 high-moisture food products, nearly 45% of the experimental initial freezing temperature data were within an absolute difference (AD) of +/- 0.15 degrees C and standard error (SE) of +/- 0.65 degrees C when compared to values predicted by the proposed model. The predicted relationship between temperature and FWF for all analyzed food products provided close agreements with experimental data (+/- 0.06 SE). The proposed model provided similar prediction capability for high- and intermediate-moisture food products. In addition, the proposed model provided statistically better prediction of initial freezing temperature and FWF than previous published models.
Bonetti, Sara; Manoli, Gabriele; Domec, Jean-Christophe; ...
2015-03-16
Here, we report a mechanistic model for the soil-plant system is coupled to a conventional slab representation of the atmospheric boundary layer (ABL) to explore the role of groundwater table (WT) variations and free atmospheric (FA) states on convective rainfall predisposition (CRP) at a Loblolly pine plantation site situated in the lower coastal plain of North Carolina. Predisposition is quantified using the crossing between modeled lifting condensation level (LCL) and convectively grown ABL depth. The LCL-ABL depth crossing is necessary for air saturation but not sufficient for cloud formation and subsequent convective rainfall occurrence. However, such crossing forms the mainmore » template for which all subsequent dynamical processes regulating the formation (or suppression) of convective rainfall operate on. If the feedback between surface fluxes and FA conditions is neglected, a reduction in latent heat flux associated with reduced WT levels is shown to enhance the ABL-LCL crossing probability. When the soil-plant system is fully coupled with ABL dynamics thereby allowing feedback with ABL temperature and humidity, FA states remain the leading control on CRP. However, vegetation water stress plays a role in controlling ABL-LCL crossing when the humidity supply by the FA is within an intermediate range of values. When FA humidity supply is low, cloud formation is suppressed independent of surface latent heat flux. Similarly, when FA moisture supply is high, cloud formation can occur independent of surface latent heat flux. In an intermediate regime of FA moisture supply, the surface latent heat flux controlled by soil water availability can supplement (or suppress) the necessary water vapor leading to reduced LCL and subsequent ABL-LCL crossing. Lastly, it is shown that this intermediate state corresponds to FA values around the mode in observed humidity lapse rates γ w (between -2.5 × 10 -6 and -1.5 × 10 -6 kg kg -1m -1), suggesting that vegetation water uptake may be controlling CRP at the study site.« less
Competitive Advantage Market Analysis | Energy Analysis | NREL
Study An NREL market assessment of raw and intermediate materials, equipment, and products for equipment for c-Si PV Abundant raw materials for production of moisture barrier films, glass, aluminum
Validation of SMAP data using Cosmic-ray Neutron Probes during the SMAPVEX16-IA Campaign
NASA Astrophysics Data System (ADS)
Russell, M. V.
2016-12-01
Global trends in consumptive water-use indicate a growing and unsustainable reliance on water resources. Each year it is estimated that 60 percent of water used for agriculture is wasted through inadequate water conservation, losses in distribution, and inappropriate times and rates of irrigation. Satellite remote sensing offers a variety of water balance datasets (precipitation, evapotranspiration, soil moisture, groundwater storage) to increase the water use efficiency in agricultural systems. In this work, we aim to validate the Soil Moisture Active Passive (SMAP) soil moisture product using the ground based cosmic-ray neutron probe (CRNP) for estimating field scale soil moisture at intermediate spatial scales as part of SMAPVEX16-IA experiment. Typical SMAP calibration and validation has been done using a combination of direct gravimetric sampling and in-situ soil moisture point observations. Although these measurements provide accurate data, it is time consuming and labor intensive to collect data over a 36 by 36 km SMAP pixel. Through a joint effort with rovers provided by the US Army Corps of Engineers and University of Nebraska-Lincoln, we are able to cover the domain in 7 hours. Data from both rovers was combined in order to produce a 1, 3, 9 and 36 km resolution product on the day of 12 SMAP overpasses in May and August 2016. Here we will describe basic QAQC procedures for estimating soil moisture from the dual rover experiment. This will include discussion about calibration, validation, and accounting for conditions such as variable road type and growing vegetation. Lastly, we will compare the calibrated rover and SMAP products. If the products are highly correlated the ground based rovers offer a strategy for collecting finer resolution products that may be used in future downscaling efforts in support of high resolution Land Surface Modeling.
Rao, Qinchun; Fisher, Mary Catherine; Guo, Mufan; Labuza, Theodore P
2013-09-11
Quality loss in intermediate-moisture foods (IMF) such as high-protein nutrition bars (HPNB) in the form of hardening, nonenzymatic browning, and free amino group loss is a general concern for the manufacturers. To measure the extent of quality loss over time in terms of these negative attributes, through changing the ratio by weight between two commercial spray-dried hen egg powders, egg white (DEW) and egg yolk (DEY), the storage stability of 10 IMF systems (water activity (aw) ∼ 0.6) containing 5% glycerol, 10% shortening, 35% protein, and 50% sweetener (either maltitol or 50% high-fructose corn syrup/50% corn syrup (HFCS/CS)) were studied. Additionally, the storage stability of the DEY powder itself was investigated. Overall, during storage at different temperatures (23, 35, and 45 °C), the storage stability of DEY in dry and IMF matrices was mainly controlled by the coaction of three chemical reactions (disulfide bond interaction, Maillard reaction, and lipid oxidation). The results showed that by replacing 25% of DEW in an IMF model system with DEY, the rate of bar hardening was significantly lower than that of the models with only DEW at all temperatures due to the softening effect of the fat in DEY. Furthermore, the use of maltitol instead of HFCS/CS in all bar systems not only resulted in decreased hardness but also drastically decreased the change in the total color difference (ΔE*). Interestingly, there was no significant loss of free amino groups in the maltitol systems at any DEW/DEY ratio.
Trubyanov, Maxim M; Mochalov, Georgy M; Suvorov, Sergey S; Puzanov, Egor S; Petukhov, Anton N; Vorotyntsev, Ilya V; Vorotyntsev, Vladimir M
2018-07-27
The current study focuses on the processes involved during the flow conversion of water into acetylene in a calcium carbide reaction cell for the trace moisture analysis of ammonia by reaction gas chromatography. The factors negatively affecting the reproducibility and the accuracy of the measurements are suggested and discussed. The intramolecular reaction of the HOCaCCH intermediate was found to be a side reaction producing background acetylene during the contact of wet ammonia gas with calcium carbide. The presence of the HOCaCCH intermediate among the reaction products is confirmed by an FTIR spectral study of calcium carbide powder exposed to wet gas. The side reaction kinetics is evaluated experimentally and its influence on the results of the gas chromatographic measurements is discussed in relation to the determination of the optimal operating parameters for ammonia analysis. The reaction gas chromatography method for the trace moisture measurements in an ammonia matrix was experimentally compared to an FTIR long-path length gas cell technique to evaluate the accuracy limitations and the resource intensity. Copyright © 2018 Elsevier B.V. All rights reserved.
Storage Stability and Improvement of Intermediate Moisture Foods
NASA Technical Reports Server (NTRS)
Labuza, T. P.
1976-01-01
Shelf life tests are used to estimate the rate of nonenzymatic browning; however, controlling the reducing sugar levels below 23:1 molar ratio to amines, slows the rate. In addition, liquid glycols surpress browning. The protozoan Tetrahymena pyriformis W can be used to estimate nutrition losses during browning. At high temperatures (80 to 120 C) used in processing intermediate moisture foods (IMF), vitamin C destruction shifts to a zero order mechanism. BHA and BHT are the most effective antioxidants against rancidity. In shelf life testing however, 45 C should be the maximum temperature used. Water binding agents are studied. The five isotherms of thirteen humectants were determined. The results show that neither the method of addition nor sequence of addition affects the a sub u lowering ability of these humectants. Results were used to formulate shelf stable IMF processed cheese foods with at least four months shelf life.
Hu, Long; Shao, Gang; Jiang, Tao; Li, Dengbing; Lv, Xinlin; Wang, Hongya; Liu, Xinsheng; Song, Haisheng; Tang, Jiang; Liu, Huan
2015-11-18
Organometal halide perovskites have recently emerged as outstanding semiconductors for solid-state optoelectronic devices. Their sensitivity to moisture is one of the biggest barriers to commercialization. In order to identify the effect of moisture in the degradation process, here we combined the in situ electrical resistance measurement with time-resolved X-ray diffraction analysis to investigate the interaction of CH3NH3PbI(3-x)Cl(x) perovskite films with moisture. Upon short-time exposure, the resistance of the perovskite films decreased and it could be fully recovered, which were ascribed to a mere chemisorption of water molecules, followed by the reversible hydration into CH3NH3PbI(3-x)Cl(x)·H2O. Upon long-time exposure, however, the resistance became irreversible due to the decomposition into PbI2. The results demonstrated the formation of monohydrated intermediate phase when the perovskites interacted with moisture. The role of moisture in accelerating the thermal degradation at 85 °C was also demonstrated. Furthermore, our study suggested that the perovskite films with fewer defects may be more inherently resistant to moisture.
Geza, Mengistu; Lowe, Kathryn S; Huntzinger, Deborah N; McCray, John E
2013-07-01
Onsite wastewater treatment systems are commonly used in the United States to reclaim domestic wastewater. A distinct biomat forms at the infiltrative surface, causing resistance to flow and decreasing soil moisture below the biomat. To simulate these conditions, previous modeling studies have used a two-layer approach: a thin biomat layer (1-5 cm thick) and the native soil layer below the biomat. However, the effect of wastewater application extends below the biomat layer. We used numerical modeling supported by experimental data to justify a new conceptual model that includes an intermediate zone (IZ) below the biomat. The conceptual model was set up using Hydrus 2D and calibrated against soil moisture and water flux measurements. The estimated hydraulic conductivity value for the IZ was between biomat and the native soil. The IZ has important implications for wastewater treatment. When the IZ was not considered, a loading rate of 5 cm d resulted in an 8.5-cm ponding. With the IZ, the same loading rate resulted in a 9.5-cm ponding. Without the IZ, up to 3.1 cm d of wastewater could be applied without ponding; with the IZ, only up to 2.8 cm d could be applied without ponding. The IZ also plays a significant role in soil moisture distribution. Without the IZ, near-saturation conditions were observed only within the biomat, whereas near-saturation conditions extended below the biomat with the IZ. Accurate prediction of ponding is important to prevent surfacing of wastewater. The degree of water and air saturation influences pollutant treatment efficiency through residence time, volatility, and biochemical reactions. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.
Huart, F; Malumba, P; Odjo, S; Al-Izzi, W; Béra, F; Beckers, Y
2018-06-11
1. This study assessed the impact of drying temperature (54, 90, and 130°C) and maize grain moisture content at harvest (36% and 29%) on in vitro digestibility, the growth performance and ileal digestibility of broiler chickens. 2. In contrast to the results from the in vitro digestibility, apparent ileal digestibility of starch and energy decreased when the drying temperature was raised from 54 to 130°C, and this effect was more pronounced in maize grain harvested at high initial moisture content (36%). Ileal protein digestibility of maize grain decreased significantly when dried at the intermediate temperature (90°C) and with a high harvest moisture content (36%). Drying temperature and initial moisture content did not significantly affect AMEn. 3. When maize was dried at 130°C, the particle sizes of flour recovered after standard milling procedures decreased significantly, which would influence animal growth performance and in vivo digestibility through animal feed selection.
NASA Technical Reports Server (NTRS)
Sellers, Piers J.; Heiser, Mark D.; Hall, Forrest G.
1992-01-01
The relationship between surface conductance and spectral vegetation indices is investigated utilizing the FIFE data set, principally the surface flux station data and images from the TM instrument. It is found that the unstressed canopy conductance for a given site for a given day is near-linearly related to the incident PAR flux. Estimates of unstressed canopy conductance were acquired via a model inversion that separated the soil and vegetation contributions to evapotranspiration and made adjustments for the effects of vapor pressure deficit and soil moisture stress.
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.
On the role of circulation changes in future Northern Hemisphere hydroclimate change
NASA Astrophysics Data System (ADS)
Seager, R.; Ting, M.; Simpson, I.; Shaw, T.
2015-12-01
The "dry-get-drier, wet-get-wetter", otherwise known as "rich-get-richer, poor-get-poorer" concept of the hydrological cycle response to rising greenhouse gases was a major advance in terms of perception of climate change in the research community and the winder public. It provides a good description of hydroclimate change in many regions but especially over the oceans. Here there is a clear divide between wet regions, with positive precipitation minus evaporation (P-E), and dry regions with negative P-E. However over land, long term P-E is either zero or positive and balanced by streamflow and it is not so simple to divide between wet and dry regions. What is more, the simple wet-get-wetter, dry-get-drier paradigm is based only on thermodynamics with rising humidity causing increased amplitude of moisture convergence and moisture divergence and, hence, larger variations in P-E. It is now being realized more and more that changes in atmospheric circulation can also drive changes in moisture convergence/divergence and that a full explanation of hydrological cycle change requires attention to circulation change. This will be illustrated with reference to North America and the Mediterranean region. In both case changes in the mean circulation are important drivers of regional hydroclimate change. Model-projected North American hydroclimate change in winter is strongly influenced by a lengthening of the zonal scale of intermediate-scale stationary waves forced by extratropical heating. Wetting at the west coast, drying in the interior southwest and wetting at the US east coast are stronger in models that have a climatological wave field that exaggerates these waves than in models that have more realistic amplitude wave fields. Intense Mediterranean region drying in both summer and winter is also explained in part by shifts towards regional high pressure that, as of now, have not been fully explained. In neither southwest North America nor the Mediterranean, despite the importance of storm systems in delivering moisture to the regions, is projected drying caused by reduced transient eddy moisture convergence. Instead thermodynamic drying and mean flow changes share the responsibility for shifting the regions to drier, more water-stressed, climates.
USDA-ARS?s Scientific Manuscript database
Weather and management constraints, as well as the intended use of the harvested forage, all influence the forage harvest system selected by the producer. Generally, maximum retention of dry matter from harvested forage crops is achieved at moistures intermediate between the standing fresh crop and ...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Krishnan, P., E-mail: pkrishnan@iari.res.in; Singh, Ravender; Verma, A.P.S.
Highlights: • In developing soybean seeds, moisture stress resulted in more proportion of water to bound state. • These changes are further corroborated by concomitant changes in seed metabolites. • Thus there exists a moisture stress and development stage dependence of seed tissue water status. - Abstract: Changes in water status of developing seeds of Soybean (Glycine max L. Merrill.) grown under different moisture stress conditions were characterized by proton nuclear magnetic resonance (NMR)- spin–spin relaxation time (T{sub 2}). A comparison of the seed development characteristics, composition and physical properties indicated that, characteristics like seed weight, seed number/ear, rate ofmore » seed filling increased with development stages but decreased with moisture stress conditions. The NMR- spin–spin relaxation (T{sub 2}) component like bound water increased with seed maturation (40–50%) but decreased with moisture stress conditions (30–40%). The changes in seed water status to increasing levels of moisture stress and seed maturity indicates that moisture stress resulted in more proportion of water to bound state and intermediate state and less proportion of water in free-state. These changes are further corroborated by significant changes in protein and starch contents in seeds under high moisture stress treatments. Thus seed water status during its development is not only affected by development processes but also by moisture stress conditions. This study strongly indicated a clear moisture stress and development stage dependence of seed tissue water status in developing soybean seeds.« less
Mechanisms of survival, responses and sources of Salmonella in low-moisture environments
Finn, Sarah; Condell, Orla; McClure, Peter; Amézquita, Alejandro; Fanning, Séamus
2013-01-01
Some Enterobacteriaceae possess the ability to survive in low-moisture environments for extended periods of time. Many of the reported food-borne outbreaks associated with low-moisture foods involve Salmonella contamination. The control of Salmonella in low-moisture foods and their production environments represents a significant challenge for all food manufacturers. This review summarizes the current state of knowledge with respect to Salmonella survival in intermediate- and low-moisture food matrices and their production environments. The mechanisms utilized by this bacterium to ensure their survival in these dry conditions remain to be fully elucidated, however, in depth transcriptomic data is now beginning to emerge regarding this observation. Earlier research work described the effect(s) that low-moisture can exert on the long-term persistence and heat tolerance of Salmonella, however, data are also now available highlighting the potential cross-tolerance to other stressors including commonly used microbicidal agents. Sources and potential control measures to reduce the risk of contamination will be explored. By extending our understanding of these geno- and phenotypes, we may be able to exploit them to improve food safety and protect public health. PMID:24294212
Water content and the conversion of phytochrome regulation of lettuce dormancy
NASA Technical Reports Server (NTRS)
Vertucci, C. W.; Vertucci, F. A.; Leopold, A. C.
1987-01-01
In an effort to determine which biological reactions can occur in relation to the water content of seeds, the regulation of lettuce seed dormancy by red and far red light was determined at various hydration levels. Far red light had an inhibiting effect on germination for seeds at all moisture contents from 4 to 32% water. Germination was progressively stimulated by red light as seed hydration increased from 8 to 15%, and reached a maximum at moisture contents above 18%. Red light was ineffective at moisture contents below 8%. Seeds that had been stimulated by red light and subsequently dried lost the enhanced germinability if stored at moisture contents above 8%. The contrast between the presumed photoconversion of phytochrome far red-absorbing (Pfr) to (Pr) occurring at any moisture content and the reverse reaction occurring only if the seed moisture content is greater than 8% may be explained on the basis of the existence of unstable intermediates in the Pr to Pfr conversion. Our results suggest that the initial photoreaction involved in phytochrome conversion is relatively independent of water content, while the subsequent partial reactions become increasingly facilitated as water content increases from 8 to 18%.
Generation of monochloropropanediols (MCPDs) in model dough systems. 1. Leavened doughs.
Hamlet, Colin G; Sadd, Peter A; Gray, David A
2004-04-07
The effect of dough recipe ingredients and processing on the generation of monochloropropanediol isomers (MCPDs) in leavened wheat doughs has been investigated. Commercial ingredients having no effect on MCPD formation were acetic acid and baking fats (triacylglycerols). Ingredients making a significant contribution to MCPD levels were yeast and flour improver [ascorbic acid, diacetyl tartaric acid esters of mono- and diglycerides (DATEM), and soya flour]. The results showed that free glycerol is a key precursor of MCPDs in leavened doughs. This glycerol is primarily generated by the yeast during proving but is also present in the flour, the yeast, and the improver. Under conditions of high dough moisture content (45%), MCPD formation was approximately proportional to glycerol concentration but showed a weaker dependence on chloride level, suggesting that the mechanisms of formation involved at least some reversible stages. MCPD generation increased with decreasing dough moisture to a point where the formation reaction was limited by chloride solubility and competing reactions involving glycerol and key precursor intermediates. These results could be predicted by a kinetic model derived from the experimental data. Glycerol was shown to account for 68% of MCPDs generated in proved full recipe dough.
[Effect of moisture content on anaerobic methanization of municipal solid waste].
Qu, Xian; He, Pin-Jing; Shao, Li-Ming; Bouchez, Théodore
2009-03-15
Biogas production, gas and liquid characteristics were investigated for comparing the effect of moisture content on methanization process of MSW with different compositions of food waste and cellulosic waste. Batch reactors were used to study the anaerobic methanization of typical Chinese and French municipal solid waste (MSW) and cellulosic waste with different moisture content, as 35%, field capacity (65%-70%), 80%, and saturated state (> 95%). The results showed that for the typical Chinese and French waste, which contained putrescible waste, the intermediate product, VFA, was diluted by high content of water, which helped to release the VFA inhibition on hydrolysis and methanization. Mass amount of methane was produced only when the moisture content of typical French waste was higher than 80%, while higher content of moisture was needed when the content of putrescible waste was higher in MSW, as > 95% for typical Chinese waste. Meanwhile the methane production rate and the ultimate cumulated methane production were increased when moisture content was leveled up. The ultimate cumulated methane production of the typical French waste with saturated state was 0.6 times higher than that of the waste with moisture content of 80%. For cellulosic waste, high moisture content of cellulosic materials contributed to increase the attachment area of microbes and enzyme on the surface of the materials, which enhance the waste hydrolysis and methanization. When the moisture content of the cellulosic materials increased from field capacity (65%) to saturated state (> 95%), the ultimate cumulated methane production increased for 3.8 times.
NASA Astrophysics Data System (ADS)
Finkenbiner, Catherine; Franz, Trenton E.; Avery, William Alexander; Heeren, Derek M.
2016-04-01
Global trends in consumptive water use indicate a growing and unsustainable reliance on water resources. Approximately 40% of total food production originates from irrigated agriculture. With increasing crop yield demands, water use efficiency must increase to maintain a stable food and water trade. This work aims to increase our understanding of soil hydrologic fluxes at intermediate spatial scales. Fixed and roving cosmic-ray neutron probes were combined in order to characterize the spatial and temporal patterns of soil moisture at three study sites across an East-West precipitation gradient in the state of Nebraska, USA. A coarse scale map was generated for the entire domain (122 km2) at each study site. We used a simplistic data merging technique to produce a statistical daily soil moisture product at a range of key spatial scales in support of current irrigation technologies: the individual sprinkler (˜102m2) for variable rate irrigation, the individual wedge (˜103m2) for variable speed irrigation, and the quarter section (0.82 km2) for uniform rate irrigation. Additionally, we were able to generate a daily soil moisture product over the entire study area at various key modeling and remote sensing scales 12, 32, and 122 km2. Our soil moisture products and derived soil properties were then compared against spatial datasets (i.e. field capacity and wilting point) from the US Department of Agriculture Web Soil Survey. The results show that our "observed" field capacity was higher compared to the Web Soil Survey products. We hypothesize that our results, when provided to irrigators, will decrease water losses due to runoff and deep percolation as sprinkler managers can better estimate irrigation application depth and times in relation to soil moisture depletion below field capacity and above maximum allowable depletion. The incorporation of this non-contact and pragmatic geophysical method into current irrigation practices across the state and globe has the potential to greatly increase agricultural water use efficiency at scale.
DOT National Transportation Integrated Search
2017-02-01
The Utah Department of Transportation has implemented a program to test the rutting and moisture : sensitivity of Dense Grade Asphalt. Under this program, asphalt mixes have become much harder and dryer in an : effort to minimize rutting potential. T...
Rheological characteristics of intermediate moisture blends of pregelatinized and raw wheat starch.
Alavi, Sajid H; Chen, Kwan-Han; Rizvi, Syed S H
2002-11-06
Rheological properties of intermediate moisture (35-45% wet basis) doughs from pregelatinized and raw wheat starch blends of various ratios were characterized using off-line capillary rheometry and online slit-die extrusion. In the case of capillary rheometer, viscosity of blends decreased by up to 50% as pregel starch concentration increased from 5 to 45%, whereas tests could not be conducted beyond 45% pregel starch concentration. For slit-die extrusion, viscosity was at a minimum at 60% pregel concentration, and it decreased by as much as 65% as pregel concentration increased from 0 to 60%. As pregel concentration increased (from 5 to 45% for the rheometer and from 0 to 60% for the extruder), the amount of water available in the system for gelatinization of existing raw starch granules decreased due to the stronger water-binding capacity of pregelatinized starch. This led to decreased additional conversion in the rheometer and extruder, which in turn caused a decrease in the volume fraction of starch and a reduction in viscosity.
NASA Astrophysics Data System (ADS)
Trifonov, N. N.; Kovalenko, E. V.; Nikolaenkova, E. K.; Tren'kin, V. B.
2012-09-01
The intermediate separation and steam reheating system and its equipment are described. Problems concerned with the presence of condensate in the stack's lower chamber and in the removing chamber, with cavitation failure of the separated moisture pumps, with misalignment of heating steam flowrates, with unstable draining of heating steam condensate, with occurrence of self oscillations, etc. are considered. A procedure for determining the level in removing heating steam condensate from steam reheater elements is proposed. Technical solutions for ensuring stable operation of the intermediate separation and steam reheating system and for achieving smaller misalignment between the apparatuses are developed.
NASA Astrophysics Data System (ADS)
Illangasekare, T. H.; Sakaki, T.; Smits, K. M.; Limsuwat, A.; Terrés-Nícoli, J. M.
2008-12-01
Understanding the dynamics of soil moisture distribution near the ground surface is of interest in various applications involving land-atmospheric interaction, evaporation from soils, CO2 leakage from carbon sequestration, vapor intrusion into buildings, and land mine detection. Natural soil heterogeneity in combination with water and energy fluxes at the soil surface creates complex spatial and temporal distributions of soil moisture. Even though considerable knowledge exists on how soil moisture conditions change in response to flux and energy boundary conditions, emerging problems involving land atmospheric interactions require the quantification of soil moisture variability both at high spatial and temporal resolutions. The issue of up-scaling becomes critical in all applications, as in general, field measurements are taken at sparsely distributed spatial locations that require assimilation with measurements taken using remote sensing technologies. It is our contention that the knowledge that will contribute to both improving our understanding of the fundamental processes and practical problem solution cannot be obtained easily in the field due to a number of constraints. One of these basic constraints is the inability to make measurements at very fine spatial scales at high temporal resolutions in naturally heterogeneous field systems. Also, as the natural boundary conditions at the land/atmospheric interface are not controllable in the field, even in pilot scale studies, the developed theories and tools cannot be validated for the diversity of conditions that could be expected in the field. Intermediate scale testing using soil tanks packed to represent different heterogeneous test configurations provides an attractive and cost effective alternative to investigate a class of problems involving the shallow unsaturated zone. In this presentation, we will discuss the advantages and limitations of studies conducted in both two and three dimensional intermediate scale test systems together with instrumentation and measuring techniques. The features and capabilities of a new coupled porous media/climate wind tunnel test system that allows for the study of near surface unsaturated soil moisture conditions under climate boundary conditions will also be presented with the goal of exploring opportunities to use such a facility to study some of the multi-scale problems in the near surface unsaturated zone.
COSMOS: COsmic-ray Soil Moisture Observing System planned for the United States
NASA Astrophysics Data System (ADS)
Zweck, C.; Zreda, M.; Shuttleworth, J.; Zeng, X.
2008-12-01
Because soil water exerts a critical control on weather, climate, ecosystem, and water cycle, understanding soil moisture changes in time and space is crucial for many fields within natural sciences. A serious handicap in soil moisture measurements is the mismatch between limited point measurements using contact methods and remote sensing estimates over large areas. We present a novel method to measure soil moisture non- invasively at an intermediate spatial scale that will alleviate this problem. The method takes advantage of the dependence of cosmic-ray neutron intensity on the hydrogen content of soils (Zreda et al., Geophysical Research Letters, accepted). Low-energy cosmic-ray neutrons are produced and moderated in the soil, transported from the soil into the atmosphere where they are measured with a cosmic-ray neutron probe to provide integrated soil moisture content over a footprint of several hundred meters and a depth of a few decimeters. The method and the instrument are intended for deployment in the continental-scale COSMOS network that is designed to cover the contiguous region of the USA. Fully deployed, the COSMOS network will consist of up to 500 probes, and will provide continuous soil moisture content (together with atmospheric pressure, temperature and relative humidity) measured and reported hourly. These data will be used for initialization and assimilation of soil moisture conditions in weather and short-term (seasonal) climate forecasting, and for other land-surface applications.
NASA Astrophysics Data System (ADS)
Quiquet, Aurélien; Roche, Didier M.; Dumas, Christophe; Paillard, Didier
2018-02-01
This paper presents the inclusion of an online dynamical downscaling of temperature and precipitation within the model of intermediate complexity iLOVECLIM v1.1. We describe the following methodology to generate temperature and precipitation fields on a 40 km × 40 km Cartesian grid of the Northern Hemisphere from the T21 native atmospheric model grid. Our scheme is not grid specific and conserves energy and moisture in the same way as the original climate model. We show that we are able to generate a high-resolution field which presents a spatial variability in better agreement with the observations compared to the standard model. Although the large-scale model biases are not corrected, for selected model parameters, the downscaling can induce a better overall performance compared to the standard version on both the high-resolution grid and on the native grid. Foreseen applications of this new model feature include the improvement of ice sheet model coupling and high-resolution land surface models.
Stochastic Analysis and Probabilistic Downscaling of Soil Moisture
NASA Astrophysics Data System (ADS)
Deshon, J. P.; Niemann, J. D.; Green, T. R.; Jones, A. S.
2017-12-01
Soil moisture is a key variable for rainfall-runoff response estimation, ecological and biogeochemical flux estimation, and biodiversity characterization, each of which is useful for watershed condition assessment. These applications require not only accurate, fine-resolution soil-moisture estimates but also confidence limits on those estimates and soil-moisture patterns that exhibit realistic statistical properties (e.g., variance and spatial correlation structure). The Equilibrium Moisture from Topography, Vegetation, and Soil (EMT+VS) model downscales coarse-resolution (9-40 km) soil moisture from satellite remote sensing or land-surface models to produce fine-resolution (10-30 m) estimates. The model was designed to produce accurate deterministic soil-moisture estimates at multiple points, but the resulting patterns do not reproduce the variance or spatial correlation of observed soil-moisture patterns. The primary objective of this research is to generalize the EMT+VS model to produce a probability density function (pdf) for soil moisture at each fine-resolution location and time. Each pdf has a mean that is equal to the deterministic soil-moisture estimate, and the pdf can be used to quantify the uncertainty in the soil-moisture estimates and to simulate soil-moisture patterns. Different versions of the generalized model are hypothesized based on how uncertainty enters the model, whether the uncertainty is additive or multiplicative, and which distributions describe the uncertainty. These versions are then tested by application to four catchments with detailed soil-moisture observations (Tarrawarra, Satellite Station, Cache la Poudre, and Nerrigundah). The performance of the generalized models is evaluated by comparing the statistical properties of the simulated soil-moisture patterns to those of the observations and the deterministic EMT+VS model. The versions of the generalized EMT+VS model with normally distributed stochastic components produce soil-moisture patterns with more realistic statistical properties than the deterministic model. Additionally, the results suggest that the variance and spatial correlation of the stochastic soil-moisture variations do not vary consistently with the spatial-average soil moisture.
Figueroa, Yetzury; Guevara, Marvilan; Pérez, Adriana; Cova, Aura; Sandoval, Aleida J; Müller, Alejandro J
2016-08-01
This work studies how sucrose (S) addition modifies the thermal properties of cassava starch (CS). Neat CS and CS-S blends with 4, 6 and 8% sugar contents (CS-S-4%, CS-S-6% and CS-S-8%) were prepared and analyzed by differential scanning calorimetry (DSC) and dynamic mechanical thermal analysis (DMTA), in a wide range of moisture levels (2-20%). In equilibrated samples with moisture contents lower than 10%, twoendothermic steps were observed during first DSC heating scans and two corresponding relaxation maxima in tan δ were detected by DMTA. The first transition, detected at around 45-55°C by both DSC and DMTA, is frequently found in starchy foods, while the second observed at higher temperatures is associated to the glass transition temperature of the blends. At higher moisture contents, only one thermal transition was observed. Samples analyzed immediately after cooling from the melt (i.e., after erasing their thermal history), exhibited a single glass transition temperature, regardless of their moisture content. Addition of sugar promotes water plasticization of CS only at high moisture contents. In the low moisture content range, anti-plasticization was observed for both neat and sugar-added CS samples. Addition of sugar decreases the moisture content needed to achieve the maximum value of the glass transition temperature before plasticization starts. The results of this work may be valuable for the study of texture establishment in low moisture content extruded food products. Copyright © 2016 Elsevier Ltd. All rights reserved.
Limits and dynamics of methane oxidation in landfill cover soils
USDA-ARS?s Scientific Manuscript database
In order to understand the limits and dynamics of methane (CH4) oxidation in landfill cover soils, we investigated CH4 oxidation in daily, intermediate, and final cover soils from two California landfills as a function of temperature, soil moisture and CO2 concentration. The results indicate a signi...
Thinning increases climatic resilience of red pine
Matthew Magruder; Sophan Chhin; Brian Palik; John B. Bradford
2013-01-01
Forest management techniques such as intermediate stand-tending practices (e.g., thinning) can promote climatic resiliency in forest stands by moderating tree competition. Residual trees gain increased access to environmental resources (i.e., soil moisture, light), which in turn has the potential to buffer trees from stressful climatic conditions. The influences of...
An Analysis of Moisture Fluxes into the Gulf of California
NASA Technical Reports Server (NTRS)
Wu, Man-Li C.; Schubert, Siegfried D.; Suarez, Max J.; Huang, Norden E.
2009-01-01
This study examines the nature of episodes of enhanced warm-season moisture flux into the Gulf of California. Both spatial structure and primary time scales of the fluxes are examined using the 40-yr ECMWF Re-Analysis data for the period 1980-2001. The analysis approach consists of a compositing technique that is keyed on the low-level moisture fluxes into the Gulf of California. The results show that the fluxes have a rich spectrum of temporal variability, with periods of enhanced transport over the gulf linked to African easterly waves on subweekly (3-8 day) time scales, the Madden-Julian oscillation (MJO) at intraseasonal time scales (20-90 day), and intermediate (10-15 day) time-scale disturbances that appear to originate primarily in the Caribbean Sea-western Atlantic Ocean. In the case of the MJO, enhanced low-level westerlies and large-scale rising motion provide an environment that favors large-scale cyclonic development near the west coast of Central America that, over the course of about 2 weeks, expands northward along the coast eventually reaching the mouth of the Gulf of California where it acts to enhance the southerly moisture flux in that region. On a larger scale, the development includes a northward shift in the eastern Pacific ITCZ, enhanced precipitation over much of Mexico and the southwestern United States, and enhanced southerly/southeasterly fluxes from the Gulf of Mexico into Mexico and the southwestern and central United States. In the case of the easterly waves, the systems that reach Mexico appear to redevelop/reorganize on the Pacific coast and then move rapidly to the northwest to contribute to the moisture flux into the Gulf of California. The most intense fluxes into the gulf on these time scales appear to be synchronized with a midlatitude short-wave trough over the U.S. West Coast and enhanced low-level southerly fluxes over the U.S. Great Plains. The intermediate (10-15 day) time-scale systems have zonal wavelengths roughly twice that of the easterly waves, and their initiation appears to be linked to an extratropical U.S. East Coast ridge and associated northeasterly winds that extend well into the Caribbean Sea during their development phase. The short (3-8 day) and, to a lesser extent, the intermediate (10-15 day) time-scale fluxes tend to be enhanced when the convectively active phase of the MJO is situated over the Americas.
Partial dehydration and cryopreservation of Citrus seeds.
Graiver, Natalia; Califano, Alicia; Zaritzky, Noemí
2011-11-01
Three categories of seed storage behavior are generally recognized among plant species: orthodox, intermediate and recalcitrant. Intermediate seeds cannot be stored in liquid nitrogen (LN) without a previous partial dehydration process. The water content (WC) of the seeds at the moment of immersion in LN must be regarded as the most critical factor in cryopreservation. The purpose of this study was to investigate the basis of the optimal hydration status for cryopreservation of Citrus seeds: C. sinensis (sweet orange), C. paradisi (grapefruit), C. reticulata (mandarin) in LN. To study the tolerance to dehydration and LN exposure, seeds were desiccated by equilibration at relative humidities between 11 and 95%. Sorption isotherms were determined and modeled; lipid content of the seeds was measured. Seed desiccation sensitivity was quantified by the quantal response model. Differential scanning calorimetry (DSC) thermograms were determined on cotyledon tissue at different moisture contents to measure ice melting enthalpies and unfrozen WC. Samples of total seed lipid extract were also analyzed by DSC to identify lipid transitions in the thermograms. The limit of hydration for LN Citrus seeds treatment corresponded to the unfrozen WC in the tissue, confirming that seed survival strictly depended on avoidance of intracellular ice formation. Copyright © 2011 Society of Chemical Industry.
NASA Astrophysics Data System (ADS)
Henneberg, Olga; Ament, Felix; Grützun, Verena
2018-05-01
Soil moisture amount and distribution control evapotranspiration and thus impact the occurrence of convective precipitation. Many recent model studies demonstrate that changes in initial soil moisture content result in modified convective precipitation. However, to quantify the resulting precipitation changes, the chaotic behavior of the atmospheric system needs to be considered. Slight changes in the simulation setup, such as the chosen model domain, also result in modifications to the simulated precipitation field. This causes an uncertainty due to stochastic variability, which can be large compared to effects caused by soil moisture variations. By shifting the model domain, we estimate the uncertainty of the model results. Our novel uncertainty estimate includes 10 simulations with shifted model boundaries and is compared to the effects on precipitation caused by variations in soil moisture amount and local distribution. With this approach, the influence of soil moisture amount and distribution on convective precipitation is quantified. Deviations in simulated precipitation can only be attributed to soil moisture impacts if the systematic effects of soil moisture modifications are larger than the inherent simulation uncertainty at the convection-resolving scale. We performed seven experiments with modified soil moisture amount or distribution to address the effect of soil moisture on precipitation. Each of the experiments consists of 10 ensemble members using the deep convection-resolving COSMO model with a grid spacing of 2.8 km. Only in experiments with very strong modification in soil moisture do precipitation changes exceed the model spread in amplitude, location or structure. These changes are caused by a 50 % soil moisture increase in either the whole or part of the model domain or by drying the whole model domain. Increasing or decreasing soil moisture both predominantly results in reduced precipitation rates. Replacing the soil moisture with realistic fields from different days has an insignificant influence on precipitation. The findings of this study underline the need for uncertainty estimates in soil moisture studies based on convection-resolving models.
NASA Astrophysics Data System (ADS)
Fiorella, R.; Poulsen, C. J.; Matheny, A. M.; Rey Sanchez, C.; Fotis, A. T.; Morin, T. H.; Vogel, C. S.; Gough, C. M.; Aron, P.; Bohrer, G.
2016-12-01
Forest structure, age, and species composition modulate fluxes of carbon and water between the land surface and the atmosphere. The response of forests to intermediate disturbances such as ecological succession, species-specific insect invasion, or selective logging that disrupt the canopy but do not promote complete stand replacement, shape how these fluxes evolve through time. We investigate the impact of an intermediate disturbance to water cycling processes by comparing vertical profiles of stable water isotopes in two closely located forest canopies in the northern lower peninsula of Michigan using cavity ring-down spectroscopy. In one of the canopies, an intermediate disturbance was prescribed in 2008 by inducing mortality in all canopy-dominant early successional species. Isotopic compositions of atmospheric water vapor are measured at six heights during two time periods (summer and early fall) at two flux towers and compared with local meteorology and calculated atmospheric back-trajectories. Disturbance has little impact on low-frequency changes in isotopic composition (e.g., >1 day); at these timescales, isotopic composition is strongly related to large-scale moisture transport. In contrast, disturbance has substantial impacts on the vertical distribution of water isotopes throughout the canopy when transpiration rates are high during the summer, but impact is muted during early fall. Sub-diurnal differences in canopy water vapor cycling are likely related to differences in species composition and response to disturbance and changes in canopy structure. Predictions of transpiration fluxes by land-surface models that do not account species-specific relationships and canopy structure are unlikely to capture these relationships, but addition of stable isotopes to land surface models may provide a useful parameter to improve these predictions.
A comparison of 3 models of 1-hr timelag fuel moisture in Hawaii
D.R. Weise; F.M. Fujioka; R.M. Nelson
2005-01-01
The U.S. National Fire Danger Rating System currently uses a moisture diffusion model developed by Fosberg to predict fine fuel moisture in woody fuels. Nelson recently developed a fuel moisture model that includes functions for both heat and moisture transfer. Fuel moisture samples were collected in Hawaii hourly for up to 96 h for three litter, one herbaceous, and...
Rousk, Kathrin; Michelsen, Anders
2017-04-01
Nitrogen (N) fixation in moss-associated cyanobacteria is one of the main sources of available N for N-limited ecosystems such as subarctic tundra. Yet, N 2 fixation in mosses is strongly influenced by soil moisture and temperature. Thus, temporal scaling up of low-frequency in situ measurements to several weeks, months or even the entire growing season without taking into account changes in abiotic conditions cannot capture the variation in moss-associated N 2 fixation. We therefore aimed to estimate moss-associated N 2 fixation throughout the snow-free period in subarctic tundra in field experiments simulating climate change: willow (Salix myrsinifolia) and birch (Betula pubescens spp. tortuosa) litter addition, and warming. To achieve this, we established relationships between measured in situ N 2 fixation rates and soil moisture and soil temperature and used high-resolution measurements of soil moisture and soil temperature (hourly from May to October) to model N 2 fixation. The modelled N 2 fixation rates were highest in the warmed (2.8 ± 0.3 kg N ha -1 ) and birch litter addition plots (2.8 ± 0.2 kg N ha -1 ), and lowest in the plots receiving willow litter (1.6 ± 0.2 kg N ha -1 ). The control plots had intermediate rates (2.2 ± 0.2 kg N ha -1 ). Further, N 2 fixation was highest during the summer in the warmed plots, but was lowest in the litter addition plots during the same period. The temperature and moisture dependence of N 2 fixation was different between the climate change treatments, indicating a shift in the N 2 fixer community. Our findings, using a combined empirical and modelling approach, suggest that a longer snow-free period and increased temperatures in a future climate will likely lead to higher N 2 fixation rates in mosses. Yet, the consequences of increased litter fall on moss-associated N 2 fixation due to shrub expansion in the Arctic will depend on the shrub species' litter traits. © 2016 John Wiley & Sons Ltd.
Anomalous swelling behavior of FM 5055 carbon phenolic composite
NASA Technical Reports Server (NTRS)
Stokes, E. H.
1992-01-01
The swelling response of a typical carbon phenolic composite was measured in the three primary material directions. The data obtained sugrest that at low and high relative humidities the incremental increase in moisture absorption can be attributed primarily to the resin. At intermediate relative humidities, the water is moving largely into the carbonized fibers.
Soil CO2 efflux from two mountain forests in the eastern Himalayas, Bhutan: components and controls
NASA Astrophysics Data System (ADS)
Wangdi, Norbu; Mayer, Mathias; Prasad Nirola, Mani; Zangmo, Norbu; Orong, Karma; Uddin Ahmed, Iftekhar; Darabant, Andras; Jandl, Robert; Gratzer, Georg; Schindlbacher, Andreas
2017-01-01
The biogeochemistry of mountain forests in the Hindu Kush Himalaya range is poorly studied, although climate change is expected to disproportionally affect the region. We measured the soil CO2 efflux (Rs) at a high-elevation (3260 m) mixed forest and a lower-elevation (2460 m) broadleaf forest in Bhutan, eastern Himalayas, during 2015. Trenching was applied to estimate the contribution of autotrophic (Ra) and heterotrophic (Rh) soil respiration. The temperature (Q10) and the moisture sensitivities of Rh were determined under controlled laboratory conditions and were used to model Rh in the field. The higher-elevation mixed forest had a higher standing tree stock, reflected in higher soil C stocks and basal soil respiration. Annual Rs was similar between the two forest sites (14.5 ± 1.2 t C ha-1 for broadleaf; 12.8 ± 1.0 t C ha-1 for mixed). Modelled annual contribution of Rh was ˜ 65 % of Rs at both sites with a higher heterotrophic contribution during winter and lower contribution during the monsoon season. Rh, estimated from trenching, was in the range of modelled Rh but showed higher temporal variability. The measured temperature sensitivity of Rh was similar at the mixed and broadleaf forest sites (Q10 2.2-2.3) under intermediate soil moisture but decreased (Q10 1.5 at both sites) in dry soil. Rs closely followed the annual course of field soil temperature at both sites. Covariation between soil temperature and moisture (cold dry winters and warm wet summers) was likely the main cause for this close relationship. Under the prevailing weather conditions, a simple temperature-driven model was able to explain more than 90 % of the temporal variation in Rs. A longer time series and/or experimental climate manipulations are required to understand the effects of eventually occurring climate extremes such as monsoon failures.
NASA Soil Moisture Data Products and Their Incorporation in DREAM
NASA Technical Reports Server (NTRS)
Blonski, Slawomir; Holland, Donald; Henderson, Vaneshette
2005-01-01
NASA provides soil moisture data products that include observations from the Advanced Microwave Scanning Radiometer on the Earth Observing System Aqua satellite, field measurements from the Soil Moisture Experiment campaigns, and model predictions from the Land Information System and the Goddard Earth Observing System Data Assimilation System. Incorporation of the NASA soil moisture products in the Dust Regional Atmospheric Model is possible through use of the satellite observations of soil moisture to set initial conditions for the dust simulations. An additional comparison of satellite soil moisture observations with mesoscale atmospheric dynamics modeling is recommended. Such a comparison would validate the use of NASA soil moisture data in applications and support acceptance of satellite soil moisture data assimilation in weather and climate modeling.
Liao, C M; Liang, H M
2000-05-01
Two models for evaluating the contents and advection of manure moisture on odor causing volatile organic compounds (VOC-odor) volatilization from stored swine manure were studied for their ability to predict the volatilization rate (indoor air concentration) and cumulative exposure dose: a MJ-I model and a MJ-II model. Both models simulating depletion of source contaminant via volatilization and degradation based on an analytical model adapted from the behavior assessment model of Jury et al. In the MJ-I model, manure moisture movement was negligible, whereas in the MJ-II model, time-dependent indoor air concentrations was a function of constant manure moisture contents and steady-state moisture advection. Predicted indoor air concentrations and inhaled doses for the study VOC-odors of p-cresol, toluene, and p-xylene varied by up to two to three orders of magnitude depending on the manure moisture conditions. The sensitivity analysis of both models suggests that when manure moisture movement exists, simply MJ-I model is inherently not sufficient to represent a more generally volatilization process, which can even become stringent as moisture content increases. The conclusion illustrates how one needs to include a wide variety of manure moisture values in order to fully assess the complex volatilization mechanisms that are present in a real situation.
Examination of Soil Moisture Retrieval Using SIR-C Radar Data and a Distributed Hydrological Model
NASA Technical Reports Server (NTRS)
Hsu, A. Y.; ONeill, P. E.; Wood, E. F.; Zion, M.
1997-01-01
A major objective of soil moisture-related hydrological-research during NASA's SIR-C/X-SAR mission was to determine and compare soil moisture patterns within humid watersheds using SAR data, ground-based measurements, and hydrologic modeling. Currently available soil moisture-inversion methods using active microwave data are only accurate when applied to bare and slightly vegetated surfaces. Moreover, as the surface dries down, the number of pixels that can provide estimated soil moisture by these radar inversion methods decreases, leading to less accuracy and, confidence in the retrieved soil moisture fields at the watershed scale. The impact of these errors in microwave- derived soil moisture on hydrological modeling of vegetated watersheds has yet to be addressed. In this study a coupled water and energy balance model operating within a topographic framework is used to predict surface soil moisture for both bare and vegetated areas. In the first model run, the hydrological model is initialized using a standard baseflow approach, while in the second model run, soil moisture values derived from SIR-C radar data are used for initialization. The results, which compare favorably with ground measurements, demonstrate the utility of combining radar-derived surface soil moisture information with basin-scale hydrological modeling.
Multiscale soil moisture estimates using static and roving cosmic-ray soil moisture sensors
NASA Astrophysics Data System (ADS)
McJannet, David; Hawdon, Aaron; Baker, Brett; Renzullo, Luigi; Searle, Ross
2017-12-01
Soil moisture plays a critical role in land surface processes and as such there has been a recent increase in the number and resolution of satellite soil moisture observations and the development of land surface process models with ever increasing resolution. Despite these developments, validation and calibration of these products has been limited because of a lack of observations on corresponding scales. A recently developed mobile soil moisture monitoring platform, known as the rover
, offers opportunities to overcome this scale issue. This paper describes methods, results and testing of soil moisture estimates produced using rover surveys on a range of scales that are commensurate with model and satellite retrievals. Our investigation involved static cosmic-ray neutron sensors and rover surveys across both broad (36 × 36 km at 9 km resolution) and intensive (10 × 10 km at 1 km resolution) scales in a cropping district in the Mallee region of Victoria, Australia. We describe approaches for converting rover survey neutron counts to soil moisture and discuss the factors controlling soil moisture variability. We use independent gravimetric and modelled soil moisture estimates collected across both space and time to validate rover soil moisture products. Measurements revealed that temporal patterns in soil moisture were preserved through time and regression modelling approaches were utilised to produce time series of property-scale soil moisture which may also have applications in calibration and validation studies or local farm management. Intensive-scale rover surveys produced reliable soil moisture estimates at 1 km resolution while broad-scale surveys produced soil moisture estimates at 9 km resolution. We conclude that the multiscale soil moisture products produced in this study are well suited to future analysis of satellite soil moisture retrievals and finer-scale soil moisture models.
Soil moisture dynamics modeling considering multi-layer root zone.
Kumar, R; Shankar, V; Jat, M K
2013-01-01
The moisture uptake by plant from soil is a key process for plant growth and movement of water in the soil-plant system. A non-linear root water uptake (RWU) model was developed for a multi-layer crop root zone. The model comprised two parts: (1) model formulation and (2) moisture flow prediction. The developed model was tested for its efficiency in predicting moisture depletion in a non-uniform root zone. A field experiment on wheat (Triticum aestivum) was conducted in the sub-temperate sub-humid agro-climate of Solan, Himachal Pradesh, India. Model-predicted soil moisture parameters, i.e., moisture status at various depths, moisture depletion and soil moisture profile in the root zone, are in good agreement with experiment results. The results of simulation emphasize the utility of the RWU model across different agro-climatic regions. The model can be used for sound irrigation management especially in water-scarce humid, temperate, arid and semi-arid regions and can also be integrated with a water transport equation to predict the solute uptake by plant biomass.
Li, Ming Ze; Gao, Yuan Ke; Di, Xue Ying; Fan, Wen Yi
2016-03-01
The moisture content of forest surface soil is an important parameter in forest ecosystems. It is practically significant for forest ecosystem related research to use microwave remote sensing technology for rapid and accurate estimation of the moisture content of forest surface soil. With the aid of TDR-300 soil moisture content measuring instrument, the moisture contents of forest surface soils of 120 sample plots at Tahe Forestry Bureau of Daxing'anling region in Heilongjiang Province were measured. Taking the moisture content of forest surface soil as the dependent variable and the polarization decomposition parameters of C band Quad-pol SAR data as independent variables, two types of quantitative estimation models (multilinear regression model and BP-neural network model) for predicting moisture content of forest surface soils were developed. The spatial distribution of moisture content of forest surface soil on the regional scale was then derived with model inversion. Results showed that the model precision was 86.0% and 89.4% with RMSE of 3.0% and 2.7% for the multilinear regression model and the BP-neural network model, respectively. It indicated that the BP-neural network model had a better performance than the multilinear regression model in quantitative estimation of the moisture content of forest surface soil. The spatial distribution of forest surface soil moisture content in the study area was then obtained by using the BP neural network model simulation with the Quad-pol SAR data.
NASA Technical Reports Server (NTRS)
Hildreth, W. W.
1978-01-01
A determination of the state of the art in soil moisture transport modeling based on physical or physiological principles was made. It was found that soil moisture models based on physical principles have been under development for more than 10 years. However, these models were shown to represent infiltration and redistribution of soil moisture quite well. Evapotranspiration has not been as adequately incorporated into the models.
Jiang, Yuhui; Shang, Yixuan; Yu, Shuyao; Liu, Jianguo
2018-01-01
Hexachlorobenzene (HCB) contamination of soils remains a significant environmental challenge all over the world. Reductive stabilization is a developing technology that can decompose the HCB with a dechlorination process. A nanometallic Al/CaO (n-Al/CaO) dispersion mixture was developed utilizing ball-milling technology in this study. The dechlorination efficiency of HCB in contaminated soils by the n-Al/CaO grinding treatment was evaluated. Response surface methodology (RSM) was employed to investigate the effects of three variables (soil moisture content, n-Al/CaO dosage and grinding time) and the interactions between these variables under the Box-Behnken Design (BBD). A high regression coefficient value (R2 = 0.9807) and low p value (<0.0001) of the quadratic model indicated that the model was accurate in predicting the experimental results. The optimal soil moisture content, n-Al/CaO dosage, and grinding time were found to be 7% (m/m), 17.7% (m/m), and 24 h, respectively, in the experimental ranges and levels. Under optimal conditions, the dechlorination efficiency was 80%. The intermediate product analysis indicated that dechlorination was the process by stepwise loss of chloride atoms. The main pathway observed within 24 h was HCB → pentachlorobenzene (PeCB) → 1,2,3,4-tetrachlorobenzene (TeCB) and 1,2,4,5-TeCB. The results indicated that the moderate soil moisture content was crucial for the hydrodechlorination of HCB. A probable mechanism was proposed wherein water acted like a hydrogen donor and promoted the hydrodechlorination process. The potential application of n-Al/CaO is an environmentally-friendly and cost-effective option for decontamination of HCB-contaminated soils. PMID:29702570
NASA Astrophysics Data System (ADS)
Smits, K. M.; Sakaki, T.; Limsuwat, A.; Illangasekare, T. H.
2009-05-01
It is widely recognized that liquid water, water vapor and temperature movement in the subsurface near the land/atmosphere interface are strongly coupled, influencing many agricultural, biological and engineering applications such as irrigation practices, the assessment of contaminant transport and the detection of buried landmines. In these systems, a clear understanding of how variations in water content, soil drainage/wetting history, porosity conditions and grain size affect the soil's thermal behavior is needed, however, the consideration of all factors is rare as very few experimental data showing the effects of these variations are available. In this study, the effect of soil moisture, drainage/wetting history, and porosity on the thermal conductivity of sandy soils with different grain sizes was investigated. For this experimental investigation, several recent sensor based technologies were compiled into a Tempe cell modified to have a network of sampling ports, continuously monitoring water saturation, capillary pressure, temperature, and soil thermal properties. The water table was established at mid elevation of the cell and then lowered slowly. The initially saturated soil sample was subjected to slow drainage, wetting, and secondary drainage cycles. After liquid water drainage ceased, evaporation was induced at the surface to remove soil moisture from the sample to obtain thermal conductivity data below the residual saturation. For the test soils studied, thermal conductivity increased with increasing moisture content, soil density and grain size while thermal conductivity values were similar for soil drying/wetting behavior. Thermal properties measured in this study were then compared with independent estimates made using empirical models from literature. These soils will be used in a proposed set of experiments in intermediate scale test tanks to obtain data to validate methods and modeling tools used for landmine detection.
Jiang, Yuhui; Shang, Yixuan; Yu, Shuyao; Liu, Jianguo
2018-04-27
Hexachlorobenzene (HCB) contamination of soils remains a significant environmental challenge all over the world. Reductive stabilization is a developing technology that can decompose the HCB with a dechlorination process. A nanometallic Al/CaO (n-Al/CaO) dispersion mixture was developed utilizing ball-milling technology in this study. The dechlorination efficiency of HCB in contaminated soils by the n-Al/CaO grinding treatment was evaluated. Response surface methodology (RSM) was employed to investigate the effects of three variables (soil moisture content, n-Al/CaO dosage and grinding time) and the interactions between these variables under the Box-Behnken Design (BBD). A high regression coefficient value ( R ² = 0.9807) and low p value (<0.0001) of the quadratic model indicated that the model was accurate in predicting the experimental results. The optimal soil moisture content, n-Al/CaO dosage, and grinding time were found to be 7% (m/m), 17.7% (m/m), and 24 h, respectively, in the experimental ranges and levels. Under optimal conditions, the dechlorination efficiency was 80%. The intermediate product analysis indicated that dechlorination was the process by stepwise loss of chloride atoms. The main pathway observed within 24 h was HCB → pentachlorobenzene (PeCB) → 1,2,3,4-tetrachlorobenzene (TeCB) and 1,2,4,5-TeCB. The results indicated that the moderate soil moisture content was crucial for the hydrodechlorination of HCB. A probable mechanism was proposed wherein water acted like a hydrogen donor and promoted the hydrodechlorination process. The potential application of n-Al/CaO is an environmentally-friendly and cost-effective option for decontamination of HCB-contaminated soils.
High resolution change estimation of soil moisture and its assimilation into a land surface model
NASA Astrophysics Data System (ADS)
Narayan, Ujjwal
Near surface soil moisture plays an important role in hydrological processes including infiltration, evapotranspiration and runoff. These processes depend non-linearly on soil moisture and hence sub-pixel scale soil moisture variability characterization is important for accurate modeling of water and energy fluxes at the pixel scale. Microwave remote sensing has evolved as an attractive technique for global monitoring of near surface soil moisture. A radiative transfer model has been tested and validated for soil moisture retrieval from passive microwave remote sensing data under a full range of vegetation water content conditions. It was demonstrated that soil moisture retrieval errors of approximately 0.04 g/g gravimetric soil moisture are attainable with vegetation water content as high as 5 kg/m2. Recognizing the limitation of low spatial resolution associated with passive sensors, an algorithm that uses low resolution passive microwave (radiometer) and high resolution active microwave (radar) data to estimate soil moisture change at the spatial resolution of radar operation has been developed and applied to coincident Passive and Active L and S band (PALS) and Airborne Synthetic Aperture Radar (AIRSAR) datasets acquired during the Soil Moisture Experiments in 2002 (SMEX02) campaign with root mean square error of 10% and a 4 times enhancement in spatial resolution. The change estimation algorithm has also been used to estimate soil moisture change at 5 km resolution using AMSR-E soil moisture product (50 km) in conjunction with the TRMM-PR data (5 km) for a 3 month period demonstrating the possibility of high resolution soil moisture change estimation using satellite based data. Soil moisture change is closely related to precipitation and soil hydraulic properties. A simple assimilation framework has been implemented to investigate whether assimilation of surface layer soil moisture change observations into a hydrologic model will potentially improve it performance. Results indicate an improvement in model prediction of near surface and deep layer soil moisture content when the update is performed to the model state as compared to free model runs. It is also seen that soil moisture change assimilation is able to mitigate the effect of erroneous precipitation input data.
Ross, E W; Taub, I A; Doona, C J; Feeherry, F E; Kustin, K
2005-03-15
Knowledge of the mathematical properties of the quasi-chemical model [Taub, Feeherry, Ross, Kustin, Doona, 2003. A quasi-chemical kinetics model for the growth and death of Staphylococcus aureus in intermediate moisture bread. J. Food Sci. 68 (8), 2530-2537], which is used to characterize and predict microbial growth-death kinetics in foods, is important for its applications in predictive microbiology. The model consists of a system of four ordinary differential equations (ODEs), which govern the temporal dependence of the bacterial life cycle (the lag, exponential growth, stationary, and death phases, respectively). The ODE system derives from a hypothetical four-step reaction scheme that postulates the activity of a critical intermediate as an antagonist to growth (perhaps through a quorum sensing biomechanism). The general behavior of the solutions to the ODEs is illustrated by several examples. In instances when explicit mathematical solutions to these ODEs are not obtainable, mathematical approximations are used to find solutions that are helpful in evaluating growth in the early stages and again near the end of the process. Useful solutions for the ODE system are also obtained in the case where the rate of antagonist formation is small. The examples and the approximate solutions provide guidance in the parameter estimation that must be done when fitting the model to data. The general behavior of the solutions is illustrated by examples, and the MATLAB programs with worked examples are included in the appendices for use by predictive microbiologists for data collected independently.
NASA Technical Reports Server (NTRS)
Soman, Vishwas V.; Crosson, William L.; Laymon, Charles; Tsegaye, Teferi
1998-01-01
Soil moisture is an important component of analysis in many Earth science disciplines. Soil moisture information can be obtained either by using microwave remote sensing or by using a hydrologic model. In this study, we combined these two approaches to increase the accuracy of profile soil moisture estimation. A hydrologic model was used to analyze the errors in the estimation of soil moisture using the data collected during Huntsville '96 microwave remote sensing experiment in Huntsville, Alabama. Root mean square errors (RMSE) in soil moisture estimation increase by 22% with increase in the model input interval from 6 hr to 12 hr for the grass-covered plot. RMSEs were reduced for given model time step by 20-50% when model soil moisture estimates were updated using remotely-sensed data. This methodology has a potential to be employed in soil moisture estimation using rainfall data collected by a space-borne sensor, such as the Tropical Rainfall Measuring Mission (TRMM) satellite, if remotely-sensed data are available to update the model estimates.
Application of IEM model on soil moisture and surface roughness estimation
NASA Technical Reports Server (NTRS)
Shi, Jiancheng; Wang, J. R.; Oneill, P. E.; Hsu, A. Y.; Engman, E. T.
1995-01-01
Monitoring spatial and temporal changes of soil moisture are of importance to hydrology, meteorology, and agriculture. This paper reports a result on study of using L-band SAR imagery to estimate soil moisture and surface roughness for bare fields. Due to limitations of the Small Perturbation Model, it is difficult to apply this model on estimation of soil moisture and surface roughness directly. In this study, we show a simplified model derived from the Integral Equation Model for estimation of soil moisture and surface roughness. We show a test of this model using JPL L-band AIRSAR data.
Effect of the method of process on the control of microbial growth by water activity in foods
NASA Technical Reports Server (NTRS)
Labuzu, T. D.
1972-01-01
Two methods for preparation of intermediate moisture foods (IMF) were investigated; water absorption and water desorption technique. Results indicate that shelf stability of IMF systems might be enhanced by preparing foods by rehumidifying dehydrated foods to optimum water activity rather than drying food to reduce the water activity.
The Impact of Microwave-Derived Surface Soil Moisture on Watershed Hydrological Modeling
NASA Technical Reports Server (NTRS)
ONeill, P. E.; Hsu, A. Y.; Jackson, T. J.; Wood, E. F.; Zion, M.
1997-01-01
The usefulness of incorporating microwave-derived soil moisture information in a semi-distributed hydrological model was demonstrated for the Washita '92 experiment in the Little Washita River watershed in Oklahoma. Initializing the hydrological model with surface soil moisture fields from the ESTAR airborne L-band microwave radiometer on a single wet day at the start of the study period produced more accurate model predictions of soil moisture than a standard hydrological initialization with streamflow data over an eight-day soil moisture drydown.
Antecedent moisture content and soil texture effects on infiltration and erosion
NASA Astrophysics Data System (ADS)
Mamedov, A. I.; Huang, C.; Levy, G. J.
2006-12-01
Water infiltration, seal formation, runoff and erosion depend on the soil's inherent properties and surface conditions. Most erosion models consider only soil inherent properties (mainly texture) in assessing infiltration and erosion without consideration of spatial and temporary variation in the surface condition, particularly the antecedent moisture content. We studied the interaction of two different surface conditions, i.e. antecedent moisture content (AMC) and aging (timing after wetting) on infiltration (IR), seal formation (runoff generation) and erosion in four soils varying from loam to clay. Soil samples were packed in erosion box and wetted with different amounts of water (0, 1, 2, 3, 4, 6, 8, or 16 mm) to obtain a wide moisture range (i.e., pF 0-6.2, or from air dry to full saturation). The boxes were put in plastic bags and allowed to age for 0.01, 1, 3, or 7 days. Then the soil in the erosion box exposed to 60 mm of rain. At no aging final IR of soils did not change significantly, but runoff volume (a measure for seal development) and soil loss increased with an increase in AMC mainly because of aggregate breakdown. For any given aging, the highest IR and smallest runoff volume and soil loss were obtained at the intermediate AMC levels (pF 2.4-4.2, between wilting point and field capacity). For instance, in the clay soil to which 3 mm of water (pF~2.7) was added, as aging increased from one to seven days, final IR increased from 5.3 to 7.9 mm h-1, while runoff and soil loss decreased from 34 mm to 22 mm, and from 630 to 360 g m2 respectively. At this AMC range, increasing aging time resulted in up to 40% increase in IR and decrease in runoff or soil loss. This tendency significantly more pronounced for clay soils because water-filled pores in the clay fabric were considered active in the stabilization process and the development of cohesive bonds between and within particles during the aging period. The results of this study are important for soil erosion modeling. In order to improve the prediction capabilities of erosion models, temporal and spatial variation of soil moisture content (AMC, wetting and aging) prior to erosive rainstorms should be considered and or incorporated. In addition, management practices could be adapted to diminish the severe soil moisture variation, where ever possible, (minimum till or no-till with known residue) to maintain the soil surface at a desired AMC level prior to expected rainstorms in order to decrease soil susceptibility to seal formation, runoff and soil loss.
Temporal changes in soil water repellency linked to the soil respiration and CH4 and CO2 fluxes
NASA Astrophysics Data System (ADS)
Qassem, Khalid; Urbanek, Emilia; van Keulen, Geertje
2014-05-01
Soil water repellency (SWR) is known to be a spatially and temporally variable phenomenon. The seasonal changes in soil moisture lead to development of soil water repellency, which in consequence may affect the microbial activity and in consequence alter the CO2 and CH4 fluxes from soils. Soil microbial activity is strongly linked to the temperature and moisture status of the soil. In terms of CO2 flux intermediate moisture contents are most favourable for the optimal microbial activity and highest CO2 fluxes. Methanogenesis occurs primarily in anaerobic water-logged habitats while methanotrophy is a strictly aerobic process. In the study we hypothesise that the changes in CO2 and CH4 fluxes are closely linked to critical moisture thresholds for soil water repellency. This research project aims to adopt a multi-disciplinary approach to comprehensively determine the effect of SWR on CO2 and CH4 fluxes. Research is conducted in situ at four sites exhibiting SWR in the southern UK. Flux measurements are carried out concomitant with meteorological and SWR observations Field observations are supported by laboratory measurements carried out on intact soil samples collected at the above identified field sites. The laboratory analyses are conducted under constant temperatures with controlled changes of soil moisture content. Methanogenic and Methanotrophic microbial populations are being analysed at different SWR and moisture contents using the latest metagenomic and metatranscriptomic approaches. Currently available data show that greenhouse gas flux are closely linked with soil moisture thresholds for SWR development.
A Comparison of Methods for a Priori Bias Correction in Soil Moisture Data Assimilation
NASA Technical Reports Server (NTRS)
Kumar, Sujay V.; Reichle, Rolf H.; Harrison, Kenneth W.; Peters-Lidard, Christa D.; Yatheendradas, Soni; Santanello, Joseph A.
2011-01-01
Data assimilation is being increasingly used to merge remotely sensed land surface variables such as soil moisture, snow and skin temperature with estimates from land models. Its success, however, depends on unbiased model predictions and unbiased observations. Here, a suite of continental-scale, synthetic soil moisture assimilation experiments is used to compare two approaches that address typical biases in soil moisture prior to data assimilation: (i) parameter estimation to calibrate the land model to the climatology of the soil moisture observations, and (ii) scaling of the observations to the model s soil moisture climatology. To enable this research, an optimization infrastructure was added to the NASA Land Information System (LIS) that includes gradient-based optimization methods and global, heuristic search algorithms. The land model calibration eliminates the bias but does not necessarily result in more realistic model parameters. Nevertheless, the experiments confirm that model calibration yields assimilation estimates of surface and root zone soil moisture that are as skillful as those obtained through scaling of the observations to the model s climatology. Analysis of innovation diagnostics underlines the importance of addressing bias in soil moisture assimilation and confirms that both approaches adequately address the issue.
Li, J; Wu, Y; Ma, Y; Lu, N; Regenstein, J M; Zhou, P
2017-08-01
High-protein intermediate moisture food (HPIMF) containing sodium caseinate (NaCN) often gave a harder texture compared with that made from whey proteins or soy proteins, due to the aggregation of protein particles. The objectives of this study were to explore whether the addition of hydrocolloids could soften the texture and illustrate the possible mechanism. Three kinds of hydrocolloids, xanthan gum, κ-carrageenan, and gum arabic were chosen, and samples including of these three kinds of hydrocolloids were studied through texture analysis using a TPA test and microstructure observation by confocal laser scanning microscopy (CLSM) and scanning electron microscopy (SEM). The texture analysis results showed that xanthan gum was more effective at softening the HPIMF containing NaCN compared to κ-carrageenan and gum arabic. In addition, with the increase of xanthan gum concentration from 0.2 to 2%, the HPIMF matrix became softer, and fractures were observed during the compression for samples with xanthan gum added at low concentrations but not 2%. Microstructure observation suggested that the matrix originally dominated by the network formed through the aggregation of swollen protein particles was inhibited by the addition of xanthan gum, resulting in the softening of the texture and also contributing to the fracture during compression. With the increase of xanthan gum concentration up to 2%, the protein dominating network would be gradually replaced with a matrix dominated by the newly formed network of xanthan gum with protein particles as fillers. Furthermore, this formation of a xanthan gum dominating network structure also resulted in changes in small molecule distribution, as observed using low-field NMR.
Modeling moisture content of fine dead wildland fuels: Input to the BEHAVE fire prediction system
Richard C. Rothermel; Ralph A. Wilson; Glen A. Morris; Stephen S. Sackett
1986-01-01
Describes a model for predicting moisture content of fine fuels for use with the BEHAVE fire behavior and fuel modeling system. The model is intended to meet the need for more accurate predictions of fine fuel moisture, particularly in northern conifer stands and on days following rain. The model is based on the Canadian Fine Fuel Moisture Code (FFMC), modified to...
NASA Astrophysics Data System (ADS)
Zhang, Ke; Yang, Tao; Ye, Jinyin; Li, Zhijia; Yu, Zhongbo
2017-04-01
Soil moisture is a key variable that regulates exchanges of water and energy between land surface and atmosphere. Soil moisture retrievals based on microwave satellite remote sensing have made it possible to estimate global surface (up to about 10 cm in depth) soil moisture routinely. Although there are many satellites operating, including NASA's Soil Moisture Acitive Passive mission (SMAP), ESA's Soil Moisture and Ocean Salinity mission (SMOS), JAXA's Advanced Microwave Scanning Radiometer 2 mission (AMSR2), and China's Fengyun (FY) missions, key differences exist between different satellite-based soil moisture products. In this study, we applied a single-channel soil moisture retrieval model forced by multiple sources of satellite brightness temperature observations to estimate consistent daily surface soil moisture across China at a spatial resolution of 25 km. By utilizing observations from multiple satellites, we are able to estimate daily soil moisture across the whole domain of China. We further developed a daily soil moisture accounting model and applied it to downscale the 25-km satellite-based soil moisture to 5 km. By comparing our estimated soil moisture with observations from a dense observation network implemented in Anhui Province, China, our estimated soil moisture results show a reasonably good agreement with the observations (RMSE < 0.1 and r > 0.8).
NASA Astrophysics Data System (ADS)
Bastola, S.; Dialynas, Y. G.; Arnone, E.; Bras, R. L.
2014-12-01
The spatial variability of soil, vegetation, topography, and precipitation controls hydrological processes, consequently resulting in high spatio-temporal variability of most of the hydrological variables, such as soil moisture. Limitation in existing measuring system to characterize this spatial variability, and its importance in various application have resulted in a need of reconciling spatially distributed soil moisture evolution model and corresponding measurements. Fully distributed ecohydrological model simulates soil moisture at high resolution soil moisture. This is relevant for range of environmental studies e.g., flood forecasting. They can also be used to evaluate the value of space born soil moisture data, by assimilating them into hydrological models. In this study, fine resolution soil moisture data simulated by a physically-based distributed hydrological model, tRIBS-VEGGIE, is compared with soil moisture data collected during the field campaign in Turkey river basin, Iowa. The soil moisture series at the 2 and 4 inch depth exhibited a more rapid response to rainfall as compared to bottom 8 and 20 inch ones. The spatial variability in two distinct land surfaces of Turkey River, IA, reflects the control of vegetation, topography and soil texture in the characterization of spatial variability. The comparison of observed and simulated soil moisture at various depth showed that model was able to capture the dynamics of soil moisture at a number of gauging stations. Discrepancies are large in some of the gauging stations, which are characterized by rugged terrain and represented, in the model, through large computational units.
Soil Moisture Project Evaluation Workshop
NASA Technical Reports Server (NTRS)
Gilbert, R. H. (Editor)
1980-01-01
Approaches planned or being developed for measuring and modeling soil moisture parameters are discussed. Topics cover analysis of spatial variability of soil moisture as a function of terrain; the value of soil moisture information in developing stream flow data; energy/scene interactions; applications of satellite data; verifying soil water budget models; soil water profile/soil temperature profile models; soil moisture sensitivity analysis; combinations of the thermal model and microwave; determing planetary roughness and field roughness; how crust or a soil layer effects microwave return; truck radar; and truck/aircraft radar comparison.
NASA Astrophysics Data System (ADS)
Tang, J.; Riley, W. J.
2017-12-01
Most existing soil carbon cycle models have modeled the moisture and temperature dependence of soil respiration using deterministic response functions. However, empirical data suggest abundant variability in both of these dependencies. We here use the recently developed SUPECA (Synthesizing Unit and Equilibrium Chemistry Approximation) theory and a published dynamic energy budget based microbial model to investigate how soil carbon decomposition responds to changes in soil moisture and temperature under the influence of organo-mineral interactions. We found that both the temperature and moisture responses are hysteretic and cannot be represented by deterministic functions. We then evaluate how the multi-scale variability in temperature and moisture forcing affect soil carbon decomposition. Our results indicate that when the model is run in scenarios mimicking laboratory incubation experiments, the often-observed temperature and moisture response functions can be well reproduced. However, when such response functions are used for model extrapolation involving more transient variability in temperature and moisture forcing (as found in real ecosystems), the dynamic model that explicitly accounts for hysteresis in temperature and moisture dependency produces significantly different estimations of soil carbon decomposition, suggesting there are large biases in models that do not resolve such hysteresis. We call for more studies on organo-mineral interactions to improve modeling of such hysteresis.
Baeza, M J; De Luís, M; Raventós, J; Escarré, A
2002-06-01
Fire behaviour under experimental conditions is described in nine Mediterranean gorse shrublands ranging from 3-12 years of age with different fuel loads. Significant differences in the fire-line intensity, fuel load and rate of fire spread have been found to be related to the stage of development of the communities. Fire spread is correlated with fuel moisture using multiple regression techniques. Differences in fuel moisture between mature and young communities under moderate weather conditions have been found. The lower moisture content identified in the mature shrubland is due both to the decreasing moisture content of senescent shrubland in some species, mainly in live fractions of Ulex parviflorus Pour. fuel, and to a substantial increase in dead fuel fractions with low percentages of moisture content. The result is that the older the shrubland is, the greater will be the decrease in the total moisture content of the vegetation. In these moderate weather conditions, the fire intensity of the mature community was as high as the maximum intensity recommended for prescribed fires. This fact seems to indicate that, even under moderate conditions, prescribed burning as an alternative management tool in the mature shrubland must always take into account fuel control; on the other hand, this technique could be applied more easily when the shrubland is at an intermediate growth stage (4-5 years of age). Therefore, more frequent low-intensity prescribed fires are indicated to abate the risk of catastrophic fire.
State of the Art in Large-Scale Soil Moisture Monitoring
NASA Technical Reports Server (NTRS)
Ochsner, Tyson E.; Cosh, Michael Harold; Cuenca, Richard H.; Dorigo, Wouter; Draper, Clara S.; Hagimoto, Yutaka; Kerr, Yan H.; Larson, Kristine M.; Njoku, Eni Gerald; Small, Eric E.;
2013-01-01
Soil moisture is an essential climate variable influencing land atmosphere interactions, an essential hydrologic variable impacting rainfall runoff processes, an essential ecological variable regulating net ecosystem exchange, and an essential agricultural variable constraining food security. Large-scale soil moisture monitoring has advanced in recent years creating opportunities to transform scientific understanding of soil moisture and related processes. These advances are being driven by researchers from a broad range of disciplines, but this complicates collaboration and communication. For some applications, the science required to utilize large-scale soil moisture data is poorly developed. In this review, we describe the state of the art in large-scale soil moisture monitoring and identify some critical needs for research to optimize the use of increasingly available soil moisture data. We review representative examples of 1) emerging in situ and proximal sensing techniques, 2) dedicated soil moisture remote sensing missions, 3) soil moisture monitoring networks, and 4) applications of large-scale soil moisture measurements. Significant near-term progress seems possible in the use of large-scale soil moisture data for drought monitoring. Assimilation of soil moisture data for meteorological or hydrologic forecasting also shows promise, but significant challenges related to model structures and model errors remain. Little progress has been made yet in the use of large-scale soil moisture observations within the context of ecological or agricultural modeling. Opportunities abound to advance the science and practice of large-scale soil moisture monitoring for the sake of improved Earth system monitoring, modeling, and forecasting.
Field measurement of moisture-buffering model inputs for residential buildings
Woods, Jason; Winkler, Jon
2016-02-05
Moisture adsorption and desorption in building materials impact indoor humidity. This effect should be included in building-energy simulations, particularly when humidity is being investigated or controlled. Several models can calculate this moisture-buffering effect, but accurate ones require model inputs that are not always known to the user of the building-energy simulation. This research developed an empirical method to extract whole-house model inputs for the effective moisture penetration depth (EMPD) model. The experimental approach was to subject the materials in the house to a square-wave relative-humidity profile, measure all of the moisture-transfer terms (e.g., infiltration, air-conditioner condensate), and calculate the onlymore » unmeasured term—the moisture sorption into the materials. We validated this method with laboratory measurements, which we used to measure the EMPD model inputs of two houses. After deriving these inputs, we measured the humidity of the same houses during tests with realistic latent and sensible loads and demonstrated the accuracy of this approach. Furthermore, these results show that the EMPD model, when given reasonable inputs, is an accurate moisture-buffering model.« less
Misrepresentation and amendment of soil moisture in conceptual hydrological modelling
NASA Astrophysics Data System (ADS)
Zhuo, Lu; Han, Dawei
2016-04-01
Although many conceptual models are very effective in simulating river runoff, their soil moisture schemes are generally not realistic in comparison with the reality (i.e., getting the right answers for the wrong reasons). This study reveals two significant misrepresentations in those models through a case study using the Xinanjiang model which is representative of many well-known conceptual hydrological models. The first is the setting of the upper limit of its soil moisture at the field capacity, due to the 'holding excess runoff' concept (i.e., runoff begins on repletion of its storage to the field capacity). The second is neglect of capillary rise of water movement. A new scheme is therefore proposed to overcome those two issues. The amended model is as effective as its original form in flow modelling, but represents more logically realistic soil water processes. The purpose of the study is to enable the hydrological model to get the right answers for the right reasons. Therefore, the new model structure has a better capability in potentially assimilating soil moisture observations to enhance its real-time flood forecasting accuracy. The new scheme is evaluated in the Pontiac catchment of the USA through a comparison with satellite observed soil moisture. The correlation between the XAJ and the observed soil moisture is enhanced significantly from 0.64 to 0.70. In addition, a new soil moisture term called SMDS (Soil Moisture Deficit to Saturation) is proposed to complement the conventional SMD (Soil Moisture Deficit).
Modeling soil moisture memory in savanna ecosystems
NASA Astrophysics Data System (ADS)
Gou, S.; Miller, G. R.
2011-12-01
Antecedent soil conditions create an ecosystem's "memory" of past rainfall events. Such soil moisture memory effects may be observed over a range of timescales, from daily to yearly, and lead to feedbacks between hydrological and ecosystem processes. In this study, we modeled the soil moisture memory effect on savanna ecosystems in California, Arizona, and Africa, using a system dynamics model created to simulate the ecohydrological processes at the plot-scale. The model was carefully calibrated using soil moisture and evapotranspiration data collected at three study sites. The model was then used to simulate scenarios with various initial soil moisture conditions and antecedent precipitation regimes, in order to study the soil moisture memory effects on the evapotranspiration of understory and overstory species. Based on the model results, soil texture and antecedent precipitation regime impact the redistribution of water within soil layers, potentially causing deeper soil layers to influence the ecosystem for a longer time. Of all the study areas modeled, soil moisture memory of California savanna ecosystem site is replenished and dries out most rapidly. Thus soil moisture memory could not maintain the high rate evapotranspiration for more than a few days without incoming rainfall event. On the contrary, soil moisture memory of Arizona savanna ecosystem site lasts the longest time. The plants with different root depths respond to different memory effects; shallow-rooted species mainly respond to the soil moisture memory in the shallow soil. The growing season of grass is largely depended on the soil moisture memory of the top 25cm soil layer. Grass transpiration is sensitive to the antecedent precipitation events within daily to weekly timescale. Deep-rooted plants have different responses since these species can access to the deeper soil moisture memory with longer time duration Soil moisture memory does not have obvious impacts on the phenology of woody plants, as these can maintain transpiration for a longer time even through the top soil layer dries out.
Soil Moisture Memory in Climate Models
NASA Technical Reports Server (NTRS)
Koster, Randal D.; Suarez, Max J.; Zukor, Dorothy J. (Technical Monitor)
2000-01-01
Water balance considerations at the soil surface lead to an equation that relates the autocorrelation of soil moisture in climate models to (1) seasonality in the statistics of the atmospheric forcing, (2) the variation of evaporation with soil moisture, (3) the variation of runoff with soil moisture, and (4) persistence in the atmospheric forcing, as perhaps induced by land atmosphere feedback. Geographical variations in the relative strengths of these factors, which can be established through analysis of model diagnostics and which can be validated to a certain extent against observations, lead to geographical variations in simulated soil moisture memory and thus, in effect, to geographical variations in seasonal precipitation predictability associated with soil moisture. The use of the equation to characterize controls on soil moisture memory is demonstrated with data from the modeling system of the NASA Seasonal-to-Interannual Prediction Project.
The Response of Extreme Precipitation to Climate Change in the North American Monsoon Region
NASA Astrophysics Data System (ADS)
Pascale, S.; Bordoni, S.; Kapnick, S. B.; Delworth, T. L.; Murakami, H.
2017-12-01
Gulf of California moisture surges (GoC surges) transport lower-level moisture in the southwestern United States and can trigger widespread convective bursts during the summertime North American monsoon (NAM). The intensity of such bursts varies over a wide spectrum, going from drier-than-average to extremely intense and persisting events. In this study we use a 50 km-horizontal resolution global coupled model (FLOR) developed at the NOAA Geophysical Fluid Dynamics Laboratory and featuring a realistic simulation of the GoC surges. We evaluate the model's ability to reproduce the intensity of precipitation during GoC surge and non-surge periods in present and doubled CO2 climatic conditions. We find that the mean number of GoC surge events per monsoon season (i.e., approximately 15) is not significantly affected by CO2 forcing. Nevertheless, when SST biases are minimized through flux adjustment, FLOR predicts a reduction in monsoonal precipitation over the southwestern United States. Our simulations further suggest that surge-related rainfall adjusts towards lower and higher percentiles, while becoming less important at intermediate values. Convective precipitation not occurring during GoC surges is instead not coherently affected by doubled CO2. Finally, the influence of CO2 forcing on the large-scale drivers of monsoonal precipitation during GoC surge events, such as the position of the monsoonal ridge, is investigated and related to precipitation changes.
NASA Technical Reports Server (NTRS)
Robock, Alan; Vinnikov, Konstantin YA.; Schlosser, C. Adam; Speranskaya, Nina A.; Xue, Yongkang
1995-01-01
Soil moisture observations in sites with natural vegetation were made for several decades in the former Soviet Union at hundreds of stations. In this paper, the authors use data from six of these stations from different climatic regimes, along with ancillary meteorological and actinometric data, to demonstrate a method to validate soil moisture simulations with biosphere and bucket models. Some early and current general circulation models (GCMs) use bucket models for soil hydrology calculations. More recently, the Simple Biosphere Model (SiB) was developed to incorporate the effects of vegetation on fluxes of moisture, momentum, and energy at the earth's surface into soil hydrology models. Until now, the bucket and SiB have been verified by comparison with actual soil moisture data only on a limited basis. In this study, a Simplified SiB (SSiB) soil hydrology model and a 15-cm bucket model are forced by observed meteorological and actinometric data every 3 h for 6-yr simulations at the six stations. The model calculations of soil moisture are compared to observations of soil moisture, literally 'ground truth,' snow cover, surface albedo, and net radiation, and with each other. For three of the stations, the SSiB and 15-cm bucket models produce good simulations of seasonal cycles and interannual variations of soil moisture. For the other three stations, there are large errors in the simulations by both models. Inconsistencies in specification of field capacity may be partly responsible. There is no evidence that the SSiB simulations are superior in simulating soil moisture variations. In fact, the models are quite similar since SSiB implicitly has a bucket embedded in it. One of the main differences between the models is in the treatment of runoff due to melting snow in the spring -- SSiB incorrectly puts all the snowmelt into runoff. While producing similar soil moisture simulations, the models produce very different surface latent and sensible heat fluxes, which would have large effects on GCM simulations.
Technical note: Evaluation of a crucible furnace retort for laboratory torrefactions of wood chips
Thomas L. Eberhardt; Karen G. Reed
2014-01-01
Torrefaction is a thermal process that improves biomass performance as a fuel by property enhancements such as decreased moisture uptake and increased carbon density. Most studies to date have used very small amounts of finely ground biomass. This study reports the testing of a crucible furnace retort that was fabricated to produce intermediate quantities of torrefied...
Simultaneous effect of initial moisture content and airflow rate on biodrying of sewage sludge.
Huiliñir, Cesar; Villegas, Manuel
2015-10-01
The simultaneous effect of initial moisture content (initial Mc) and air-flow rate (AFR) on biodrying performance was evaluated. For the study, a 3(2) factorial design, whose factors were AFR (1, 2 and 3 L/min kg(TS)) and initial Mc (59, 68 and 78% w.b.), was used. Using energy and water mass balance the main routes of water removal, energy use and efficiencies were determined. The results show that initial Mc has a stronger effect on the biodrying than the AFR, affecting the air outlet temperature and improving the water removal, with higher maximum temperatures obtained around 68% and the lowest maximum matrix temperature obtained at initial Mc = 78%.Through the water mass balance it was found that the main mechanism for water removal was the aeration, with higher water removal at intermediate initial Mc (68%) and high AFR (3 L/min kg(TS)). The energy balance indicated that bioreaction is the main energy source for water evaporation, with higher energy produced at intermediate initial Mc (68%). Finally, it was found that low values of initial Mc (59%) improve biodrying efficiency. Copyright © 2015 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Schreiner-McGraw, A. P.; Vivoni, E. R.; Mascaro, G.; Franz, T. E.
2015-06-01
Soil moisture dynamics reflect the complex interactions of meteorological conditions with soil, vegetation and terrain properties. In this study, intermediate scale soil moisture estimates from the cosmic-ray sensing (CRS) method are evaluated for two semiarid ecosystems in the southwestern United States: a mesquite savanna at the Santa Rita Experimental Range (SRER) and a mixed shrubland at the Jornada Experimental Range (JER). Evaluations of the CRS method are performed for small watersheds instrumented with a distributed sensor network consisting of soil moisture sensor profiles, an eddy covariance tower and runoff flumes used to close the water balance. We found an excellent agreement between the CRS method and the distributed sensor network (RMSE of 0.009 and 0.013 m3 m-3 at SRER and JER) at the hourly time scale over the 19-month study period, primarily due to the inclusion of 5 cm observations of shallow soil moisture. Good agreement was obtained in soil moisture changes estimated from the CRS and watershed water balance methods (RMSE = 0.001 and 0.038 m3 m-3 at SRER and JER), with deviations due to bypassing of the CRS measurement depth during large rainfall events. This limitation, however, was used to show that drier-than-average conditions at SRER promoted plant water uptake from deeper layers, while the wetter-than-average period at JER resulted in leakage towards deeper soils. Using the distributed sensor network, we quantified the spatial variability of soil moisture in the CRS footprint and the relation between evapotranspiration and soil moisture, in both cases finding similar predictive relations at both sites that are applicable to other semiarid ecosystems in the southwestern US. Furthermore, soil moisture spatial variability was related to evapotranspiration in a manner consistent with analytical relations derived using the CRS method, opening up new possibilities for understanding land-atmosphere interactions.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Qu, X.; Cemagref, UR-HBAN, Parc de Tourvoie, Antony cedex F-92163; Vavilin, V.A.
Utilizing stable carbon isotope data to account for aceticlastic and non-aceticlastic pathways of methane generation, a model was created to describe laboratory batch anaerobic decomposition of cellulosic materials (office paper and cardboard). The total organic and inorganic carbon concentrations, methane production volume, and methane and CO{sub 2} partial pressure values were used for the model calibration and validation. According to the fluorescent in situ hybridization observations, three groups of methanogens including strictly hydrogenotrophic methanogens, strictly aceticlastic methanogens (Methanosaeta sp.) and Methanosarcina sp., consuming both acetate and H{sub 2}/H{sub 2}CO{sub 3} as well as acetate-oxidizing syntrophs, were considered. It was shownmore » that temporary inhibition of aceticlastic methanogens by non-ionized volatile fatty acids or acidic pH was responsible for two-step methane production from office paper at 35 {sup o}C where during the first and second steps methane was generated mostly from H{sub 2}/H{sub 2}CO{sub 3} and acetate, respectively. Water saturated and unsaturated cases were tested. According to the model, at the intermediate moisture (150%), much lower methane production occurred because of full-time inhibition of aceticlastic methanogens. At the lowest moisture, methane production was very low because most likely hydrolysis was seriously inhibited. Simulations showed that during cardboard and office paper biodegradation at 55 {sup o}C, non-aceticlastic syntrophic oxidation by acetate-oxidizing syntrophs and hydrogenotrophic methanogens were the dominant methanogenic pathways.« less
NASA Astrophysics Data System (ADS)
Wanders, N.; Bierkens, M. F. P.; de Jong, S. M.; de Roo, A.; Karssenberg, D.
2014-08-01
Large-scale hydrological models are nowadays mostly calibrated using observed discharge. As a result, a large part of the hydrological system, in particular the unsaturated zone, remains uncalibrated. Soil moisture observations from satellites have the potential to fill this gap. Here we evaluate the added value of remotely sensed soil moisture in calibration of large-scale hydrological models by addressing two research questions: (1) Which parameters of hydrological models can be identified by calibration with remotely sensed soil moisture? (2) Does calibration with remotely sensed soil moisture lead to an improved calibration of hydrological models compared to calibration based only on discharge observations, such that this leads to improved simulations of soil moisture content and discharge? A dual state and parameter Ensemble Kalman Filter is used to calibrate the hydrological model LISFLOOD for the Upper Danube. Calibration is done using discharge and remotely sensed soil moisture acquired by AMSR-E, SMOS, and ASCAT. Calibration with discharge data improves the estimation of groundwater and routing parameters. Calibration with only remotely sensed soil moisture results in an accurate identification of parameters related to land-surface processes. For the Upper Danube upstream area up to 40,000 km2, calibration on both discharge and soil moisture results in a reduction by 10-30% in the RMSE for discharge simulations, compared to calibration on discharge alone. The conclusion is that remotely sensed soil moisture holds potential for calibration of hydrological models, leading to a better simulation of soil moisture content throughout the catchment and a better simulation of discharge in upstream areas. This article was corrected on 15 SEP 2014. See the end of the full text for details.
Storage Stability of Food Protein Hydrolysates-A Review.
Rao, Qinchun; Klaassen Kamdar, Andre; Labuza, Theodore P
2016-05-18
In recent years, mainly due to the specific health benefits associated with (1) the discovery of bioactive peptides in protein hydrolysates, (2) the reduction of protein allergenicity by protein hydrolysis, and (3) the improved protein digestibility and absorption of protein hydrolysates, the utilization of protein hydrolysates in functional foods and beverages has significantly increased. Although the specific health benefits from different hydrolysates are somewhat proven, the delivery and/or stability of these benefits is debatable during distribution, storage, and consumption. In this review, we discuss (1) the quality changes in different food protein hydrolysates during storage; (2) the resulting changes in the structure and texture of three food matrices, i.e., low moisture foods (LMF, aw < 0.6), intermediate moisture foods (IMF, 0.6 ≤ aw < 0.85), and high moisture foods (HMF, aw ≥ 0.85); and (3) the potential solutions to improve storage stability of food protein hydrolysates. In addition, we note there is a great need for evaluation of biofunction availability of bioactive peptides in food protein hydrolysates during storage.
Improving Water Level and Soil Moisture Over Peatlands in a Global Land Modeling System
NASA Technical Reports Server (NTRS)
Bechtold, M.; De Lannoy, G. J. M.; Roose, D.; Reichle, R. H.; Koster, R. D.; Mahanama, S. P.
2017-01-01
New model structure for peatlands results in improved skill metrics (without any parameter calibration) Simulated surface soil moisture strongly affected by new model, but reliable soil moisture data lacking for validation.
Evaluation of a Soil Moisture Data Assimilation System Over West Africa
NASA Astrophysics Data System (ADS)
Bolten, J. D.; Crow, W.; Zhan, X.; Jackson, T.; Reynolds, C.
2009-05-01
A crucial requirement of global crop yield forecasts by the U.S. Department of Agriculture (USDA) International Production Assessment Division (IPAD) is the regional characterization of surface and sub-surface soil moisture. However, due to the spatial heterogeneity and dynamic nature of precipitation events and resulting soil moisture, accurate estimation of regional land surface-atmosphere interactions based sparse ground measurements is difficult. IPAD estimates global soil moisture using daily estimates of minimum and maximum temperature and precipitation applied to a modified Palmer two-layer soil moisture model which calculates the daily amount of soil moisture withdrawn by evapotranspiration and replenished by precipitation. We attempt to improve upon the existing system by applying an Ensemble Kalman filter (EnKF) data assimilation system to integrate surface soil moisture retrievals from the NASA Advanced Microwave Scanning Radiometer (AMSR-E) into the USDA soil moisture model. This work aims at evaluating the utility of merging satellite-retrieved soil moisture estimates with the IPAD two-layer soil moisture model used within the DBMS. We present a quantitative analysis of the assimilated soil moisture product over West Africa (9°N- 20°N; 20°W-20°E). This region contains many key agricultural areas and has a high agro- meteorological gradient from desert and semi-arid vegetation in the North, to grassland, trees and crops in the South, thus providing an ideal location for evaluating the assimilated soil moisture product over multiple land cover types and conditions. A data denial experimental approach is utilized to isolate the added utility of integrating remotely-sensed soil moisture by comparing assimilated soil moisture results obtained using (relatively) low-quality precipitation products obtained from real-time satellite imagery to baseline model runs forced with higher quality rainfall. An analysis of root-zone anomalies for each model simulation suggests that the assimilation of AMSR-E surface soil moisture retrievals can add significant value to USDA root-zone predictions derived from real-time satellite precipitation products.
The use of remotely sensed soil moisture data in large-scale models of the hydrological cycle
NASA Technical Reports Server (NTRS)
Salomonson, V. V.; Gurney, R. J.; Schmugge, T. J.
1985-01-01
Manabe (1982) has reviewed numerical simulations of the atmosphere which provided a framework within which an examination of the dynamics of the hydrological cycle could be conducted. It was found that the climate is sensitive to soil moisture variability in space and time. The challenge arises now to improve the observations of soil moisture so as to provide up-dated boundary condition inputs to large scale models including the hydrological cycle. Attention is given to details regarding the significance of understanding soil moisture variations, soil moisture estimation using remote sensing, and energy and moisture balance modeling.
A semi-mechanistic model of dead fine fuel moisture for Temperate and Mediterranean ecosystems
NASA Astrophysics Data System (ADS)
Resco de Dios, Víctor; Fellows, Aaron; Boer, Matthias; Bradstock, Ross; Nolan, Rachel; Goulden, Michel
2014-05-01
Fire is a major disturbance in terrestrial ecosystems globally. It has an enormous economic and social cost, and leads to fatalities in the worst cases. The moisture content of the vegetation (fuel moisture) is one of the main determinants of fire risk. Predicting the moisture content of dead and fine fuel (< 2.5 cm in diameter) is particularly important, as this is often the most important component of the fuel complex for fire propagation. A variety of drought indices, empirical and mechanistic models have been proposed to model fuel moisture. A commonality across these different approaches is that they have been neither validated across large temporal datasets nor validated across broadly different vegetation types. Here, we present the results of a study performed at 6 locations in California, USA (5 sites) and New South Wales, Australia (1 site), where 10-hours fuel moisture content was continuously measured every 30 minutes during one full year at each site. We observed that drought indices did not accurately predict fuel moisture, and that empirical and mechanistic models both needed site-specific calibrations, which hinders their global application as indices of fuel moisture. We developed a novel, single equation and semi-mechanistic model, based on atmospheric vapor-pressure deficit. Across sites and years, mean absolute error (MAE) of predicted fuel moisture was 4.7%. MAE dropped <1% in the critical range of fuel moisture <10%. The high simplicity, accuracy and precision of our model makes it suitable for a wide range of applications: from operational purposes, to global vegetation models.
Hydrologic downscaling of soil moisture using global data without site-specific calibration
USDA-ARS?s Scientific Manuscript database
Numerous applications require fine-resolution (10-30 m) soil moisture patterns, but most satellite remote sensing and land-surface models provide coarse-resolution (9-60 km) soil moisture estimates. The Equilibrium Moisture from Topography, Vegetation, and Soil (EMT+VS) model downscales soil moistu...
NASA Astrophysics Data System (ADS)
Tuttle, S. E.; Salvucci, G.
2012-12-01
Soil moisture influences many hydrological processes in the water and energy cycles, such as runoff generation, groundwater recharge, and evapotranspiration, and thus is important for climate modeling, water resources management, agriculture, and civil engineering. Large-scale estimates of soil moisture are produced almost exclusively from remote sensing, while validation of remotely sensed soil moisture has relied heavily on ground truthing, which is at an inherently smaller scale. Here we present a complementary method to determine the information content in different soil moisture products using only large-scale precipitation data (i.e. without modeling). This study builds on the work of Salvucci [2001], Saleem and Salvucci [2002], and Sun et al. [2011], in which precipitation was conditionally averaged according to soil moisture level, resulting in moisture-outflow curves that estimate the dependence of drainage, runoff, and evapotranspiration on soil moisture (i.e. sigmoidal relations that reflect stressed evapotranspiration for dry soils, roughly constant flux equal to potential evaporation minus capillary rise for moderately dry soils, and rapid drainage for very wet soils). We postulate that high quality satellite estimates of soil moisture, using large-scale precipitation data, will yield similar sigmoidal moisture-outflow curves to those that have been observed at field sites, while poor quality estimates will yield flatter, less informative curves that explain less of the precipitation variability. Following this logic, gridded ¼ degree NLDAS precipitation data were compared to three AMSR-E derived soil moisture products (VUA-NASA, or LPRM [Owe et al., 2001], NSIDC [Njoku et al., 2003], and NSIDC-LSP [Jones & Kimball, 2011]) for a period of nine years (2001-2010) across the contiguous United States. Gaps in the daily soil moisture data were filled using a multiple regression model reliant on past and future soil moisture and precipitation, and soil moisture was then converted to a ranked wetness index, in order to reconcile the wide range and magnitude of the soil moisture products. Generalized linear models were employed to fit a polynomial model to precipitation, given wetness index. Various measures of fit (e.g. log likelihood) were used to judge the amount of information in each soil moisture product, as indicated by the amount of precipitation variability explained by the fitted model. Using these methods, regional patterns appear in soil moisture product performance.
NASA Astrophysics Data System (ADS)
Larochelle, Kevin J.
This study focused on moisture and intermediate temperature effects on the embrittlement phenomenon and stress rupture life of the ceramic matrix composite (CMC) made of Sylramic(TM) fibers with an in-situ layer of boron nitride (Syl-iBN), boron nitride interphase (BN), and SiC matrix (Syl-iBN/BN/SiC). Stress rupture tests were performed at 550°C or 750°C with moisture contents of 0.0, 0.2, or 0.6 atm partial pressure of water vapor, pH 2O. The CMC stress rupture strengths at 100 hrs at 550°C with 0.0, 0.2, or 0.6 atm pH2O were 75%, 65% and 51% of the monotonic room temperature tensile strength, respectively. At 750°C, the corresponding strengths were 67%, 51%, and 49%, respectively. Field Emission Scanning Electron Microscopy (FESEM) analysis showed that the amount of pesting by glass formations increased with time, temperature, and pH2O leading to embrittlement. Total embrittlement times for 550°C were estimated to be greater than 63 hrs for 0.0 atm pH2O greater than 38 hrs for 0.2 atm pH 2O and between 8 and 71 hrs for 0.6 atm pH2O. Corresponding estimated embrittlement times for the 750°C were greater than 83 hrs, between 13 and 71 hrs, and between 1 and 6 hrs. A time-dependent, phenomenological, Monte Carlo-type simulation of composite failure was developed. The simulated total embrittlement times for the 550°C cases were 300 hrs, 100 hrs, and 25 hrs for 0.0, 0.2, and 0.6 atm pH 2O, respectively. The corresponding embrittlement times for the 750°C cases were 300 hrs, 20 hrs, and 3 hrs. A detailed sensitivity analysis on the variables used in the model was conducted. The model was most sensitive to variation in the ultimate strength of the CMC at room temperature, the ultimate strength of the CMC at elevated temperature, and the reference strength of a fiber and it was least sensitive to variation in the modulus of elasticity of the matrix and fiber. The sensitivity analysis showed that the stress ruptures curves generated by variation in the total embrittlement time simulate the trends in the experimental data. This research showed that the degree of stress rupture strength degradation increases with temperature, moisture content level, and exposure time.
A new model for predicting moisture uptake by packaged solid pharmaceuticals.
Chen, Y; Li, Y
2003-04-14
A novel mathematical model has been developed for predicting moisture uptake by packaged solid pharmaceutical products during storage. High density polyethylene (HDPE) bottles containing the tablet products of two new chemical entities and desiccants are investigated. Permeability of the bottles is determined at different temperatures using steady-state data. Moisture sorption isotherms of the two model drug products and desiccants at the same temperatures are determined and expressed in polynomial equations. The isotherms are used for modeling the time-humidity profile in the container, which enables the prediction of the moisture content of individual component during storage. Predicted moisture contents agree well with real time stability data. The current model could serve as a guide during packaging selection for moisture protection, so as to reduce the cost and cycle time of screening study.
Response of some Thematic Mapper band ratios to variation in soil water content
NASA Technical Reports Server (NTRS)
Musick, H. Brad; Pelletier, Ramona E.
1986-01-01
Bidirectional reflectance to nadir in the reflective TM bands and the 1.15-1.3-micron band was measured in the laboratory as moisture content was varied in ten soils. Stronger absorption by water in TM5 and TM7 was expected to cause ratios of other bands to TM5 and TM7 to increase with water content, but in most cases these ratios were constant or decreased at low to intermediate water content and increased only at high moisture levels. Because these ratios were found to decrease as illumination elevation angle decreased, it was suggested that increased roughness resulting from the methods of moistening and mixing the soil may have tended to counteract the expected ratio increases.
The Impact of Rainfall on Soil Moisture Dynamics in a Foggy Desert.
Li, Bonan; Wang, Lixin; Kaseke, Kudzai F; Li, Lin; Seely, Mary K
2016-01-01
Soil moisture is a key variable in dryland ecosystems since it determines the occurrence and duration of vegetation water stress and affects the development of weather patterns including rainfall. However, the lack of ground observations of soil moisture and rainfall dynamics in many drylands has long been a major obstacle in understanding ecohydrological processes in these ecosystems. It is also uncertain to what extent rainfall controls soil moisture dynamics in fog dominated dryland systems. To this end, in this study, twelve to nineteen months' continuous daily records of rainfall and soil moisture (from January 2014 to August 2015) obtained from three sites (one sand dune site and two gravel plain sites) in the Namib Desert are reported. A process-based model simulating the stochastic soil moisture dynamics in water-limited systems was used to study the relationships between soil moisture and rainfall dynamics. Model sensitivity in response to different soil and vegetation parameters under diverse soil textures was also investigated. Our field observations showed that surface soil moisture dynamics generally follow rainfall patterns at the two gravel plain sites, whereas soil moisture dynamics in the sand dune site did not show a significant relationship with rainfall pattern. The modeling results suggested that most of the soil moisture dynamics can be simulated except the daily fluctuations, which may require a modification of the model structure to include non-rainfall components. Sensitivity analyses suggested that soil hygroscopic point (sh) and field capacity (sfc) were two main parameters controlling soil moisture output, though permanent wilting point (sw) was also very sensitive under the parameter setting of sand dune (Gobabeb) and gravel plain (Kleinberg). Overall, the modeling results were not sensitive to the parameters in non-bounded group (e.g., soil hydraulic conductivity (Ks) and soil porosity (n)). Field observations, stochastic modeling results as well as sensitivity analyses provide soil moisture baseline information for future monitoring and the prediction of soil moisture patterns in the Namib Desert.
The Impact of Rainfall on Soil Moisture Dynamics in a Foggy Desert
Li, Bonan; Wang, Lixin; Kaseke, Kudzai F.; Li, Lin; Seely, Mary K.
2016-01-01
Soil moisture is a key variable in dryland ecosystems since it determines the occurrence and duration of vegetation water stress and affects the development of weather patterns including rainfall. However, the lack of ground observations of soil moisture and rainfall dynamics in many drylands has long been a major obstacle in understanding ecohydrological processes in these ecosystems. It is also uncertain to what extent rainfall controls soil moisture dynamics in fog dominated dryland systems. To this end, in this study, twelve to nineteen months’ continuous daily records of rainfall and soil moisture (from January 2014 to August 2015) obtained from three sites (one sand dune site and two gravel plain sites) in the Namib Desert are reported. A process-based model simulating the stochastic soil moisture dynamics in water-limited systems was used to study the relationships between soil moisture and rainfall dynamics. Model sensitivity in response to different soil and vegetation parameters under diverse soil textures was also investigated. Our field observations showed that surface soil moisture dynamics generally follow rainfall patterns at the two gravel plain sites, whereas soil moisture dynamics in the sand dune site did not show a significant relationship with rainfall pattern. The modeling results suggested that most of the soil moisture dynamics can be simulated except the daily fluctuations, which may require a modification of the model structure to include non-rainfall components. Sensitivity analyses suggested that soil hygroscopic point (sh) and field capacity (sfc) were two main parameters controlling soil moisture output, though permanent wilting point (sw) was also very sensitive under the parameter setting of sand dune (Gobabeb) and gravel plain (Kleinberg). Overall, the modeling results were not sensitive to the parameters in non-bounded group (e.g., soil hydraulic conductivity (Ks) and soil porosity (n)). Field observations, stochastic modeling results as well as sensitivity analyses provide soil moisture baseline information for future monitoring and the prediction of soil moisture patterns in the Namib Desert. PMID:27764203
NASA Astrophysics Data System (ADS)
Mishra, V.; Cruise, J. F.; Mecikalski, J. R.
2015-12-01
Developing accurate vertical soil moisture profiles with minimum input requirements is important to agricultural as well as land surface modeling. Earlier studies show that the principle of maximum entropy (POME) can be utilized to develop vertical soil moisture profiles with accuracy (MAE of about 1% for a monotonically dry profile; nearly 2% for monotonically wet profiles and 3.8% for mixed profiles) with minimum constraints (surface, mean and bottom soil moisture contents). In this study, the constraints for the vertical soil moisture profiles were obtained from remotely sensed data. Low resolution (25 km) MW soil moisture estimates (AMSR-E) were downscaled to 4 km using a soil evaporation efficiency index based disaggregation approach. The downscaled MW soil moisture estimates served as a surface boundary condition, while 4 km resolution TIR based Atmospheric Land Exchange Inverse (ALEXI) estimates provided the required mean root-zone soil moisture content. Bottom soil moisture content is assumed to be a soil dependent constant. Mulit-year (2002-2011) gridded profiles were developed for the southeastern United States using the POME method. The soil moisture profiles were compared to those generated in land surface models (Land Information System (LIS) and an agricultural model DSSAT) along with available NRCS SCAN sites in the study region. The end product, spatial soil moisture profiles, can be assimilated into agricultural and hydrologic models in lieu of precipitation for data scarce regions.Developing accurate vertical soil moisture profiles with minimum input requirements is important to agricultural as well as land surface modeling. Previous studies have shown that the principle of maximum entropy (POME) can be utilized with minimal constraints to develop vertical soil moisture profiles with accuracy (MAE = 1% for monotonically dry profiles; MAE = 2% for monotonically wet profiles and MAE = 3.8% for mixed profiles) when compared to laboratory and field data. In this study, vertical soil moisture profiles were developed using the POME model to evaluate an irrigation schedule over a maze field in north central Alabama (USA). The model was validated using both field data and a physically based mathematical model. The results demonstrate that a simple two-constraint entropy model under the assumption of a uniform initial soil moisture distribution can simulate most soil moisture profiles within the field area for 6 different soil types. The results of the irrigation simulation demonstrated that the POME model produced a very efficient irrigation strategy with loss of about 1.9% of the total applied irrigation water. However, areas of fine-textured soil (i.e. silty clay) resulted in plant stress of nearly 30% of the available moisture content due to insufficient water supply on the last day of the drying phase of the irrigation cycle. Overall, the POME approach showed promise as a general strategy to guide irrigation in humid environments, with minimum input requirements.
A Mulitivariate Statistical Model Describing the Compound Nature of Soil Moisture Drought
NASA Astrophysics Data System (ADS)
Manning, Colin; Widmann, Martin; Bevacqua, Emanuele; Maraun, Douglas; Van Loon, Anne; Vrac, Mathieu
2017-04-01
Soil moisture in Europe acts to partition incoming energy into sensible and latent heat fluxes, thereby exerting a large influence on temperature variability. Soil moisture is predominantly controlled by precipitation and evapotranspiration. When these meteorological variables are accumulated over different timescales, their joint multivariate distribution and dependence structure can be used to provide information of soil moisture. We therefore consider soil moisture drought as a compound event of meteorological drought (deficits of precipitation) and heat waves, or more specifically, periods of high Potential Evapotraspiration (PET). We present here a statistical model of soil moisture based on Pair Copula Constructions (PCC) that can describe the dependence amongst soil moisture and its contributing meteorological variables. The model is designed in such a way that it can account for concurrences of meteorological drought and heat waves and describe the dependence between these conditions at a local level. The model is composed of four variables; daily soil moisture (h); a short term and a long term accumulated precipitation variable (Y1 and Y_2) that account for the propagation of meteorological drought to soil moisture drought; and accumulated PET (Y_3), calculated using the Penman Monteith equation, which can represent the effect of a heat wave on soil conditions. Copula are multivariate distribution functions that allow one to model the dependence structure of given variables separately from their marginal behaviour. PCCs then allow in theory for the formulation of a multivariate distribution of any dimension where the multivariate distribution is decomposed into a product of marginal probability density functions and two-dimensional copula, of which some are conditional. We apply PCC here in such a way that allows us to provide estimates of h and their uncertainty through conditioning on the Y in the form h=h|y_1,y_2,y_3 (1) Applying the model to various Fluxnet sites across Europe, we find the model has good skill and can particularly capture periods of low soil moisture well. We illustrate the relevance of the dependence structure of these Y variables to soil moisture and show how it may be generalised to offer information of soil moisture on a widespread scale where few observations of soil moisture exist. We then present results from a validation study of a selection of EURO CORDEX climate models where we demonstrate the skill of these models in representing these dependencies and so offer insight into the skill seen in the representation of soil moisture in these models.
NASA Astrophysics Data System (ADS)
Martens, B.; Miralles, D.; Lievens, H.; Fernández-Prieto, D.; Verhoest, N. E. C.
2016-06-01
Terrestrial evaporation is an essential variable in the climate system that links the water, energy and carbon cycles over land. Despite this crucial importance, it remains one of the most uncertain components of the hydrological cycle, mainly due to known difficulties to model the constraints imposed by land water availability on terrestrial evaporation. The main objective of this study is to assimilate satellite soil moisture observations from the Soil Moisture and Ocean Salinity (SMOS) mission into an existing evaporation model. Our over-arching goal is to find an optimal use of satellite soil moisture that can help to improve our understanding of evaporation at continental scales. To this end, the Global Land Evaporation Amsterdam Model (GLEAM) is used to simulate evaporation fields over continental Australia for the period September 2010-December 2013. SMOS soil moisture observations are assimilated using a Newtonian Nudging algorithm in a series of experiments. Model estimates of surface soil moisture and evaporation are validated against soil moisture probe and eddy-covariance measurements, respectively. Finally, an analogous experiment in which Advanced Microwave Scanning Radiometer (AMSR-E) soil moisture is assimilated (instead of SMOS) allows to perform a relative assessment of the quality of both satellite soil moisture products. Results indicate that the modelled soil moisture from GLEAM can be improved through the assimilation of SMOS soil moisture: the average correlation coefficient between in situ measurements and the modelled soil moisture over the complete sample of stations increased from 0.68 to 0.71 and a statistical significant increase in the correlations is achieved for 17 out of the 25 individual stations. Our results also suggest a higher accuracy of the ascending SMOS data compared to the descending data, and overall higher quality of SMOS compared to AMSR-E retrievals over Australia. On the other hand, the effect of soil moisture data assimilation on the evaporation fields is very mild, and difficult to assess due to the limited availability of eddy-covariance data. Nonetheless, our continental-scale simulations indicate that the assimilation of soil moisture can have a substantial impact on the estimated dynamics of evaporation in water-limited regimes. Progressing towards our goal of using satellite soil moisture to increase understanding of global land evaporation, future research will focus on the global application of this methodology and the consideration of multiple evaporation models.
NASA Astrophysics Data System (ADS)
Zhu, Fanglong; Zhou, Yu; Liu, Suyan
2013-10-01
In this paper, we propose a new fractal model to determine the moisture effective diffusivity of porous membrane such as expanded polytetrafluorethylene membrane, by taking account of both parallel and perpendicular channels to diffusion flow direction. With the consideration of both the Knudsen and bulk diffusion effect, a relationship between micro-structural parameters and effective moisture diffusivity is deduced. The effective moisture diffusivities predicted by the present fractal model are compared with moisture diffusion experiment data and calculated values obtained from other theoretical models.
Uncertain soil moisture feedbacks in model projections of Sahel precipitation
NASA Astrophysics Data System (ADS)
Berg, Alexis; Lintner, Benjamin R.; Findell, Kirsten; Giannini, Alessandra
2017-06-01
Given the uncertainties in climate model projections of Sahel precipitation, at the northern edge of the West African Monsoon, understanding the factors governing projected precipitation changes in this semiarid region is crucial. This study investigates how long-term soil moisture changes projected under climate change may feedback on projected changes of Sahel rainfall, using simulations with and without soil moisture change from five climate models participating in the Global Land Atmosphere Coupling Experiment-Coupled Model Intercomparison Project phase 5 experiment. In four out of five models analyzed, soil moisture feedbacks significantly influence the projected West African precipitation response to warming; however, the sign of these feedbacks differs across the models. These results demonstrate that reducing uncertainties across model projections of the West African Monsoon requires, among other factors, improved mechanistic understanding and constraint of simulated land-atmosphere feedbacks, even at the large spatial scales considered here.
On the assimilation of satellite derived soil moisture in numerical weather prediction models
NASA Astrophysics Data System (ADS)
Drusch, M.
2006-12-01
Satellite derived surface soil moisture data sets are readily available and have been used successfully in hydrological applications. In many operational numerical weather prediction systems the initial soil moisture conditions are analysed from the modelled background and 2 m temperature and relative humidity. This approach has proven its efficiency to improve surface latent and sensible heat fluxes and consequently the forecast on large geographical domains. However, since soil moisture is not always related to screen level variables, model errors and uncertainties in the forcing data can accumulate in root zone soil moisture. Remotely sensed surface soil moisture is directly linked to the model's uppermost soil layer and therefore is a stronger constraint for the soil moisture analysis. Three data assimilation experiments with the Integrated Forecast System (IFS) of the European Centre for Medium-range Weather Forecasts (ECMWF) have been performed for the two months period of June and July 2002: A control run based on the operational soil moisture analysis, an open loop run with freely evolving soil moisture, and an experimental run incorporating bias corrected TMI (TRMM Microwave Imager) derived soil moisture over the southern United States through a nudging scheme using 6-hourly departures. Apart from the soil moisture analysis, the system setup reflects the operational forecast configuration including the atmospheric 4D-Var analysis. Soil moisture analysed in the nudging experiment is the most accurate estimate when compared against in-situ observations from the Oklahoma Mesonet. The corresponding forecast for 2 m temperature and relative humidity is almost as accurate as in the control experiment. Furthermore, it is shown that the soil moisture analysis influences local weather parameters including the planetary boundary layer height and cloud coverage. The transferability of the results to other satellite derived soil moisture data sets will be discussed.
Effect of intermediate layers on atomic layer deposition-aluminum oxide protected silver mirrors
NASA Astrophysics Data System (ADS)
Fryauf, David M.; Diaz Leon, Juan J.; Phillips, Andrew C.; Kobayashi, Nobuhiko P.
2017-07-01
This work investigates intermediate materials deposited between silver (Ag) thin-film mirrors and an aluminum oxide (AlOx) barrier overlayer and compares the effects on mirror durability to environmental stresses. Physical vapor deposition of various fluorides, oxides, and nitrides in combination with AlOx by atomic layer deposition (ALD) is used to develop several coating recipes. Ag-AlOx samples with different intermediate materials undergo aggressive high-temperature (80°C), high-humidity (80%) (HTHH) testing for 10 days. Reflectivity of mirror samples is measured before and after HTHH testing, and image processing techniques are used to analyze the specular surface of the samples after HTHH testing. Among the seven intermediate materials used in this work, TiN, MgAl2O4, NiO, and Al2O3 intermediate layers offer more robust protection against chemical corrosion and moisture when compared with samples with no intermediate layer. In addition, results show that the performance of the ALD-AlOx barrier overlayer depends significantly on the ALD-growth process temperature. Because higher durability is observed in samples with less transparent TiN and NiO layers, we propose a figure of merit based on post-HTHH testing reflectivity change and specular reflective mirror surface area remaining after HTHH testing to judge overall barrier performance.
Acosta, Oscar; Usaga, Jessie; Churey, John J; Worobo, Randy W; Padilla-Zakour, Olga I
2017-06-01
The low thermal tolerance of Salmonella enterica in foods with intermediate moisture levels, such as caramel sauces, ensures that mild heat treatment is sufficient to achieve 5-log reductions of this pathogen. This treatment mitigates the risk posed by salmonellae in raw materials; however, recontamination might occur because of survival of the pathogen in products that are not heated before consumption. This study was conducted to evaluate the effect of water activity (a w ) on the thermal tolerance and survival of S. enterica serovars Tennessee and Senftenberg. The D-values at 76, 78, and 80°C, z-values, and survival at 20.0 ± 0.5°C for 32 weeks of these two serovars were determined in goat's milk caramel at three a w values (0.85, 0.90, and 0.93). The highest thermal tolerance was observed at a w = 0.85 for Salmonella Senftenberg (D 76°C = 2.9 ± 0.3 min), and the lowest was at a w = 0.93 for Salmonella Tennessee (D 80°C = 0.131 ± 0.007 min). After a logarithmic transformation of the z-values, a significant interaction between serovar and a w was found (P < 0.0001), but no consistent trends were observed at the three evaluated a w levels for either serovar. Survival response was modeled using two sigmoidal three-parameter models. A significant interaction was found between nominal variables a w and serovar when comparing inflection points of the resulting curves: P < 0.0016 for the logistic model (R 2 = 0.91) and P < 0.0014 for the Gompertz model (R 2 = 0.92). Although a >8-log reduction was observed at week 20 of storage, regardless of the product's a w and the serovar, low levels of salmonellae were found in the product up to week 32 of storage. Our findings may assist the food industry with the establishment of critical limits for the safe thermal treatment of milk- and sugar-based foods with intermediate moisture levels. The survival data presented here highlight the relevance of implementing and effectively maintaining good sanitation and hygiene practices during the production of goat's milk caramel and similar food products.
Inferring Soil Moisture Memory from Streamflow Observations Using a Simple Water Balance Model
NASA Technical Reports Server (NTRS)
Orth, Rene; Koster, Randal Dean; Seneviratne, Sonia I.
2013-01-01
Soil moisture is known for its integrative behavior and resulting memory characteristics. Soil moisture anomalies can persist for weeks or even months into the future, making initial soil moisture a potentially important contributor to skill in weather forecasting. A major difficulty when investigating soil moisture and its memory using observations is the sparse availability of long-term measurements and their limited spatial representativeness. In contrast, there is an abundance of long-term streamflow measurements for catchments of various sizes across the world. We investigate in this study whether such streamflow measurements can be used to infer and characterize soil moisture memory in respective catchments. Our approach uses a simple water balance model in which evapotranspiration and runoff ratios are expressed as simple functions of soil moisture; optimized functions for the model are determined using streamflow observations, and the optimized model in turn provides information on soil moisture memory on the catchment scale. The validity of the approach is demonstrated with data from three heavily monitored catchments. The approach is then applied to streamflow data in several small catchments across Switzerland to obtain a spatially distributed description of soil moisture memory and to show how memory varies, for example, with altitude and topography.
NASA Astrophysics Data System (ADS)
Baldwin, D.; Manfreda, S.; Keller, K.; Smithwick, E. A. H.
2017-03-01
Satellite-based near-surface (0-2 cm) soil moisture estimates have global coverage, but do not capture variations of soil moisture in the root zone (up to 100 cm depth) and may be biased with respect to ground-based soil moisture measurements. Here, we present an ensemble Kalman filter (EnKF) hydrologic data assimilation system that predicts bias in satellite soil moisture data to support the physically based Soil Moisture Analytical Relationship (SMAR) infiltration model, which estimates root zone soil moisture with satellite soil moisture data. The SMAR-EnKF model estimates a regional-scale bias parameter using available in situ data. The regional bias parameter is added to satellite soil moisture retrievals before their use in the SMAR model, and the bias parameter is updated continuously over time with the EnKF algorithm. In this study, the SMAR-EnKF assimilates in situ soil moisture at 43 Soil Climate Analysis Network (SCAN) monitoring locations across the conterminous U.S. Multivariate regression models are developed to estimate SMAR parameters using soil physical properties and the moderate resolution imaging spectroradiometer (MODIS) evapotranspiration data product as covariates. SMAR-EnKF root zone soil moisture predictions are in relatively close agreement with in situ observations when using optimal model parameters, with root mean square errors averaging 0.051 [cm3 cm-3] (standard error, s.e. = 0.005). The average root mean square error associated with a 20-fold cross-validation analysis with permuted SMAR parameter regression models increases moderately (0.082 [cm3 cm-3], s.e. = 0.004). The expected regional-scale satellite correction bias is negative in four out of six ecoregions studied (mean = -0.12 [-], s.e. = 0.002), excluding the Great Plains and Eastern Temperate Forests (0.053 [-], s.e. = 0.001). With its capability of estimating regional-scale satellite bias, the SMAR-EnKF system can predict root zone soil moisture over broad extents and has applications in drought predictions and other operational hydrologic modeling purposes.
Qi, Sheng; Belton, Peter; McAuley, William; Codoni, Doroty; Darji, Neerav
2013-04-01
Gelucire 50/13, a polyoxyethylene glycol glyceride mixture, has been widely used in drug delivery, but its moisture uptake behaviour is still poorly understood. In this study, the effects of relative humidity, temperature, and drug incorporation on the moisture uptake of Gelucire are reported in relation to their practical implications for preparation of solid dispersions using this material. DVS combined with kinetics modelling was used as the main experimental method to study the moisture uptake behaviour of Gelucire. Thermal and microscopic methods were employed to investigate the effect of moisture uptake on the physical properties of the material and drug loaded solid dispersions. The moisture uptake by Gelucire 50/13 is temperature and relative humidity dependent. At low temperatures and low relative humidities, moisture sorption follows a GAB model. The model fitting indicated that at high relative humidities the sorption is a complex process, potentially involving PEG being dissolved and the PEG solution acting as solvent to dissolve other components. Careful control of the storage and processing environmental conditions are required when using Gelucire 50/13. The incorporation of model drugs not only influences the moisture uptake capacity of Gelucire 50/13 but also the solidification behaviour.
Land-atmosphere coupling and soil moisture memory contribute to long-term agricultural drought
NASA Astrophysics Data System (ADS)
Kumar, S.; Newman, M.; Lawrence, D. M.; Livneh, B.; Lombardozzi, D. L.
2017-12-01
We assessed the contribution of land-atmosphere coupling and soil moisture memory on long-term agricultural droughts in the US. We performed an ensemble of climate model simulations to study soil moisture dynamics under two atmospheric forcing scenarios: active and muted land-atmosphere coupling. Land-atmosphere coupling contributes to a 12% increase and 36% decrease in the decorrelation time scale of soil moisture anomalies in the US Great Plains and the Southwest, respectively. These differences in soil moisture memory affect the length and severity of modeled drought. Consequently, long-term droughts are 10% longer and 3% more severe in the Great Plains, and 15% shorter and 21% less severe in the Southwest. An analysis of Coupled Model Intercomparsion Project phase 5 data shows four fold uncertainty in soil moisture memory across models that strongly affects simulated long-term droughts and is potentially attributable to the differences in soil water storage capacity across models.
Assimilation of Passive and Active Microwave Soil Moisture Retrievals
NASA Technical Reports Server (NTRS)
Draper, C. S.; Reichle, R. H.; DeLannoy, G. J. M.; Liu, Q.
2012-01-01
Root-zone soil moisture is an important control over the partition of land surface energy and moisture, and the assimilation of remotely sensed near-surface soil moisture has been shown to improve model profile soil moisture [1]. To date, efforts to assimilate remotely sensed near-surface soil moisture at large scales have focused on soil moisture derived from the passive microwave Advanced Microwave Scanning Radiometer (AMSR-E) and the active Advanced Scatterometer (ASCAT; together with its predecessor on the European Remote Sensing satellites (ERS. The assimilation of passive and active microwave soil moisture observations has not yet been directly compared, and so this study compares the impact of assimilating ASCAT and AMSR-E soil moisture data, both separately and together. Since the soil moisture retrieval skill from active and passive microwave data is thought to differ according to surface characteristics [2], the impact of each assimilation on the model soil moisture skill is assessed according to land cover type, by comparison to in situ soil moisture observations.
Qi, Guangxia; Yue, Dongbei; Liu, Jianguo; Li, Rui; Shi, Xiaochong; He, Liang; Guo, Jingting; Miao, Haomei; Nie, Yongfeng
2013-10-15
Waste samples at different depths of a covered municipal solid waste (MSW) landfill in Beijing, China, were excavated and characterized to investigate the impact of intermediate soil cover on waste stabilization. A comparatively high amount of unstable organic matter with 83.3 g kg(-1) dry weight (dw) total organic carbon was detected in the 6-year-old MSW, where toxic inorganic elements containing As, Cd, Cr, Cu, Mn, Ni, Pb, and Zn of 10.1, 0.98, 85.49, 259.7, 530.4, 30.5, 84.0, and 981.7 mg kg(-1) dw, respectively, largely accumulated because of the barrier effect of intermediate soil cover. This accumulation resulted in decreased microbial activities. The intermediate soil cover also caused significant reduction in moisture in MSW under the soil layer, which was as low as 25.9%, and led to inefficient biodegradation of 8- and 10-year-old MSW. Therefore, intermediate soil cover with low permeability seems to act as a barrier that divides a landfill into two landfill cells with different degradation processes by restraining water flow and hazardous matter. Copyright © 2013 Elsevier Ltd. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhu, Chunmei; Leung, Lai R.; Gochis, David
2009-11-29
The influence of antecedent soil moisture on North American monsoon system (NAMS) precipitation variability was explored using the MM5 mesoscale model coupled with the Variable Infiltration Capacity (VIC) land surface model. Sensitivity experiments were performed with extreme wet and dry initial soil moisture conditions for both the 1984 wet monsoon year and the 1989 dry year. The MM5-VIC model reproduced the key features of NAMS in 1984 and 1989 especially over northwestern Mexico. Our modeling results indicate that the land surface has memory of the initial soil wetness prescribed at the onset of the monsoon that persists over most ofmore » the region well into the monsoon season (e.g. until August). However, in contrast to the classical thermal contrast concept, where wetter soils lead to cooler surface temperatures, less land-sea thermal contrast, weaker monsoon circulations and less precipitation, the coupled model consistently demonstrated a positive soil moisture – precipitation feedback. Specifically, anomalously wet premonsoon soil moisture always lead to enhanced monsoon precipitation, and the reverse was also true. The surface temperature changes induced by differences in surface energy flux partitioning associated with pre-monsoon soil moisture anomalies changed the surface pressure and consequently the flow field in the coupled model, which in turn changed moisture convergence and, accordingly, precipitation patterns. Both the largescale circulation change and local land-atmospheric interactions in response to premonsoon soil moisture anomalies play important roles in the coupled model’s positive soil moisture monsoon precipitation feedback. However, the former may be sensitive to the strength and location of the thermal anomalies, thus leaving open the possibility of both positive and negative soil moisture precipitation feedbacks.« less
NASA Technical Reports Server (NTRS)
Bolten, John D.; Crow, Wade T.; Zhan, Xiwu; Jackson, Thomas J.; Reynolds,Curt
2010-01-01
Soil moisture is a fundamental data source used by the United States Department of Agriculture (USDA) International Production Assessment Division (IPAD) to monitor crop growth stage and condition and subsequently, globally forecast agricultural yields. Currently, the USDA IPAD estimates surface and root-zone soil moisture using a two-layer modified Palmer soil moisture model forced by global precipitation and temperature measurements. However, this approach suffers from well-known errors arising from uncertainty in model forcing data and highly simplified model physics. Here we attempt to correct for these errors by designing and applying an Ensemble Kalman filter (EnKF) data assimilation system to integrate surface soil moisture retrievals from the NASA Advanced Microwave Scanning Radiometer (AMSR-E) into the USDA modified Palmer soil moisture model. An assessment of soil moisture analysis products produced from this assimilation has been completed for a five-year (2002 to 2007) period over the North American continent between 23degN - 50degN and 128degW - 65degW. In particular, a data denial experimental approach is utilized to isolate the added utility of integrating remotely-sensed soil moisture by comparing EnKF soil moisture results obtained using (relatively) low-quality precipitation products obtained from real-time satellite imagery to baseline Palmer model runs forced with higher quality rainfall. An analysis of root-zone anomalies for each model simulation suggests that the assimilation of AMSR-E surface soil moisture retrievals can add significant value to USDA root-zone predictions derived from real-time satellite precipitation products.
Prediction of moisture variation during composting process: A comparison of mathematical models.
Wang, Yongjiang; Ai, Ping; Cao, Hongliang; Liu, Zhigang
2015-10-01
This study was carried out to develop and compare three models for simulating the moisture content during composting. Model 1 described changes in water content using mass balance, while Model 2 introduced a liquid-gas transferred water term. Model 3 predicted changes in moisture content without complex degradation kinetics. Average deviations for Model 1-3 were 8.909, 7.422 and 5.374 kg m(-3) while standard deviations were 10.299, 8.374 and 6.095, respectively. The results showed that Model 1 is complex and involves more state variables, but can be used to reveal the effect of humidity on moisture content. Model 2 tested the hypothesis of liquid-gas transfer and was shown to be capable of predicting moisture content during composting. Model 3 could predict water content well without considering degradation kinetics. Copyright © 2015 Elsevier Ltd. All rights reserved.
What is the philosophy of modelling soil moisture movement?
NASA Astrophysics Data System (ADS)
Chen, J.; Wu, Y.
2009-12-01
In laboratory, the soil moisture movement in the different soil textures has been analysed. From field investigation, at a spot, the soil moisture movement in the root zone, vadose zone and shallow aquifer has been explored. In addition, on ground slopes, the interflow in the near surface soil layers has been studied. Along the regions near river reaches, the expansion and shrink of the saturated area due to rainfall occurrences have been observed. From those previous explorations regarding soil moisture movement, numerical models to represent this hydrologic process have been developed. However, generally, due to high heterogeneity and stratification of soil in a basin, modelling soil moisture movement is rather challenging. Normally, some empirical equations or artificial manipulation are employed to adjust the soil moisture movement in various numerical models. In this study, we inspect the soil moisture movement equations used in a watershed model, SWAT (Soil and Water Assessment Tool) (Neitsch et al., 2005), to examine the limitations of our knowledge in such a hydrologic process. Then, we adopt the features of a topographic-information based on a hydrologic model, TOPMODEL (Beven and Kirkby, 1979), to enhance the representation of soil moisture movement in SWAT. Basically, the results of the study reveal, to some extent, the philosophy of modelling soil moisture movement in numerical models, which will be presented in the conference. Beven, K.J. and Kirkby, M.J., 1979. A physically based variable contributing area model of basin hydrology. Hydrol. Science Bulletin, 24: 43-69. Neitsch, S.L., Arnold, J.G., Kiniry, J.R., Williams, J.R. and King, K.W., 2005. Soil and Water Assessment Tool Theoretical Documentation, Grassland, soil and research service, Temple, TX.
Electrical Imaging of Roots and Trunks
NASA Astrophysics Data System (ADS)
Al Hagrey, S.; Werban, U.; Meissner, R.; Ismaeil, A.; Rabbel, W.
2005-05-01
We applied geoelectric and GPR techniques to analyze problems of botanical structures and even processes, e.g., mapping root zones, internal structure of trunks, and water uptake by roots. The dielectric nature of root zones and trunks is generally a consequence of relatively high moisture content. The electric method, applied to root zones, can discriminate between old, thick, isolated roots (high resistivity) and the network of young, active, and hydraulically conductive zones (low resistivity). Both types of roots show low radar velocity and a strong attenuation caused by the dominant effect of moisture (high dielectric constant) on the electromagnetic wave propagation. Single root branches could be observed in radargrams by their reflection and diffraction parabolas. We have perfected the inversion method for perfect and imperfect cylindrical objects, such as trunks, and developed a new multielectrodes (needle or gel) ring array for fast applications on living trees and discs. Using synthetic models we tested the technique successfully and analyzed it as a function of total electrode number and configuration. Measurements at a trunk show a well established inverse relationship between the imaged resistivity and the moisture content determined from cores. The central resistivity maximum of healthy trees strongly decreases toward the rim. This agrees with the moisture decrease to the outside where active sap flow processes take place. Branching, growth anomalies (new or old shoots) and meteorological effects (sunshine and wind direction) lead to deviations of the concentric electric structure. The strongest anomalies are related to infections causing wet, rotting spots or cavities. The heartwood resistivity is highest in olive and oak trunks, intermediate in young fruit trees and lowest in cork oak trunks that are considered to be anomalously wet. Compared to acoustic tomography our electric technique shows a better resolution in imaging internal ring structures where moisture is the most dominating factor. We conclude that our imaging resistivity technique is applicable for investigating or controlling the botanical and physical conditions of endangered trees (health inspection) and capable to monitor dynamic processes of sap flow if adequate tracers are used.
Remotely sensed soil moisture input to a hydrologic model
NASA Technical Reports Server (NTRS)
Engman, E. T.; Kustas, W. P.; Wang, J. R.
1989-01-01
The possibility of using detailed spatial soil moisture maps as input to a runoff model was investigated. The water balance of a small drainage basin was simulated using a simple storage model. Aircraft microwave measurements of soil moisture were used to construct two-dimensional maps of the spatial distribution of the soil moisture. Data from overflights on different dates provided the temporal changes resulting from soil drainage and evapotranspiration. The study site and data collection are described, and the soil measurement data are given. The model selection is discussed, and the simulation results are summarized. It is concluded that a time series of soil moisture is a valuable new type of data for verifying model performance and for updating and correcting simulated streamflow.
We have developed a coupled land-surface and dry deposition model for realistic treatment of surface fluxes of heat, moisture, and chemical dry deposition within a comprehensive air quality modeling system. A new land-surface model (LSM) with explicit treatment of soil moisture...
The Value of SMAP Soil Moisture Observations For Agricultural Applications
NASA Astrophysics Data System (ADS)
Mladenova, I. E.; Bolten, J. D.; Crow, W.; Reynolds, C. A.
2017-12-01
Knowledge of the amount of soil moisture (SM) in the root zone (RZ) is critical source of information for crop analysts and agricultural agencies as it controls crop development and crop condition changes and can largely impact end-of-season yield. Foreign Agricultural Services (FAS), a subdivision of U.S. Department of Agriculture (USDA) that is in charge with providing information on current and expected global crop supply and demand estimates, has been relying on RZSM estimates generated by the modified two-layer Palmer model, which has been enhanced to allow the assimilation of satellite-based soil moisture data. Generally the accuracy of model-based soil moisture estimates is dependent on the precision of the forcing data that drives the model and more specifically, the accuracy of the precipitation data. Data assimilation gives the opportunity to correct for such precipitation-related inaccuracies and enhance the quality of the model estimates. Here we demonstrate the value of ingesting passive-based soil moisture observations derived from the Soil Moisture Active Passive (SMAP) mission. In terms of agriculture, general understanding is that the change in soil moisture conditions precede the change in vegetation status, suggesting that soil moisture can be used as an early indicator of expected crop conditions. Therefore, we assess the accuracy of the SMAP enhanced Palmer model by examining the lag rank cross-correlation coefficient between the model generated soil moisture observations and the Normalized Difference Vegetation Index (NDVI).
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.
Assimilation of SMOS Retrieved Soil Moisture into the Land Information System
NASA Technical Reports Server (NTRS)
Blankenship, Clay; Case, Jonathan; Zavodsky, Bradley; Jedlovec, Gary
2014-01-01
Soil moisture retrievals from the Soil Moisture and Ocean Salinity (SMOS) instrument are assimilated into the Noah land surface model (LSM) within the NASA Land Information System (LIS). Before assimilation, SMOS retrievals are bias-corrected to match the model climatological distribution using a Cumulative Distribution Function (CDF) matching approach. Data assimilation is done via the Ensemble Kalman Filter. The goal is to improve the representation of soil moisture within the LSM, and ultimately to improve numerical weather forecasts through better land surface initialization. We present a case study showing a large area of irrigation in the lower Mississippi River Valley, in an area with extensive rice agriculture. High soil moisture value in this region are observed by SMOS, but not captured in the forcing data. After assimilation, the model fields reflect the observed geographic patterns of soil moisture. Plans for a modeling experiment and operational use of the data are given. This work helps prepare for the assimilation of Soil Moisture Active/Passive (SMAP) retrievals in the near future.
NASA Astrophysics Data System (ADS)
Schreiner-McGraw, A. P.; Vivoni, E. R.; Mascaro, G.; Franz, T. E.
2016-01-01
Soil moisture dynamics reflect the complex interactions of meteorological conditions with soil, vegetation and terrain properties. In this study, intermediate-scale soil moisture estimates from the cosmic-ray neutron sensing (CRNS) method are evaluated for two semiarid ecosystems in the southwestern United States: a mesquite savanna at the Santa Rita Experimental Range (SRER) and a mixed shrubland at the Jornada Experimental Range (JER). Evaluations of the CRNS method are performed for small watersheds instrumented with a distributed sensor network consisting of soil moisture sensor profiles, an eddy covariance tower, and runoff flumes used to close the water balance. We found a very good agreement between the CRNS method and the distributed sensor network (root mean square error (RMSE) of 0.009 and 0.013 m3 m-3 at SRER and JER, respectively) at the hourly timescale over the 19-month study period, primarily due to the inclusion of 5 cm observations of shallow soil moisture. Good agreement was also obtained in soil moisture changes estimated from the CRNS and watershed water balance methods (RMSE of 0.001 and 0.082 m3 m-3 at SRER and JER, respectively), with deviations due to bypassing of the CRNS measurement depth during large rainfall events. Once validated, the CRNS soil moisture estimates were used to investigate hydrological processes at the footprint scale at each site. Through the computation of the water balance, we showed that drier-than-average conditions at SRER promoted plant water uptake from deeper soil layers, while the wetter-than-average period at JER resulted in percolation towards deeper soils. The CRNS measurements were then used to quantify the link between evapotranspiration and soil moisture at a commensurate scale, finding similar predictive relations at both sites that are applicable to other semiarid ecosystems in the southwestern US.
Soil Moisture and the Persistence of North American Drought.
NASA Astrophysics Data System (ADS)
Oglesby, Robert J.; Erickson, David J., III
1989-11-01
We describe numerical sensitivity experiments exploring the effects of soil moisture on North American summertime climate using the NCAR CCMI, a 12-layer global atmospheric general circulation model. In particular. the hypothesis that reduced soil moisture may help induce and amplify warm, dry summers over midlatitude continental interiors is examined. Equilibrium climate statistics are computed for the perpetual July model response to imposed soil moisture anomalies over North America between 36° and 49°N. In addition, the persistence of imposed soil moisture anomalies is examined through use of the seasonal cycle mode of operation with use of various initial atmospheric states both equilibrated and nonequilibrated to the initial soil moisture anomaly.The climate statistics generated by thew model simulations resemble in a general way those of the summer of 1988, when extensive heat and drought occurred over much of North America. A reduction in soil moisture in the model leads to an increase in surface temperature, lower surface pressure, increased ridging aloft, and a northward shift of the jet stream. Low-level moisture advection from the Gulf of Mexico is important in determining where persistent soil moisture deficits can be maintained. In seasonal cycle simulations, it lock longer for an initially unequilibrated atmosphere to respond to the imposed soil moisture anomaly, via moisture transport from the Gulf of Mexico, than when initially the atmosphere was in equilibrium with the imposed anomaly., i.e., the initial state was obtained from the appropriate perpetual July simulation. The results demonstrate the important role of soil moisture in prolonging and/or amplifying North American summertime drought.
NASA Astrophysics Data System (ADS)
Zhang, Shuwen; Li, Haorui; Zhang, Weidong; Qiu, Chongjian; Li, Xin
2005-11-01
The paper investigates the ability to retrieve the true soil moisture profile by assimilating near-surface soil moisture into a soil moisture model with an ensemble Kaiman filter (EnKF) assimilation scheme, including the effect of ensemble size, update interval and nonlinearities in the profile retrieval, the required time for full retrieval of the soil moisture profiles, and the possible influence of the depth of the soil moisture observation. These questions are addressed by a desktop study using synthetic data. The “true” soil moisture profiles are generated from the soil moisture model under the boundary condition of 0.5 cm d-1 evaporation. To test the assimilation schemes, the model is initialized with a poor initial guess of the soil moisture profile, and different ensemble sizes are tested showing that an ensemble of 40 members is enough to represent the covariance of the model forecasts. Also compared are the results with those from the direct insertion assimilation scheme, showing that the EnKF is superior to the direct insertion assimilation scheme, for hourly observations, with retrieval of the soil moisture profile being achieved in 16 h as compared to 12 days or more. For daily observations, the true soil moisture profile is achieved in about 15 days with the EnKF, but it is impossible to approximate the true moisture within 18 days by using direct insertion. It is also found that observation depth does not have a significant effect on profile retrieval time for the EnKF. The nonlinearities have some negative influence on the optimal estimates of soil moisture profile but not very seriously.
NASA Astrophysics Data System (ADS)
Drusch, M.
2007-02-01
Satellite-derived surface soil moisture data sets are readily available and have been used successfully in hydrological applications. In many operational numerical weather prediction systems the initial soil moisture conditions are analyzed from the modeled background and 2 m temperature and relative humidity. This approach has proven its efficiency to improve surface latent and sensible heat fluxes and consequently the forecast on large geographical domains. However, since soil moisture is not always related to screen level variables, model errors and uncertainties in the forcing data can accumulate in root zone soil moisture. Remotely sensed surface soil moisture is directly linked to the model's uppermost soil layer and therefore is a stronger constraint for the soil moisture analysis. For this study, three data assimilation experiments with the Integrated Forecast System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF) have been performed for the 2-month period of June and July 2002: a control run based on the operational soil moisture analysis, an open loop run with freely evolving soil moisture, and an experimental run incorporating TMI (TRMM Microwave Imager) derived soil moisture over the southern United States. In this experimental run the satellite-derived soil moisture product is introduced through a nudging scheme using 6-hourly increments. Apart from the soil moisture analysis, the system setup reflects the operational forecast configuration including the atmospheric 4D-Var analysis. Soil moisture analyzed in the nudging experiment is the most accurate estimate when compared against in situ observations from the Oklahoma Mesonet. The corresponding forecast for 2 m temperature and relative humidity is almost as accurate as in the control experiment. Furthermore, it is shown that the soil moisture analysis influences local weather parameters including the planetary boundary layer height and cloud coverage.
SMERGE: A multi-decadal root-zone soil moisture product for CONUS
NASA Astrophysics Data System (ADS)
Crow, W. T.; Dong, J.; Tobin, K. J.; Torres, R.
2017-12-01
Multi-decadal root-zone soil moisture products are of value for a range of water resource and climate applications. The NASA-funded root-zone soil moisture merging project (SMERGE) seeks to develop such products through the optimal merging of land surface model predictions with surface soil moisture retrievals acquired from multi-sensor remote sensing products. This presentation will describe the creation and validation of a daily, multi-decadal (1979-2015), vertically-integrated (both surface to 40 cm and surface to 100 cm), 0.125-degree root-zone product over the contiguous United States (CONUS). The modeling backbone of the system is based on hourly root-zone soil moisture simulations generated by the Noah model (v3.2) operating within the North American Land Data Assimilation System (NLDAS-2). Remotely-sensed surface soil moisture retrievals are taken from the multi-sensor European Space Agency Climate Change Initiative soil moisture data set (ESA CCI SM). In particular, the talk will detail: 1) the exponential smoothing approach used to convert surface ESA CCI SM retrievals into root-zone soil moisture estimates, 2) the averaging technique applied to merge (temporally-sporadic) remotely-sensed with (continuous) NLDAS-2 land surface model estimates of root-zone soil moisture into the unified SMERGE product, and 3) the validation of the SMERGE product using long-term, ground-based soil moisture datasets available within CONUS.
NASA Astrophysics Data System (ADS)
Chen, M.; Willgoose, G. R.; Saco, P. M.
2009-12-01
This paper investigates the soil moisture dynamics over two subcatchments (Stanley and Krui) in the Goulburn River in NSW during a three year period (2005-2007) using the Hydrus 1-D unsaturated soil water flow model. The model was calibrated to the seven Stanley microcatchment sites (1 sqkm site) using continuous time surface 30cm and full profile soil moisture measurements. Soil type, leaf area index and soil depth were found to be the key parameters changing model fit to the soil moisture time series. They either shifted the time series up or down, changed the steepness of dry-down recessions or determined the lowest point of soil moisture dry-down respectively. Good correlations were obtained between observed and simulated soil water storage (R=0.8-0.9) when calibrated parameters for one site were applied to the other sites. Soil type was also found to be the main determinant (after rainfall) of the mean of modelled soil moisture time series. Simulations of top 30cm were better than those of the whole soil profile. Within the Stanley microcatchment excellent soil moisture matches could be generated simply by adjusting the mean of soil moisture up or down slightly. Only minor modification of soil properties from site to site enable good fits for all of the Stanley sites. We extended the predictions of soil moisture to a larger spatial scale of the Krui catchment (sites up to 30km distant from Stanley) using soil and vegetation parameters from Stanley but the locally recorded rainfall at the soil moisture measurement site. The results were encouraging (R=0.7~0.8). These results show that it is possible to use a calibrated soil moisture model to extrapolate the soil moisture to other sites for a catchment with an area of up to 1000km2. This paper demonstrates the potential usefulness of continuous time, point scale soil moisture (typical of that measured by permanently installed TDR probes) in predicting the soil wetness status over a catchment of significant size.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Woods, Jason; Winkler, Jon
Moisture adsorption and desorption in building materials impact indoor humidity. This effect should be included in building-energy simulations, particularly when humidity is being investigated or controlled. Several models can calculate this moisture-buffering effect, but accurate ones require model inputs that are not always known to the user of the building-energy simulation. This research developed an empirical method to extract whole-house model inputs for the effective moisture penetration depth (EMPD) model. The experimental approach was to subject the materials in the house to a square-wave relative-humidity profile, measure all of the moisture-transfer terms (e.g., infiltration, air-conditioner condensate), and calculate the onlymore » unmeasured term—the moisture sorption into the materials. We validated this method with laboratory measurements, which we used to measure the EMPD model inputs of two houses. After deriving these inputs, we measured the humidity of the same houses during tests with realistic latent and sensible loads and demonstrated the accuracy of this approach. Furthermore, these results show that the EMPD model, when given reasonable inputs, is an accurate moisture-buffering model.« less
NASA Astrophysics Data System (ADS)
Chen, Zhuowei; Shi, Liangsheng; Ye, Ming; Zhu, Yan; Yang, Jinzhong
2018-06-01
Nitrogen reactive transport modeling is subject to uncertainty in model parameters, structures, and scenarios. By using a new variance-based global sensitivity analysis method, this paper identifies important parameters for nitrogen reactive transport with simultaneous consideration of these three uncertainties. A combination of three scenarios of soil temperature and two scenarios of soil moisture creates a total of six scenarios. Four alternative models describing the effect of soil temperature and moisture content are used to evaluate the reduction functions used for calculating actual reaction rates. The results show that for nitrogen reactive transport problem, parameter importance varies substantially among different models and scenarios. Denitrification and nitrification process is sensitive to soil moisture content status rather than to the moisture function parameter. Nitrification process becomes more important at low moisture content and low temperature. However, the changing importance of nitrification activity with respect to temperature change highly relies on the selected model. Model-averaging is suggested to assess the nitrification (or denitrification) contribution by reducing the possible model error. Despite the introduction of biochemical heterogeneity or not, fairly consistent parameter importance rank is obtained in this study: optimal denitrification rate (Kden) is the most important parameter; reference temperature (Tr) is more important than temperature coefficient (Q10); empirical constant in moisture response function (m) is the least important one. Vertical distribution of soil moisture but not temperature plays predominant role controlling nitrogen reaction. This study provides insight into the nitrogen reactive transport modeling and demonstrates an effective strategy of selecting the important parameters when future temperature and soil moisture carry uncertainties or when modelers face with multiple ways of establishing nitrogen models.
NASA Astrophysics Data System (ADS)
Legates, David R.; Junghenn, Katherine T.
2018-04-01
Many local weather station networks that measure a number of meteorological variables (i.e. , mesonetworks) have recently been established, with soil moisture occasionally being part of the suite of measured variables. These mesonetworks provide data from which detailed estimates of various hydrological parameters, such as precipitation and reference evapotranspiration, can be made which, when coupled with simple surface characteristics available from soil surveys, can be used to obtain estimates of soil moisture. The question is Can meteorological data be used with a simple hydrologic model to estimate accurately daily soil moisture at a mesonetwork site? Using a state-of-the-art mesonetwork that also includes soil moisture measurements across the US State of Delaware, the efficacy of a simple, modified Thornthwaite/Mather-based daily water balance model based on these mesonetwork observations to estimate site-specific soil moisture is determined. Results suggest that the model works reasonably well for most well-drained sites and provides good qualitative estimates of measured soil moisture, often near the accuracy of the soil moisture instrumentation. The model exhibits particular trouble in that it cannot properly simulate the slow drainage that occurs in poorly drained soils after heavy rains and interception loss, resulting from grass not being short cropped as expected also adversely affects the simulation. However, the model could be tuned to accommodate some non-standard siting characteristics.
Klinzing, Gerard R; Zavaliangos, Antonios
2016-08-01
This work establishes a predictive model that explicitly recognizes microstructural parameters in the description of the overall mass uptake and local gradients of moisture into tablets. Model equations were formulated based on local tablet geometry to describe the transient uptake of moisture. An analytical solution to a simplified set of model equations was solved to predict the overall mass uptake and moisture gradients with the tablets. The analytical solution takes into account individual diffusion mechanisms in different scales of porosity and diffusion into the solid phase. The time constant of mass uptake was found to be a function of several key material properties, such as tablet relative density, pore tortuosity, and equilibrium moisture content of the material. The predictions of the model are in excellent agreement with experimental results for microcrystalline cellulose tablets without the need for parameter fitting. The model presented provides a new method to analyze the transient uptake of moisture into hydrophilic materials with the knowledge of only a few fundamental material and microstructural parameters. In addition, the model allows for quick and insightful predictions of moisture diffusion for a variety of practical applications including pharmaceutical tablets, porous polymer systems, or cementitious materials. Copyright © 2016 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Wanders, N.; Karssenberg, D.; Bierkens, M. F. P.; Van Dam, J. C.; De Jong, S. M.
2012-04-01
Soil moisture is a key variable in the hydrological cycle and important in hydrological modelling. When assimilating soil moisture into flood forecasting models, the improvement of forecasting skills depends on the ability to accurately estimate the spatial and temporal patterns of soil moisture content throughout the river basin. Space-borne remote sensing may provide this information with a high temporal and spatial resolution and with a global coverage. Currently three microwave soil moisture products are available: AMSR-E, ASCAT and SMOS. The quality of these satellite-based products is often assessed by comparing them with in-situ observations of soil moisture. This comparison is however hampered by the difference in spatial and temporal support (i.e., resolution, scale), because the spatial resolution of microwave satellites is rather low compared to in-situ field measurements. Thus, the aim of this study is to derive a method to assess the uncertainty of microwave satellite soil moisture products at the correct spatial support. To overcome the difference in support size between in-situ soil moisture observations and remote sensed soil moisture, we used a stochastic, distributed unsaturated zone model (SWAP, van Dam (2000)) that is upscaled to the support of different satellite products. A detailed assessment of the SWAP model uncertainty is included to ensure that the uncertainty in satellite soil moisture is not overestimated due to an underestimation of the model uncertainty. We simulated unsaturated water flow up to a depth of 1.5m with a vertical resolution of 1 to 10 cm and on a horizontal grid of 1 km2 for the period Jan 2010 - Jun 2011. The SWAP model was first calibrated and validated on in-situ data of the REMEDHUS soil moisture network (Spain). Next, to evaluate the satellite products, the model was run for areas in the proximity of 79 meteorological stations in Spain, where model results were aggregated to the correct support of the satellite product by averaging model results from the 1 km2 grid within the remote sensing footprint. Overall 440 (AMSR-E, SMOS) to 680 (ASCAT) timeseries were compared to the aggregated SWAP model results, providing valuable information on the uncertainty of satellite soil moisture at the proper support. Our results show that temporal dynamics are best captured by ASCAT resulting in an average correlation of 0.72 with the model, while ASMR-E (0.41) and SMOS (0.42) are less capable of representing these dynamics. Standard deviations found for ASCAT and SMOS are low, 0.049 and 0.051m3m-3 respectively, while AMSR-E has a higher value of 0.062m3m-3. All standard deviations are higher than the average model uncertainty of 0.017m3m-3. All satellite products show a negative bias compared to the model results, with the largest value for SMOS. Satellite uncertainty is not found to be significantly related to topography, but is found to increase in densely vegetated areas. In general AMSR-E has most difficulties capturing soil moisture dynamics in Spain, while SMOS and mainly ASCAT have a fair to good performance. However, all products contain valuable information about the near-surface soil moisture over Spain. Van Dam, J.C., 2000, Field scale water flow and solute transport. SWAP model concepts, parameter estimation and case studies. Ph.D. thesis, Wageningen University
NASA Astrophysics Data System (ADS)
Ramírez, Beatriz H.; Teuling, Adriaan J.; Ganzeveld, Laurens; Hegger, Zita; Leemans, Rik
2017-09-01
Mountain areas are characterized by a large heterogeneity in hydrological and meteorological conditions. This heterogeneity is currently poorly represented by gauging networks and by the coarse scale of global and regional climate and hydrological models. Tropical Montane Cloud Forests (TMCFs) are found in a narrow elevation range and are characterized by persistent fog. Their water balance depends on local and upwind temperatures and moisture, therefore, changes in these parameters will alter TMCF hydrology. Until recently the hydrological functioning of TMCFs was mainly studied in coastal regions, while continental TMCFs were largely ignored. This study contributes to fill this gap by focusing on a TMCF which is located on the northern eastern Andes at an elevation of 1550-2300 m asl, in the Orinoco river basin highlands. In this study, we describe the spatial and seasonal meteorological variability, analyse the corresponding catchment hydrological response to different land cover, and perform a sensitivity analysis on uncertainties related to rainfall interpolation, catchment area estimation and streamflow measurements. Hydro-meteorological measurements, including hourly solar radiation, temperature, relative humidity, wind speed, precipitation, soil moisture and streamflow, were collected from June 2013 to May 2014 at three gauged neighbouring catchments with contrasting TMCF/grassland cover and less than 250 m elevation difference. We found wetter and less seasonally contrasting conditions at higher elevations, indicating a positive relation between elevation and fog or rainfall persistence. This pattern is similar to that of other eastern Andean TMCFs, however, the study site had higher wet season rainfall and lower dry season rainfall suggesting that upwind contrasts in land cover and moisture can influence the meteorological conditions at eastern Andean TMCFs. Contrasting streamflow dynamics between the studied catchments reflect the overall system response as a function of the catchments' elevation and land cover. The forested catchment, located at the higher elevations, had the highest seasonal streamflows. During the wet season, different land covers at the lower elevations were important in defining the streamflow responses between the deforested catchment and the catchment with intermediate forest cover. Streamflows were higher and the rainfall-runoff responses were faster in the deforested catchment than in the intermediate forest cover catchment. During the dry season, the catchments' elevation defined streamflows due to higher water inputs and lower evaporative demand at the higher elevations.
Measuring Moisture Levels in Graphite Epoxy Composite Sandwich Structures
NASA Technical Reports Server (NTRS)
Nurge, Mark; Youngquist, Robert; Starr, Stanley
2011-01-01
Graphite epoxy composite (GEC) materials are used in the construction of rocket fairings, nose cones, interstage adapters, and heat shields due to their high strength and light weight. However, they absorb moisture depending on the environmental conditions they are exposed to prior to launch. Too much moisture absorption can become a problem when temperature and pressure changes experienced during launch cause the water to vaporize. The rapid state change of the water can result in structural failure of the material. In addition, heat and moisture combine to weaken GEC structures. Diffusion models that predict the total accumulated moisture content based on the environmental conditions are one accepted method of determining if the material strength has been reduced to an unacceptable level. However, there currently doesn t exist any field measurement technique to estimate the actual moisture content of a composite structure. A multi-layer diffusion model was constructed with Mathematica to predict moisture absorption and desorption from the GEC sandwich structure. This model is used in conjunction with relative humidity/temperature sensors both on the inside and outside of the material to determine the moisture levels in the structure. Because the core materials have much higher diffusivity than the face sheets, a single relative humidity measurement will accurately reflect the moisture levels in the core. When combined with an external relative humidity measurement, the model can be used to determine the moisture levels in the face sheets. Since diffusion is temperaturedependent, the temperature measurements are used to determine the diffusivity of the face sheets for the model computations.
NASA Technical Reports Server (NTRS)
Maggioni, V.; Anagnostou, E. N.; Reichle, R. H.
2013-01-01
The contribution of rainfall forcing errors relative to model (structural and parameter) uncertainty in the prediction of soil moisture is investigated by integrating the NASA Catchment Land Surface Model (CLSM), forced with hydro-meteorological data, in the Oklahoma region. Rainfall-forcing uncertainty is introduced using a stochastic error model that generates ensemble rainfall fields from satellite rainfall products. The ensemble satellite rain fields are propagated through CLSM to produce soil moisture ensembles. Errors in CLSM are modeled with two different approaches: either by perturbing model parameters (representing model parameter uncertainty) or by adding randomly generated noise (representing model structure and parameter uncertainty) to the model prognostic variables. Our findings highlight that the method currently used in the NASA GEOS-5 Land Data Assimilation System to perturb CLSM variables poorly describes the uncertainty in the predicted soil moisture, even when combined with rainfall model perturbations. On the other hand, by adding model parameter perturbations to rainfall forcing perturbations, a better characterization of uncertainty in soil moisture simulations is observed. Specifically, an analysis of the rank histograms shows that the most consistent ensemble of soil moisture is obtained by combining rainfall and model parameter perturbations. When rainfall forcing and model prognostic perturbations are added, the rank histogram shows a U-shape at the domain average scale, which corresponds to a lack of variability in the forecast ensemble. The more accurate estimation of the soil moisture prediction uncertainty obtained by combining rainfall and parameter perturbations is encouraging for the application of this approach in ensemble data assimilation systems.
Adeeb A. Rahman; Thomas J. Urbanik; Mustafa Mahamid
2002-01-01
This research develops a model using finite element to study the response of a panel made of a typical commercial corrugated fireboard due to an induced moisture function at one side of the fiberboard. The model predicts how the moisture diffusion will permeate through the fiberboard's layers (medium and liners) providing information on moisture content at any...
A 3D moisture-stress FEM analysis for time dependent problems in timber structures
NASA Astrophysics Data System (ADS)
Fortino, Stefania; Mirianon, Florian; Toratti, Tomi
2009-11-01
This paper presents a 3D moisture-stress numerical analysis for timber structures under variable humidity and load conditions. An orthotropic viscoelastic-mechanosorptive material model is specialized on the basis of previous models. Both the constitutive model and the equations needed to describe the moisture flow across the structure are implemented into user subroutines of the Abaqus finite element code and a coupled moisture-stress analysis is performed for several types of mechanical loads and moisture changes. The presented computational approach is validated by analyzing some wood tests described in the literature and comparing the computational results with the reported experimental data.
Using SMAP to identify structural errors in hydrologic models
NASA Astrophysics Data System (ADS)
Crow, W. T.; Reichle, R. H.; Chen, F.; Xia, Y.; Liu, Q.
2017-12-01
Despite decades of effort, and the development of progressively more complex models, there continues to be underlying uncertainty regarding the representation of basic water and energy balance processes in land surface models. Soil moisture occupies a central conceptual position between atmosphere forcing of the land surface and resulting surface water fluxes. As such, direct observations of soil moisture are potentially of great value for identifying and correcting fundamental structural problems affecting these models. However, to date, this potential has not yet been realized using satellite-based retrieval products. Using soil moisture data sets produced by the NASA Soil Moisture Active/Passive mission, this presentation will explore the use of the remotely-sensed soil moisture data products as a constraint to reject certain types of surface runoff parameterizations within a land surface model. Results will demonstrate that the precision of the SMAP Level 4 Surface and Root-Zone soil moisture product allows for the robust sampling of correlation statistics describing the true strength of the relationship between pre-storm soil moisture and subsequent storm-scale runoff efficiency (i.e., total storm flow divided by total rainfall both in units of depth). For a set of 16 basins located in the South-Central United States, we will use these sampled correlations to demonstrate that so-called "infiltration-excess" runoff parameterizations under predict the importance of pre-storm soil moisture for determining storm-scale runoff efficiency. To conclude, we will discuss prospects for leveraging this insight to improve short-term hydrologic forecasting and additional avenues for SMAP soil moisture products to provide process-level insight for hydrologic modelers.
NASA Astrophysics Data System (ADS)
Tabtaing, S.; Paengkanya, S.; Tanthong, P.
2017-09-01
Puffing technique is the process that can improve texture and volumetric of crisp fruit and vegetable. However, the effect of chemical composite in foods on puffing characteristics is still lack of study. Therefore, potato and apple slices were comparative study on their physical properties. Potato and apple were sliced into 2.5 mm thickness and 2.5 cm in diameter. Potato slices were treated by hot water for 2 min while apple slices were not treatment. After that, they were dried in 3 steps. First step, they were dried by hot air at temperature of 90°C until their moisture content reached to 30, 40, and 50 % dry basis. Then they were puffed by hot air at temperature of 130, 150, and 170°C for 2 min. Finally, they were dried again by hot air at temperature of 90°C until their final moisture content reached to 4% dry basis. The experimental results showed that chemical composite of food affected on physical properties of puffed product. Puffed potato had higher volume ratio than those puffed apple because potato slices contains starch. The higher starch content provided more hard texture of potato than those apples. Puffing temperature and moisture content strongly affected on the color, volume ratio, and textural properties of puffed potato slices. In addition, the high drying rate of puffed product observed at high puffing temperature and higher moisture content.
Todd F. Hutchinson; Elaine Kennedy Sutherland; Daniel A. Yaussy
2005-01-01
This study quantifies prescribed fire effects at four sites in southern Ohio, from 1995 to 2002. Each site had three treatment units: an unburned control, a unit burned 2x (1996 and 1999), and a unit burned 4 x (1996-1999). Vegetation plots were stratified by an integrated moisture index (IMI) into xeric, intermediate, and mesic classes. Prior to treatments, oak (...
NASA Astrophysics Data System (ADS)
Karssenberg, D.; Wanders, N.; de Roo, A.; de Jong, S.; Bierkens, M. F.
2013-12-01
Large-scale hydrological models are nowadays mostly calibrated using observed discharge. As a result, a large part of the hydrological system that is not directly linked to discharge, in particular the unsaturated zone, remains uncalibrated, or might be modified unrealistically. Soil moisture observations from satellites have the potential to fill this gap, as these provide the closest thing to a direct measurement of the state of the unsaturated zone, and thus are potentially useful in calibrating unsaturated zone model parameters. This is expected to result in a better identification of the complete hydrological system, potentially leading to improved forecasts of the hydrograph as well. Here we evaluate this added value of remotely sensed soil moisture in calibration of large-scale hydrological models by addressing two research questions: 1) Which parameters of hydrological models can be identified by calibration with remotely sensed soil moisture? 2) Does calibration with remotely sensed soil moisture lead to an improved calibration of hydrological models compared to approaches that calibrate only with discharge, such that this leads to improved forecasts of soil moisture content and discharge as well? To answer these questions we use a dual state and parameter ensemble Kalman filter to calibrate the hydrological model LISFLOOD for the Upper Danube area. Calibration is done with discharge and remotely sensed soil moisture acquired by AMSR-E, SMOS and ASCAT. Four scenarios are studied: no calibration (expert knowledge), calibration on discharge, calibration on remote sensing data (three satellites) and calibration on both discharge and remote sensing data. Using a split-sample approach, the model is calibrated for a period of 2 years and validated for the calibrated model parameters on a validation period of 10 years. Results show that calibration with discharge data improves the estimation of groundwater parameters (e.g., groundwater reservoir constant) and routing parameters. Calibration with only remotely sensed soil moisture results in an accurate calibration of parameters related to land surface process (e.g., the saturated conductivity of the soil), which is not possible when calibrating on discharge alone. For the upstream area up to 40000 km2, calibration on both discharge and soil moisture results in a reduction by 10-30 % in the RMSE for discharge simulations, compared to calibration on discharge alone. For discharge in the downstream area, the model performance due to assimilation of remotely sensed soil moisture is not increased or slightly decreased, most probably due to the longer relative importance of the routing and contribution of groundwater in downstream areas. When microwave soil moisture is used for calibration the RMSE of soil moisture simulations decreases from 0.072 m3m-3 to 0.062 m3m-3. The conclusion is that remotely sensed soil moisture holds potential for calibration of hydrological models leading to a better simulation of soil moisture content throughout and a better simulation of discharge in upstream areas, particularly if discharge observations are sparse.
Guynot, M E; Ramos, A J; Sanchis, V; Marín, S
2005-05-25
A hurdle technology approach has been applied to control common mold species causing spoilage of intermediate moisture bakery products (Eurotium spp., Aspergillus spp., and Penicillium corylophilum), growing on a fermented bakery product analogue (FBPA). The factors studied included a combination of different levels of weak acid preservatives (potassium sorbate, calcium propionate, and sodium benzoate; 0-0.3%), pH (4.5-5.5), and water activity (a(w); 0.80-0.90). Potassium sorbate was found to be the most effective in preventing fungal spoilage of this kind of products at the maximum concentration tested (0.3%) regardless of a(w). The same concentration of calcium propionate and sodium benzoate was effective only at low a(w) levels. On the other hand, potassium sorbate activity was slightly reduced at pH 5.5, the 0.3% being only effective at 0.80 a(w). These findings indicate that potassium sorbate may be a suitable preserving agent to inhibit deterioration of a FBPA of slightly acidic pH (near 4.5) by xerophilic fungi. Further studies have to be done in order to adjust the minimal inhibitory concentration necessary to obtain a product with the required shelf life.
NASA Astrophysics Data System (ADS)
Schwörer, C.; Fisher, D. M.; Gavin, D. G.; Temperli, C.; Bartlein, P. J.
2015-12-01
Mountain forest composition and distribution is strongly affected by temperature and is expected to shift to higher elevations with climate change. However, warmer winters will also lead to an upward shift of the snowline and a decrease in snowpack at lower and intermediate elevations. In the mountain ranges of Western North America, snowpack plays an important role in providing additional moisture during the dry summer months. It is therefore unclear if the projected climate change will lead to a rise of subalpine forest due to a longer growing season or a contraction due to drought stress. Since forest succession processes take place over decades and centuries we use LandClim, a dynamic vegetation model, to assess the impact of climate change on mountain forests on the Olympic Peninsula (Washington, USA). As a reality check we first simulate vegetation dynamics since the last Ice Age and compare model output with paleobotanical data from five natural archives that span the topographic and climatic gradients on the Peninsula. LandClim produces realistic present-day species compositions with respect to elevation and precipitation gradients. Moreover, the simulations of forest dynamics for the last 16,000 years generally agree with the pollen and macrofossil data. We then simulated mountain forests under future climate projections. As a result, our model indicates drastic changes in species composition with a replacement of mountain hemlock (Tsuga mertensiana) by more drought-resistant species such as subalpine fir (Abies lasiocarpa). On the drier, eastern side of the Peninsula, the model even suggests a lowering of timberline due to insufficient moisture availability in shallow alpine soils. Our results have important implications for ecosystem managers and stress the urgency of climate change mitigation.
Mechanisms of northeastern Brazil rainfall anomalies due to Southern Tropical Atlantic variability
NASA Astrophysics Data System (ADS)
Neelin, J.; Su, H.
2004-05-01
Observational studies have shown that the rainfall anomalies in eastern equatorial South America, including Nordeste Brazil, have a positive correlation with tropical southern Atlantic sea surface temperature (SST) anomalies. Such relationships are reproduced in model simulations with the quasi-equilibrium tropical circulation model (QTCM), which includes a simple land model. A suite of model ensemble experiments is analysed using observed SST over the tropical oceans, the tropical Atlantic and the tropical southern Atlantic (30S-0), respectively (with climatological SST in the remainder of the oceans). Warm tropical south Atlantic SST anomalies yield positive precipitation anomalies over the Nordeste and the southern edge of the Atlantic marine intertropical convergence zone (ITCZ). Mechanisms associated with moisture variations are responsible for the land precipitation changes. Increases in moisture over the Atlantic cause positive anomalies in moisture advection, spreading increased moisture downwind. Where the basic state is far from the convective stability threshold, moisture changes have little effect, but the margins of the climatological convection zone are affected. The increased moisture supply due to advection is enhanced by increases in low-level convergence required by moist static energy balances. The moisture convergence term is several times larger, but experiments altering the moisture advection confirm that the feedback is initiated by wind acting on moisture gradient. This mechanism has several features in common with the recently published "upped-ante" mechanism for El Nino impacts on this region. In that case, the moisture gradient is initiated by warm free tropospheric temperature anomalies increasing the typical value of low-level moisture required to sustain convection in the convection zones. Both mechanisms suggest the usefulness of coordinating ocean and land in situ observations of boundary layer moisture.
Using Whole-House Field Tests to Empirically Derive Moisture Buffering Model Inputs
DOE Office of Scientific and Technical Information (OSTI.GOV)
Woods, J.; Winkler, J.; Christensen, D.
2014-08-01
Building energy simulations can be used to predict a building's interior conditions, along with the energy use associated with keeping these conditions comfortable. These models simulate the loads on the building (e.g., internal gains, envelope heat transfer), determine the operation of the space conditioning equipment, and then calculate the building's temperature and humidity throughout the year. The indoor temperature and humidity are affected not only by the loads and the space conditioning equipment, but also by the capacitance of the building materials, which buffer changes in temperature and humidity. This research developed an empirical method to extract whole-house model inputsmore » for use with a more accurate moisture capacitance model (the effective moisture penetration depth model). The experimental approach was to subject the materials in the house to a square-wave relative humidity profile, measure all of the moisture transfer terms (e.g., infiltration, air conditioner condensate) and calculate the only unmeasured term: the moisture absorption into the materials. After validating the method with laboratory measurements, we performed the tests in a field house. A least-squares fit of an analytical solution to the measured moisture absorption curves was used to determine the three independent model parameters representing the moisture buffering potential of this house and its furnishings. Follow on tests with realistic latent and sensible loads showed good agreement with the derived parameters, especially compared to the commonly-used effective capacitance approach. These results show that the EMPD model, once the inputs are known, is an accurate moisture buffering model.« less
NASA Technical Reports Server (NTRS)
Li, Bailing; Toll, David; Zhan, Xiwu; Cosgrove, Brian
2011-01-01
Model simulated soil moisture fields are often biased due to errors in input parameters and deficiencies in model physics. Satellite derived soil moisture estimates, if retrieved appropriately, represent the spatial mean of soil moisture in a footprint area, and can be used to reduce model bias (at locations near the surface) through data assimilation techniques. While assimilating the retrievals can reduce model bias, it can also destroy the mass balance enforced by the model governing equation because water is removed from or added to the soil by the assimilation algorithm. In addition, studies have shown that assimilation of surface observations can adversely impact soil moisture estimates in the lower soil layers due to imperfect model physics, even though the bias near the surface is decreased. In this study, an ensemble Kalman filter (EnKF) with a mass conservation updating scheme was developed to assimilate the actual value of Advanced Microwave Scanning Radiometer (AMSR-E) soil moisture retrievals to improve the mean of simulated soil moisture fields by the Noah land surface model. Assimilation results using the conventional and the mass conservation updating scheme in the Little Washita watershed of Oklahoma showed that, while both updating schemes reduced the bias in the shallow root zone, the mass conservation scheme provided better estimates in the deeper profile. The mass conservation scheme also yielded physically consistent estimates of fluxes and maintained the water budget. Impacts of model physics on the assimilation results are discussed.
NASA Technical Reports Server (NTRS)
Arya, L. M.; Richter, J. C.; Davidson, S. A. (Principal Investigator)
1982-01-01
Soil moisture characteristics predicted by the Arya-Paris model were compared with the laboratory measured data for 181 New Jersey soil horizons. For a number of soil horizons, the predicted and the measured moisture characteristic curves are almost coincident; for a large number of other horizons, despite some disparity, their shapes are strikingly similar. Uncertainties in the model input and laboratory measurement of the moisture characteristic are indicated, and recommendations for additional experimentation and testing are made.
Assimilating soil moisture into an Earth System Model
NASA Astrophysics Data System (ADS)
Stacke, Tobias; Hagemann, Stefan
2017-04-01
Several modelling studies reported potential impacts of soil moisture anomalies on regional climate. In particular for short prediction periods, perturbations of the soil moisture state may result in significant alteration of surface temperature in the following season. However, it is not clear yet whether or not soil moisture anomalies affect climate also on larger temporal and spatial scales. In an earlier study, we showed that soil moisture anomalies can persist for several seasons in the deeper soil layers of a land surface model. Additionally, those anomalies can influence root zone moisture, in particular during explicitly dry or wet periods. Thus, one prerequisite for predictability, namely the existence of long term memory, is evident for simulated soil moisture and might be exploited to improve climate predictions. The second prerequisite is the sensitivity of the climate system to soil moisture. In order to investigate this sensitivity for decadal simulations, we implemented a soil moisture assimilation scheme into the Max-Planck Institute for Meteorology's Earth System Model (MPI-ESM). The assimilation scheme is based on a simple nudging algorithm and updates the surface soil moisture state once per day. In our experiments, the MPI-ESM is used which includes model components for the interactive simulation of atmosphere, land and ocean. Artificial assimilation data is created from a control simulation to nudge the MPI-ESM towards predominantly dry and wet states. First analyses are focused on the impact of the assimilation on land surface variables and reveal distinct differences in the long-term mean values between wet and dry state simulations. Precipitation, evapotranspiration and runoff are larger in the wet state compared to the dry state, resulting in an increased moisture transport from the land to atmosphere and ocean. Consequently, surface temperatures are lower in the wet state simulations by more than one Kelvin. In terms of spatial pattern, the largest differences between both simulations are seen for continental areas, while regions with a maritime climate are least sensitive to soil moisture assimilation.
NASA Astrophysics Data System (ADS)
Fahim, A. M.; Shen, R.; Yue, Z.; Di, W.; Mushtaq Shah, S.
2015-12-01
Moisture in the upper most layer of soil column from 14 different models under Coupled Model Intercomparison Project Phase-5 (CMIP5) project were analyzed for four seasons of the year. Aim of this study was to explore variability in soil moisture over south Asia using multi model ensemble and relationship between summer rainfall and soil moisture for spring and summer season. GLDAS (Global Land Data Assimilation System) dataset set was used for comparing CMIP5 ensemble mean soil moisture in different season. Ensemble mean represents soil moisture well in accordance with the geographical features; prominent arid regions are indicated profoundly. Empirical Orthogonal Function (EOF) analysis was applied to study the variability. First component of EOF explains 17%, 16%, 11% and 11% variability for spring, summer, autumn and winter season respectively. Analysis reveal increasing trend in soil moisture over most parts of Afghanistan, Central and north western parts of Pakistan, northern India and eastern to south eastern parts of China, in spring season. During summer, south western part of India exhibits highest negative trend while rest of the study area show minute trend (increasing or decreasing). In autumn, south west of India is under highest negative loadings. During winter season, north western parts of study area show decreasing trend. Summer rainfall has very week (negative or positive) spatial correlation, with spring soil moisture, while possess higher correlation with summer soil moisture. Our studies have significant contribution to understand complex nature of land - atmosphere interactions, as soil moisture prediction plays an important role in the cycle of sink and source of many air pollutants. Next level of research should be on filling the gaps between accurately measuring the soil moisture using satellite remote sensing and land surface modelling. Impact of soil moisture in tracking down different types of pollutant will also be studied.
NASA Astrophysics Data System (ADS)
Willgoose, G. R.; Chen, M.; Cohen, S.; Saco, P. M.; Hancock, G. R.
2013-12-01
In humid areas it is generally considered that soil moisture scales spatially according to the wetness index of the landscape. This scaling arises from lateral flow downslope of ground water within the soil zone. However, in semi-arid and drier regions, this lateral flow is small and fluxes are dominated by vertical flows driven by infiltration and evapotranspiration. Thus, in the absence of runon processes, soil moisture at a location is more driven by local factors such as soil and vegetation properties at that location rather than upstream processes draining to that point. The 'apparent' spatial randomness of soil and vegetation properties generally suggests that soil moisture for semi-arid regions is spatially random. In this presentation a new analysis of neutron probe data during summer from the Tarrawarra site near Melbourne, Australia shows persistent spatial organisation of soil moisture over several years. This suggests a link between permanent features of the catchment (e.g. soil properties) and soil moisture distribution, even though the spatial pattern of soil moisture during the 4 summers monitored appears spatially random. This and other data establishes a prima facie case that soil variations drive spatial variation in soil moisture. Accordingly, we used a previously published spatial scaling relationship for soil properties derived using the mARM pedogenesis model to simulate the spatial variation of soil grading. This soil grading distribution was used in the Rosetta pedotransfer model to derive a spatial distribution of soil functional properties (e.g. saturated hydraulic conductivity, porosity). These functional properties were then input into the HYDRUS-1D soil moisture model and soil moisture simulated for 3 years at daily resolution. The HYDRUS model used had previously been calibrated to field observed soil moisture data at our SASMAS field site. The scaling behaviour of soil moisture derived from this modelling will be discussed and compared with observed data from our SASMAS field sites.
NASA Astrophysics Data System (ADS)
Sanchez-Mejia, Z. M.; Papuga, S. A.
2013-12-01
In semiarid regions, where water resources are limited and precipitation dynamics are changing, understanding land surface-atmosphere interactions that regulate the coupled soil moisture-precipitation system is key for resource management and planning. We present a modeling approach to study soil moisture and albedo controls on planetary boundary layer height (PBLh). We used data from the Santa Rita Creosote Ameriflux site and Tucson Airport atmospheric sounding to generate empirical relationships between soil moisture, albedo and PBLh. We developed empirical relationships and show that at least 50% of the variation in PBLh can be explained by soil moisture and albedo. Then, we used a stochastically driven two-layer bucket model of soil moisture dynamics and our empirical relationships to model PBLh. We explored soil moisture dynamics under three different mean annual precipitation regimes: current, increase, and decrease, to evaluate at the influence on soil moisture on land surface-atmospheric processes. While our precipitation regimes are simple, they represent future precipitation regimes that can influence the two soil layers in our conceptual framework. For instance, an increase in annual precipitation, could impact on deep soil moisture and atmospheric processes if precipitation events remain intense. We observed that the response of soil moisture, albedo, and the PBLh will depend not only on changes in annual precipitation, but also on the frequency and intensity of this change. We argue that because albedo and soil moisture data are readily available at multiple temporal and spatial scales, developing empirical relationships that can be used in land surface - atmosphere applications are of great value.
Moisture origin and transport processes in Colombia, northern South America
NASA Astrophysics Data System (ADS)
Hoyos, I.; Dominguez, F.; Cañón-Barriga, J.; Martínez, J. A.; Nieto, R.; Gimeno, L.; Dirmeyer, P. A.
2018-02-01
We assess the spatial structure of moisture flux divergence, regional moisture sources and transport processes over Colombia, in northern South America. Using three independent methods the dynamic recycling model (DRM), FLEXPART and the Quasi-isentropic back-trajectory (QIBT) models we quantify the moisture sources that contribute to precipitation over the region. We find that moisture from the Atlantic Ocean and terrestrial recycling are the most important sources of moisture for Colombia, highlighting the importance of the Orinoco and Amazon basins as regional providers of atmospheric moisture. The results show the influence of long-range cross-equatorial flow from the Atlantic Ocean into the target region and the role of the study area as a passage of moisture into South America. We also describe the seasonal moisture transport mechanisms of the well-known low-level westerly and Caribbean jets that originate in the Pacific Ocean and Caribbean Sea, respectively. We find that these dynamical systems play an important role in the convergence of moisture over western Colombia.
Assimilation of SMOS (and SMAP) Retrieved Soil Moisture into the Land Information System
NASA Technical Reports Server (NTRS)
Blankenship, Clay; Zavodsky, Bradley; Case, Jonathan; Stano, Geoffrey
2016-01-01
Goal: Accurate, high-resolution (approx.3 km) soil moisture in near-real time. Situational awareness (drought assessment, flood and fire threat). Local modeling applications (to improve sfc-PBL exchanges) Method: Assimilate satellite soil moisture retrievals into a land surface model. Combines high-resolution geophysical model data with latest satellite observations.
Guynot, M Elena; Marín, Sonia; Sanchis, Vicente; Ramos, Antonio J
2005-05-25
Mould growth was modelled on fermented bakery product analogues (FBPA) of two different pH (4.5 and 5.5), different water activity (a(w)) levels (0.80-0.90) and potassium sorbate concentrations (0-0.3%) by using seven moulds commonly causing spoilage of bakery products (Eurotium spp., Aspergillus spp. and Penicillium corylophilum). For the description of fungal growth (growth rates) as a function of a(w), potassium sorbate concentration and pH, 10-terms polynomial models were developed. Modelling enables prediction of spoilage during storage as a function of the factors affecting fungal growth. At pH 4.5 the concentration of potassium sorbate could be reduced to some extent only at low levels of a(w), whereas at pH 5.5 fungal growth was observed even by adding 0.3% of potassium sorbate. However, this preservative could be a valuable alternative as antifungal in such bakery product, of slightly acidic pH, if a long shelf life has not to be achieved.
Nolet, Corjan; Poortinga, Ate; Roosjen, Peter; Bartholomeus, Harm; Ruessink, Gerben
2014-01-01
Surface moisture is an important supply limiting factor for aeolian sand transport, which is the primary driver of coastal dune development. As such, it is critical to account for the control of surface moisture on available sand for dune building. Optical remote sensing has the potential to measure surface moisture at a high spatio-temporal resolution. It is based on the principle that wet sand appears darker than dry sand: it is less reflective. The goals of this study are (1) to measure and model reflectance under controlled laboratory conditions as function of wavelength () and surface moisture () over the optical domain of 350–2500 nm, and (2) to explore the implications of our laboratory findings for accurately mapping the distribution of surface moisture under natural conditions. A laboratory spectroscopy experiment was conducted to measure spectral reflectance (1 nm interval) under different surface moisture conditions using beach sand. A non-linear increase of reflectance upon drying was observed over the full range of wavelengths. Two models were developed and tested. The first model is grounded in optics and describes the proportional contribution of scattering and absorption of light by pore water in an unsaturated sand matrix. The second model is grounded in soil physics and links the hydraulic behaviour of pore water in an unsaturated sand matrix to its optical properties. The optical model performed well for volumetric moisture content 24% ( 0.97), but underestimated reflectance for between 24–30% ( 0.92), most notable around the 1940 nm water absorption peak. The soil-physical model performed very well ( 0.99) but is limited to 4% 24%. Results from a field experiment show that a short-wave infrared terrestrial laser scanner ( = 1550 nm) can accurately relate surface moisture to reflectance (standard error 2.6%), demonstrating its potential to derive spatially extensive surface moisture maps of a natural coastal beach. PMID:25383709
An Object-Oriented Python Implementation of an Intermediate-Level Atmospheric Model
NASA Astrophysics Data System (ADS)
Lin, J. W.
2008-12-01
The Neelin-Zeng Quasi-equilibrium Tropical Circulation Model (QTCM1) is a Fortran-based intermediate-level atmospheric model that includes simplified treatments of several physical processes, including a GCM-like convective scheme and a land-surface scheme with representations of different surface types, evaporation, and soil moisture. This model has been used in studies of the Madden-Julian oscillation, ENSO, and vegetation-atmosphere interaction effects on climate. Through the assumption of convective quasi-equilibrium in the troposphere, the QTCM1 is able to include full nonlinearity, resolve baroclinic disturbances, and generate a reasonable climatology, all at low computational cost. One year of simulation on a PC at 5.625 × 3.75 degree longitude-latitude resolution takes under three minutes of wall-clock time. The Python package qtcm implements the QTCM1 in a mixed-language environment that retains the speed of compiled Fortran while providing the benefits of Python's object-oriented framework and robust suite of utilities and datatypes. We describe key programming constructs used to create this modeling environment: the decomposition of model runs into Python objects, providing methods so visualization tools are attached to model runs, and the use of Python's mutable datatypes (lists and dictionaries) to implement the "run list" entity, which enables total runtime control of subroutine execution order and content. The result is an interactive modeling environment where the traditional sequence of "hypothesis → modeling → visualization and analysis" is opened up and made nonlinear and flexible. In this environment, science tasks such as parameter-space exploration and testing alternative parameterizations can be easily automated, without the need for multiple versions of the model code interacting with a bevy of makefiles and shell scripts. The environment also simplifies interfacing of the atmospheric model to other models (e.g., hydrologic models, statistical models) and analysis tools. The tools developed for this package can be adapted to create similar environments for hydrologic models.
J. D. Carlson; Larry S. Bradshaw; Ralph M. Nelson; Randall R Bensch; Rafal Jabrzemski
2007-01-01
The application of a next-generation dead-fuel moisture model, the 'Nelson model', to four timelag fuel classes using an extensive 21-month dataset of dead-fuel moisture observations is described. Developed by Ralph Nelson in the 1990s, the Nelson model is a dead-fuel moisture model designed to take advantage of frequent automated weather observations....
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.
NASA Astrophysics Data System (ADS)
Wu, Mousong; Sholze, Marko
2017-04-01
We investigated the importance of soil moisture data on assimilation of a terrestrial biosphere model (BETHY) for a long time period from 2010 to 2015. Totally, 101 parameters related to carbon turnover, soil respiration, as well as soil texture were selected for optimization within a carbon cycle data assimilation system (CCDAS). Soil moisture data from Soil Moisture and Ocean Salinity (SMOS) product was derived for 10 sites representing different plant function types (PFTs) as well as different climate zones. Uncertainty of SMOS soil moisture data was also estimated using triple collocation analysis (TCA) method by comparing with ASCAT dataset and BETHY forward simulation results. Assimilation of soil moisture to the system improved soil moisture as well as net primary productivity(NPP) and net ecosystem productivity (NEP) when compared with soil moisture derived from in-situ measurements and fluxnet datasets. Parameter uncertainties were largely reduced relatively to prior values. Using SMOS soil moisture data for assimilation of a terrestrial biosphere model proved to be an efficient approach in reducing uncertainty in ecosystem fluxes simulation. It could be further used in regional an global assimilation work to constrain carbon dioxide concentration simulation by combining with other sources of measurements.
NASA Astrophysics Data System (ADS)
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.
NASA Astrophysics Data System (ADS)
Srivastava, Prashant K., ,, Dr.; O'Neill, Peggy, ,, Dr.
2014-05-01
Soil moisture is an important element for weather and climate prediction, hydrological sciences, and applications. Hence, measurements of this hydrologic variable are required to improve our understanding of hydrological processes, ecosystem functions, and the linkages between the Earth's water, energy, and carbon cycles (Srivastava et al. 2013). The retrieval of soil moisture depends not only on parameterizations in the retrieval algorithm but also on the soil dielectric mixing models used (Behari 2005). Although a number of soil dielectric mixing models have been developed, testing these models for soil moisture retrieval has still not been fully explored, especially with SMAP-like simulators. The main objective of this work focuses on testing different dielectric models for soil moisture retrieval using the Combined Radar/Radiometer (ComRAD) ground-based L-band simulator developed jointly by NASA/GSFC and George Washington University (O'Neill et al., 2006). The ComRAD system was deployed during a field experiment in 2012 in order to provide long active/passive measurements of two crops under controlled conditions during an entire growing season. L-band passive data were acquired at a look angle of 40 degree from nadir at both horizontal & vertical polarization. Currently, there are many dielectric models available for soil moisture retrieval; however, four dielectric models (Mironov, Dobson, Wang & Schmugge and Hallikainen) were tested here and found to be promising for soil moisture retrieval (some with higher performances). All the above-mentioned dielectric models were integrated with Single Channel Algorithms using H (SCA-H) and V (SCA-V) polarizations for the soil moisture retrievals. All the ground-based observations were collected from test site-United States Department of Agriculture (USDA) OPE3, located a few miles away from NASA GSFC. Ground truth data were collected using a theta probe and in situ sensors which were then used for validation. Analysis indicated a higher performance in terms of soil moisture retrieval accuracy for the Mironov dielectric model (RMSE of 0.035 m3/m3), followed by Dobson, Wang & Schmugge, and Hallikainen. This analysis indicates that Mironov dielectric model is promising for passive-only microwave soil moisture retrieval and could be a useful choice for SMAP satellite soil moisture retrieval. Keywords: Dielectric models; Single Channel Algorithm, Combined Radar/Radiometer, Soil moisture; L band References: Behari, J. (2005). Dielectric Behavior of Soil (pp. 22-40). Springer Netherlands O'Neill, P. E., Lang, R. H., Kurum, M., Utku, C., & Carver, K. R. (2006), Multi-Sensor Microwave Soil Moisture Remote Sensing: NASA's Combined Radar/Radiometer (ComRAD) System. In IEEE MicroRad, 2006 (pp. 50-54). IEEE. Srivastava, P. K., Han, D., Rico Ramirez, M. A., & Islam, T. (2013), Appraisal of SMOS soil moisture at a catchment scale in a temperate maritime climate. Journal of Hydrology, 498, 292-304. USDA OPE3 web site at http://www.ars.usda.gov/Research/.
A simple nudging scheme to assimilate ASCAT soil moisture data in the WRF model
NASA Astrophysics Data System (ADS)
Capecchi, V.; Gozzini, B.
2012-04-01
The present work shows results obtained in a numerical experiment using the WRF (Weather and Research Forecasting, www.wrf-model.org) model. A control run where soil moisture is constrained by GFS global analysis is compared with a test run where soil moisture analysis is obtained via a simple nudging scheme using ASCAT data. The basic idea of the assimilation scheme is to "nudge" the first level (0-10 cm below ground in NOAH model) of volumetric soil moisture of the first-guess (say θ(b,1) derived from global model) towards the ASCAT derived value (say ^θ A). The soil moisture analysis θ(a,1) is given by: { θ + K (^θA - θ ) l = 1 θ(a,1) = θ(b,l) (b,l) l > 1 (b,l) (1) where l is the model soil level. K is a constant scalar value that is user specified and in this study it is equal to 0.2 (same value as in similar studies). Soil moisture is critical for estimating latent and sensible heat fluxes as well as boundary layer structure. This parameter is, however, poorly assimilated in current global and regional numerical models since no extensive soil moisture observation network exists. Remote sensing technologies offer a synoptic view of the dynamics and spatial distribution of soil moisture with a frequent temporal coverage and with a horizontal resolution similar to mesoscale NWP model. Several studies have shown that measurements of normalized backscatter (surface soil wetness) from the Advanced Scatterometer (ASCAT) operating at microwave frequencies and boarded on the meteorological operational (Metop) satellite, offer quality information about surface soil moisture. Recently several studies deal with the implementation of simple assimilation procedures (nudging, Extended Kalman Filter, etc...) to integrate ASCAT data in NWP models. They found improvements in screen temperature predictions, particularly in areas such as North-America and in the Tropics, where it is strong the land-atmosphere coupling. The ECMWF (Newsletter No. 127) is currently implementing and testing an EKF for combining conventional observations and remote sensed soil moisture data in order to produce a more accurate analysis. In the present work verification skills (RMSE, BIAS, correlation) of both control and test run are presented using observed data collected by International Soil Moisture Network. Moreover improvements in temperature predictions are evaluated.
NASA Astrophysics Data System (ADS)
Ajami, H.; Sharma, A.
2016-12-01
A computationally efficient, semi-distributed hydrologic modeling framework is developed to simulate water balance at a catchment scale. The Soil Moisture and Runoff simulation Toolkit (SMART) is based upon the delineation of contiguous and topologically connected Hydrologic Response Units (HRUs). In SMART, HRUs are delineated using thresholds obtained from topographic and geomorphic analysis of a catchment, and simulation elements are distributed cross sections or equivalent cross sections (ECS) delineated in first order sub-basins. ECSs are formulated by aggregating topographic and physiographic properties of the part or entire first order sub-basins to further reduce computational time in SMART. Previous investigations using SMART have shown that temporal dynamics of soil moisture are well captured at a HRU level using the ECS delineation approach. However, spatial variability of soil moisture within a given HRU is ignored. Here, we examined a number of disaggregation schemes for soil moisture distribution in each HRU. The disaggregation schemes are either based on topographic based indices or a covariance matrix obtained from distributed soil moisture simulations. To assess the performance of the disaggregation schemes, soil moisture simulations from an integrated land surface-groundwater model, ParFlow.CLM in Baldry sub-catchment, Australia are used. ParFlow is a variably saturated sub-surface flow model that is coupled to the Common Land Model (CLM). Our results illustrate that the statistical disaggregation scheme performs better than the methods based on topographic data in approximating soil moisture distribution at a 60m scale. Moreover, the statistical disaggregation scheme maintains temporal correlation of simulated daily soil moisture while preserves the mean sub-basin soil moisture. Future work is focused on assessing the performance of this scheme in catchments with various topographic and climate settings.
Evaluation of a microwave resonator for predicting grain moisture independent of bulk density
USDA-ARS?s Scientific Manuscript database
This work evaluated the ability of a planar whispering mode resonator to predict moisture considering moisture and densities expected in an on-harvester application. A calibration model was developed to accurately predict moisture over the moisture, density and temperature ranges evaluated. This mod...
Calculating moisture content for 1000-hour timelag fuels in western Washington and western Oregon.
Roger D. Ottmar; David V. Sandberg
1985-01-01
A predictive model is presented to calculate moisture content of 1000-hour timelag fuels in Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) and western hemlock (Tsuga heterophylla (Raf.) Sarg.) logging slash in western Washington and western Oregon. The model is a modification of the 1000-hour fuel moisture model of the...
NASA Technical Reports Server (NTRS)
Blankenship, Clay B.; Crosson, William L.; Case, Jonathan L.; Hale, Robert
2010-01-01
Improve simulations of soil moisture/temperature, and consequently boundary layer states and processes, by assimilating AMSR-E soil moisture estimates into a coupled land surface-mesoscale model Provide a new land surface model as an option in the Land Information System (LIS)
NASA Technical Reports Server (NTRS)
Blankenship, Clay; Case, Jonathan L.; Zavodsky, Bradley
2015-01-01
Land surface models are important components of numerical weather prediction (NWP) models, partitioning incoming energy into latent and sensitive heat fluxes that affect boundary layer growth and destabilization. During warm-season months, diurnal heating and convective initiation depend strongly on evapotranspiration and available boundary layer moisture, which are substantially affected by soil moisture content. Therefore, to properly simulate warm-season processes in NWP models, an accurate initialization of the land surface state is important for accurately depicting the exchange of heat and moisture between the surface and boundary layer. In this study, soil moisture retrievals from the Soil Moisture and Ocean Salinity (SMOS) satellite radiometer are assimilated into the Noah Land Surface Model via an Ensemble Kalman Filter embedded within the NASA Land Information System (LIS) software framework. The output from LIS-Noah is subsequently used to initialize runs of the Weather Research and Forecasting (WRF) NWP model. The impact of assimilating SMOS retrievals is assessed by initializing the WRF model with LIS-Noah output obtained with and without SMOS data assimilation. The southeastern United States is used as the domain for a preliminary case study. During the summer months, there is extensive irrigation in the lower Mississippi Valley for rice and other crops. The irrigation is not represented in the meteorological forcing used to drive the LIS-Noah integration, but the irrigated areas show up clearly in the SMOS soil moisture retrievals, resulting in a case with a large difference in initial soil moisture conditions. The impact of SMOS data assimilation on both Noah soil moisture fields and on short-term (0-48 hour) WRF weather forecasts will be presented.
A model of the CO2 exchanges between biosphere and atmosphere in the tundra
NASA Technical Reports Server (NTRS)
Labgaa, Rachid R.; Gautier, Catherine
1992-01-01
A physical model of the soil thermal regime in a permafrost terrain has been developed and validated with soil temperature measurements at Barrow, Alaska. The model calculates daily soil temperatures as a function of depth and average moisture contents of the organic and mineral layers using a set of five climatic variables, i.e., air temperature, precipitation, cloudiness, wind speed, and relative humidity. The model is not only designed to study the impact of climate change on the soil temperature and moisture regime, but also to provide the input to a decomposition and net primary production model. In this context, it is well known that CO2 exchanges between the terrestrial biosphere and the atmosphere are driven by soil temperature through decomposition of soil organic matter and root respiration. However, in tundra ecosystems, net CO2 exchange is extremely sensitive to soil moisture content; therefore it is necessary to predict variations in soil moisture in order to assess the impact of climate change on carbon fluxes. To this end, the present model includes the representation of the soil moisture response to changes in climatic conditions. The results presented in the foregoing demonstrate that large errors in soil temperature and permafrost depth estimates arise from neglecting the dependence of the soil thermal regime on soil moisture contents. Permafrost terrain is an example of a situation where soil moisture and temperature are particularly interrelated: drainage conditions improve when the depth of the permafrost increases; a decrease in soil moisture content leads to a decrease in the latent heat required for the phase transition so that the heat penetrates faster and deeper, and the maximum depth of thaw increases; and as excepted, soil thermal coefficients increase with moisture.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Woods, Jason; Winkler, Jon
Moisture buffering of building materials has a significant impact on the building's indoor humidity, and building energy simulations need to model this buffering to accurately predict the humidity. Researchers requiring a simple moisture-buffering approach typically rely on the effective-capacitance model, which has been shown to be a poor predictor of actual indoor humidity. This paper describes an alternative two-layer effective moisture penetration depth (EMPD) model and its inputs. While this model has been used previously, there is a need to understand the sensitivity of this model to uncertain inputs. In this paper, we use the moisture-adsorbent materials exposed to themore » interior air: drywall, wood, and carpet. We use a global sensitivity analysis to determine which inputs are most influential and how the model's prediction capability degrades due to uncertainty in these inputs. We then compare the model's humidity prediction with measured data from five houses, which shows that this model, and a set of simple inputs, can give reasonable prediction of the indoor humidity.« less
Woods, Jason; Winkler, Jon
2018-01-31
Moisture buffering of building materials has a significant impact on the building's indoor humidity, and building energy simulations need to model this buffering to accurately predict the humidity. Researchers requiring a simple moisture-buffering approach typically rely on the effective-capacitance model, which has been shown to be a poor predictor of actual indoor humidity. This paper describes an alternative two-layer effective moisture penetration depth (EMPD) model and its inputs. While this model has been used previously, there is a need to understand the sensitivity of this model to uncertain inputs. In this paper, we use the moisture-adsorbent materials exposed to themore » interior air: drywall, wood, and carpet. We use a global sensitivity analysis to determine which inputs are most influential and how the model's prediction capability degrades due to uncertainty in these inputs. We then compare the model's humidity prediction with measured data from five houses, which shows that this model, and a set of simple inputs, can give reasonable prediction of the indoor humidity.« less
Adeeb A. Rahman; Thomas J. Urbanik; Mustafa Mahamid
2006-01-01
This paper presents a model using finite element method to study the response of a typical commercial corrugated fiberboard due to an induced moisture function at one side of the fiberboard. The model predicts how the moisture diffusion will permeate through the fiberboardâs layers(medium and liners) providing information on moisture content at any given point...
NASA Astrophysics Data System (ADS)
Hu, Z.; Xu, L.; Yu, B.
2018-04-01
A empirical model is established to analyse the daily retrieval of soil moisture from passive microwave remote sensing using convolutional neural networks (CNN). Soil moisture plays an important role in the water cycle. However, with the rapidly increasing of the acquiring technology for remotely sensed data, it's a hard task for remote sensing practitioners to find a fast and convenient model to deal with the massive data. In this paper, the AMSR-E brightness temperatures are used to train CNN for the prediction of the European centre for medium-range weather forecasts (ECMWF) model. Compared with the classical inversion methods, the deep learning-based method is more suitable for global soil moisture retrieval. It is very well supported by graphics processing unit (GPU) acceleration, which can meet the demand of massive data inversion. Once the model trained, a global soil moisture map can be predicted in less than 10 seconds. What's more, the method of soil moisture retrieval based on deep learning can learn the complex texture features from the big remote sensing data. In this experiment, the results demonstrates that the CNN deployed to retrieve global soil moisture can achieve a better performance than the support vector regression (SVR) for soil moisture retrieval.
Assimilation of ASCAT near-surface soil moisture into the SIM hydrological model over France
NASA Astrophysics Data System (ADS)
Draper, C.; Mahfouf, J.-F.; Calvet, J.-C.; Martin, E.; Wagner, W.
2011-12-01
This study examines whether the assimilation of remotely sensed near-surface soil moisture observations might benefit an operational hydrological model, specifically Météo-France's SAFRAN-ISBA-MODCOU (SIM) model. Soil moisture data derived from ASCAT backscatter observations are assimilated into SIM using a Simplified Extended Kalman Filter (SEKF) over 3.5 years. The benefit of the assimilation is tested by comparison to a delayed cut-off version of SIM, in which the land surface is forced with more accurate atmospheric analyses, due to the availability of additional atmospheric observations after the near-real time data cut-off. However, comparing the near-real time and delayed cut-off SIM models revealed that the main difference between them is a dry bias in the near-real time precipitation forcing, which resulted in a dry bias in the root-zone soil moisture and associated surface moisture flux forecasts. While assimilating the ASCAT data did reduce the root-zone soil moisture dry bias (by nearly 50%), this was more likely due to a bias within the SEKF, than due to the assimilation having accurately responded to the precipitation errors. Several improvements to the assimilation are identified to address this, and a bias-aware strategy is suggested for explicitly correcting the model bias. However, in this experiment the moisture added by the SEKF was quickly lost from the model surface due to the enhanced surface fluxes (particularly drainage) induced by the wetter soil moisture states. Consequently, by the end of each winter, during which frozen conditions prevent the ASCAT data from being assimilated, the model land surface had returned to its original (dry-biased) climate. This highlights that it would be more effective to address the precipitation bias directly, than to correct it by constraining the model soil moisture through data assimilation.
NASA Astrophysics Data System (ADS)
Nasta, Paolo; Penna, Daniele; Brocca, Luca; Zuecco, Giulia; Romano, Nunzio
2018-02-01
Indirect measurements of field-scale (hectometer grid-size) spatial-average near-surface soil moisture are becoming increasingly available by exploiting new-generation ground-based and satellite sensors. Nonetheless, modeling applications for water resources management require knowledge of plot-scale (1-5 m grid-size) soil moisture by using measurements through spatially-distributed sensor network systems. Since efforts to fulfill such requirements are not always possible due to time and budget constraints, alternative approaches are desirable. In this study, we explore the feasibility of determining spatial-average soil moisture and soil moisture patterns given the knowledge of long-term records of climate forcing data and topographic attributes. A downscaling approach is proposed that couples two different models: the Eco-Hydrological Bucket and Equilibrium Moisture from Topography. This approach helps identify the relative importance of two compound topographic indexes in explaining the spatial variation of soil moisture patterns, indicating valley- and hillslope-dependence controlled by lateral flow and radiative processes, respectively. The integrated model also detects temporal instability if the dominant type of topographic dependence changes with spatial-average soil moisture. Model application was carried out at three sites in different parts of Italy, each characterized by different environmental conditions. Prior calibration was performed by using sparse and sporadic soil moisture values measured by portable time domain reflectometry devices. Cross-site comparisons offer different interpretations in the explained spatial variation of soil moisture patterns, with time-invariant valley-dependence (site in northern Italy) and hillslope-dependence (site in southern Italy). The sources of soil moisture spatial variation at the site in central Italy are time-variant within the year and the seasonal change of topographic dependence can be conveniently correlated to a climate indicator such as the aridity index.
Large-area Soil Moisture Surveys Using a Cosmic-ray Rover: Approaches and Results from Australia
NASA Astrophysics Data System (ADS)
Hawdon, A. A.; McJannet, D. L.; Renzullo, L. J.; Baker, B.; Searle, R.
2017-12-01
Recent improvements in satellite instrumentation has increased the resolution and frequency of soil moisture observations, and this in turn has supported the development of higher resolution land surface process models. Calibration and validation of these products is restricted by the mismatch of scales between remotely sensed and contemporary ground based observations. Although the cosmic ray neutron soil moisture probe can provide estimates soil moisture at a scale useful for the calibration and validation purposes, it is spatially limited to a single, fixed location. This scaling issue has been addressed with the development of mobile soil moisture monitoring systems that utilizes the cosmic ray neutron method, typically referred to as a `rover'. This manuscript describes a project designed to develop approaches for undertaking rover surveys to produce soil moisture estimates at scales comparable to satellite observations and land surface process models. A custom designed, trailer-mounted rover was used to conduct repeat surveys at two scales in the Mallee region of Victoria, Australia. A broad scale survey was conducted at 36 x 36 km covering an area of a standard SMAP pixel and an intensive scale survey was conducted over a 10 x 10 km portion of the broad scale survey, which is at a scale equivalent to that used for national water balance modelling. We will describe the design of the rover, the methods used for converting neutron counts into soil moisture and discuss factors controlling soil moisture variability. We found that the intensive scale rover surveys produced reliable soil moisture estimates at 1 km resolution and the broad scale at 9 km resolution. We conclude that these products are well suited for future analysis of satellite soil moisture retrievals and finer scale soil moisture models.
NASA Astrophysics Data System (ADS)
Huang, Chunlin; Chen, Weijin; Wang, Weizhen; Gu, Juan
2017-04-01
Uncertainties in model parameters can easily cause systematic differences between model states and observations from ground or satellites, which significantly affect the accuracy of soil moisture estimation in data assimilation systems. In this paper, a novel soil moisture assimilation scheme is developed to simultaneously assimilate AMSR-E brightness temperature (TB) and MODIS Land Surface Temperature (LST), which can correct model bias by simultaneously updating model states and parameters with dual ensemble Kalman filter (DEnKS). The Common Land Model (CoLM) and a Q-h Radiative Transfer Model (RTM) are adopted as model operator and observation operator, respectively. The assimilation experiment is conducted in Naqu, Tibet Plateau, from May 31 to September 27, 2011. Compared with in-situ measurements, the accuracy of soil moisture estimation is tremendously improved in terms of a variety of scales. The updated soil temperature by assimilating MODIS LST as input of RTM can reduce the differences between the simulated and observed brightness temperatures to a certain degree, which helps to improve the estimation of soil moisture and model parameters. The updated parameters show large discrepancy with the default ones and the former effectively reduces the states bias of CoLM. Results demonstrate the potential of assimilating both microwave TB and MODIS LST to improve the estimation of soil moisture and related parameters. Furthermore, this study also indicates that the developed scheme is an effective soil moisture downscaling approach for coarse-scale microwave TB.
[Bare Soil Moisture Inversion Model Based on Visible-Shortwave Infrared Reflectance].
Zheng, Xiao-po; Sun, Yue-jun; Qin, Qi-ming; Ren, Hua-zhong; Gao, Zhong-ling; Wu, Ling; Meng, Qing-ye; Wang, Jin-liang; Wang, Jian-hua
2015-08-01
Soil is the loose solum of land surface that can support plants. It consists of minerals, organics, atmosphere, moisture, microbes, et al. Among its complex compositions, soil moisture varies greatly. Therefore, the fast and accurate inversion of soil moisture by using remote sensing is very crucial. In order to reduce the influence of soil type on the retrieval of soil moisture, this paper proposed a normalized spectral slope and absorption index named NSSAI to estimate soil moisture. The modeling of the new index contains several key steps: Firstly, soil samples with different moisture level were artificially prepared, and soil reflectance spectra was consequently measured using spectroradiometer produced by ASD Company. Secondly, the moisture absorption spectral feature located at shortwave wavelengths and the spectral slope of visible wavelengths were calculated after analyzing the regular spectral feature change patterns of different soil at different moisture conditions. Then advantages of the two features at reducing soil types' effects was synthesized to build the NSSAI. Thirdly, a linear relationship between NSSAI and soil moisture was established. The result showed that NSSAI worked better (correlation coefficient is 0.93) than most of other traditional methods in soil moisture extraction. It can weaken the influences caused by soil types at different moisture levels and improve the bare soil moisture inversion accuracy.
Mass Conservation in Modeling Moisture Diffusion in Multi-Layer Carbon Composite Structures
NASA Technical Reports Server (NTRS)
Nurge, Mark A.; Youngquist, Robert C.; Starr, Stanley O.
2009-01-01
Moisture diffusion in multi-layer carbon composite structures is difficult to model using finite difference methods due to the discontinuity in concentrations between adjacent layers of differing materials. Applying a mass conserving approach at these boundaries proved to be effective at accurately predicting moisture uptake for a sample exposed to a fixed temperature and relative humidity. Details of the model developed are presented and compared with actual moisture uptake data gathered over 130 days from a graphite epoxy composite sandwich coupon with a Rohacell foam core.
New Physical Algorithms for Downscaling SMAP Soil Moisture
NASA Astrophysics Data System (ADS)
Sadeghi, M.; Ghafari, E.; Babaeian, E.; Davary, K.; Farid, A.; Jones, S. B.; Tuller, M.
2017-12-01
The NASA Soil Moisture Active Passive (SMAP) mission provides new means for estimation of surface soil moisture at the global scale. However, for many hydrological and agricultural applications the spatial SMAP resolution is too low. To address this scale issue we fused SMAP data with MODIS observations to generate soil moisture maps at 1-km spatial resolution. In course of this study we have improved several existing empirical algorithms and introduced a new physical approach for downscaling SMAP data. The universal triangle/trapezoid model was applied to relate soil moisture to optical/thermal observations such as NDVI, land surface temperature and surface reflectance. These algorithms were evaluated with in situ data measured at 5-cm depth. Our results demonstrate that downscaling SMAP soil moisture data based on physical indicators of soil moisture derived from the MODIS satellite leads to higher accuracy than that achievable with empirical downscaling algorithms. Keywords: Soil moisture, microwave data, downscaling, MODIS, triangle/trapezoid model.
NASA Astrophysics Data System (ADS)
Wrona, Elizabeth; Rowlandson, Tracy L.; Nambiar, Manoj; Berg, Aaron A.; Colliander, Andreas; Marsh, Philip
2017-05-01
This study examines the Soil Moisture Active Passive soil moisture product on the Equal Area Scalable Earth-2 (EASE-2) 36 km Global cylindrical and North Polar azimuthal grids relative to two in situ soil moisture monitoring networks that were installed in 2015 and 2016. Results indicate that there is no relationship between the Soil Moisture Active Passive (SMAP) Level-2 passive soil moisture product and the upscaled in situ measurements. Additionally, there is very low correlation between modeled brightness temperature using the Community Microwave Emission Model and the Level-1 C SMAP brightness temperature interpolated to the EASE-2 Global grid; however, there is a much stronger relationship to the brightness temperature measurements interpolated to the North Polar grid, suggesting that the soil moisture product could be improved with interpolation on the North Polar grid.
NASA Technical Reports Server (NTRS)
Lapenta, William M.; Crosson, William; Dembek, Scott; Lakhtakia, Mercedes
1998-01-01
It is well known that soil moisture is a characteristic of the land surface that strongly affects the partitioning of outgoing radiation into sensible and latent heat which significantly impacts both weather and climate. Detailed land surface schemes are now being coupled to mesoscale atmospheric models in order to represent the effect of soil moisture upon atmospheric simulations. However, there is little direct soil moisture data available to initialize these models on regional to continental scales. As a result, a Soil Hydrology Model (SHM) is currently being used to generate an indirect estimate of the soil moisture conditions over the continental United States at a grid resolution of 36 Km on a daily basis since 8 May 1995. The SHM is forced by analyses of atmospheric observations including precipitation and contains detailed information on slope soil and landcover characteristics.The purpose of this paper is to evaluate the utility of initializing a detailed coupled model with the soil moisture data produced by SHM.
Uncertainty in Ecohydrological Modeling in an Arid Region Determined with Bayesian Methods
Yang, Junjun; He, Zhibin; Du, Jun; Chen, Longfei; Zhu, Xi
2016-01-01
In arid regions, water resources are a key forcing factor in ecosystem circulation, and soil moisture is the critical link that constrains plant and animal life on the soil surface and underground. Simulation of soil moisture in arid ecosystems is inherently difficult due to high variability. We assessed the applicability of the process-oriented CoupModel for forecasting of soil water relations in arid regions. We used vertical soil moisture profiling for model calibration. We determined that model-structural uncertainty constituted the largest error; the model did not capture the extremes of low soil moisture in the desert-oasis ecotone (DOE), particularly below 40 cm soil depth. Our results showed that total uncertainty in soil moisture prediction was improved when input and output data, parameter value array, and structure errors were characterized explicitly. Bayesian analysis was applied with prior information to reduce uncertainty. The need to provide independent descriptions of uncertainty analysis (UA) in the input and output data was demonstrated. Application of soil moisture simulation in arid regions will be useful for dune-stabilization and revegetation efforts in the DOE. PMID:26963523
NASA Astrophysics Data System (ADS)
Christiansen, Jesper; Elberling, Bo; Ribbons, Relena; Hedo, Javier; José Fernández Alonso, Maria; Krych, Lukasz; Sandris Nielsen, Dennis; Kitzler, Barbara
2016-04-01
Reactive nitrogen (N) in the environment has doubled relative to the natural global N cycle with consequences for biogeochemical cycling of soil N. Also, climate change is expected to alter precipitation patterns and increase soil temperatures which in Arctic environments may accelerate permafrost thawing. The combination of changes in the soil N cycle and hydrological regimes may alter microbial transformations of soil N with unknown impacts on N2O and N2 emissions from temperate and Arctic soils. We present the first results of soil N2O and N2 emissions, chemistry and microbial communities over soil hydrological gradients (upslope, intermediate and wet) across a global N deposition gradient. The global gradient covered an N-limited high Arctic tundra (Zackenberg-ZA), a pacific temperate rain forest (Vancouver Island-VI) and an N saturated forest in Austria (Klausenleopoldsdorf-KL). The N2O and N2 emissions were measured from intact cores at field moisture in a He-atmosphere system. Extractable NH4+ and NO3-, organic and microbial C and N and potential enzyme-activities were determined on soil samples. Soil genomic DNA was subjected to MiSeq-based tag-encoded 16S rRNA and ITS gene amplicon sequencing for the bacterial and fungal community structure. Similar soil moisture levels were observed for the upslope, intermediate and wet locations at ZA, VI and KL, respectively. Extractable NO3- was highest at the N rich KL and lowest at ZA and showed no trend with soil moisture similar to NH4+. At ZA and VI soil NH4+ was higher than NO3- indicating a tighter N cycling. N2O emissions increased with soil moisture at all sites. The N2O emissions for the wet locations ranked similarly to NO3- with the largest response to soil moisture at KL. N2 emissions were remarkably similar across the sites and increased with soil wetness. Microbial C and N also increased with soil moisture and were overall lowest at the N rich KL site. The potential activity of protease enzyme was site dependent indicating different capacities for N turnover of the microbial community. These findings indicate a positive feedback between increased soil N and wetter soils that promotes N2O relative to N2. These interactions may be site specific due to differential functional diversity of the soil microbial community. Future characterization of the community structure will shed light on the link between the role of microbial groups related to soil N cycling pathways and the resultant partitioning of N2O and N2 emissions in these contrasting environments.
Impact of moisture variations on the circulation of the south-west monsoon
NASA Astrophysics Data System (ADS)
Kishtawal, C. M.; Pal, P. K.; Narayanan, M. S.; Manna, S. K.; Sharma, O. P.; Agarwal, Sangeeta; Upadhyaya, H. C.
1993-12-01
The impact of moisture anomalies on the circulation of the south-west Indian monsoon has been studied with a general circulation model. Newtonian relaxation is adopted to subject the model atmosphere under sustained moisture anomalies. The impact of negative anomalies of moisture was seen as a divergent circulation anomaly, while the positive anomaly was a stronger convergent anomaly. Although the humidity fields display a resilient behaviour, and relax back to normal patterns 1-2 days after the forcing terms in humidity are withdrawn, the circulation anomalies created by the moisture variation keeps growing. A feedback between positive moisture anomalies and low level convergence exists, which is terminated in the absence of external forcings.
Grote, Edmund E.; Belnap, Jayne; Housman, David C.; Sparks, Jed P.
2010-01-01
Biological soil crusts (biocrusts) are an integral part of the soil system in arid regions worldwide, stabilizing soil surfaces, aiding vascular plant establishment, and are significant sources of ecosystem nitrogen and carbon. Hydration and temperature primarily control ecosystem CO2 flux in these systems. Using constructed mesocosms for incubations under controlled laboratory conditions, we examined the effect of temperature (5-35 1C) and water content (WC, 20-100%) on CO2 exchange in light cyanobacterially dominated) and dark cyanobacteria/lichen and moss dominated) biocrusts of the cool Colorado Plateau Desert in Utah and the hot Chihuahuan Desert in New Mexico. In light crusts from both Utah and New Mexico, net photosynthesis was highest at temperatures 430 1C. Net photosynthesis in light crusts from Utah was relatively insensitive to changes in soil moisture. In contrast, light crusts from New Mexico tended to exhibit higher rates of net photosynthesis at higher soil moisture. Dark crusts originating from both sites exhibited the greatest net photosynthesis at intermediate soil water content (40-60%). Declines in net photosynthesis were observed in dark crusts with crusts from Utah showing declines at temperatures 425 1C and those originating from New Mexico showing declines at temperatures 435 1C. Maximum net photosynthesis in all crust types from all locations were strongly influenced by offsets in the optimal temperature and water content for gross photosynthesis compared with dark respiration. Gross photosynthesis tended to be maximized at some intermediate value of temperature and water content and dark respiration tended to increase linearly. The results of this study suggest biocrusts are capable of CO2 exchange under a wide range of conditions. However, significant changes in the magnitude of this exchange should be expected for the temperature and precipitation changes suggested by current climate models.
NASA Astrophysics Data System (ADS)
Lehman, B. M.; Niemann, J. D.
2008-12-01
Soil moisture exerts significant control over the partitioning of latent and sensible energy fluxes, the magnitude of both vertical and lateral water fluxes, the physiological and water-use characteristics of vegetation, and nutrient cycling. Considerable progress has been made in determining how soil characteristics, topography, and vegetation influence spatial patterns of soil moisture in humid environments at the catchment, hillslope, and plant scales. However, understanding of the controls on soil moisture patterns beyond the plant scale in semi-arid environments remains more limited. This study examines the relationships between the spatial patterns of near surface soil moisture (upper 5 cm), terrain indices, and soil properties in a small, semi-arid, montane catchment. The 8 ha catchment, located in the Cache La Poudre River Canyon in north-central Colorado, has a total relief of 115 m and an average elevation of 2193 m. It is characterized by steep slopes and shallow, gravelly/sandy soils with scattered granite outcroppings. Depth to bedrock ranges from 0 m to greater than 1 m. Vegetation in the catchment is highly correlated with topographic aspect. In particular, north-facing hillslopes are predominately vegetated by ponderosa pines, while south-facing slopes are mostly vegetated by several shrub species. Soil samples were collected at a 30 m resolution to characterize soil texture and bulk density, and several datasets consisting of more than 300 point measurements of soil moisture were collected using time domain reflectometry (TDR) between Fall 2007 and Summer 2008 at a 15 m resolution. Results from soil textural analysis performed with sieving and the ASTM standard hydrometer method show that soil texture is finer on the north-facing hillslope than on the south-facing hillslope. Cos(aspect) is the best univariate predictor of silts, while slope is the best predictor of coarser fractions up to fine gravel. Bulk density increases with depth but shows no significant relationship with topographic indices. When the catchment average soil moisture is low, the variance of soil moisture increases with the average. When the average is high, the variance remains relatively constant. Little of the variation in soil moisture is explained by topographic indices when the catchment is either very wet or dry; however, when the average soil moisture takes on intermediate values, cos(aspect) is consistently the best predictor among the terrain indices considered.
NASA Astrophysics Data System (ADS)
Singh, G.; Panda, R. K.; Mohanty, B.
2015-12-01
Prediction of root zone soil moisture status at field level is vital for developing efficient agricultural water management schemes. In this study, root zone soil moisture was estimated across the Rana watershed in Eastern India, by assimilation of near-surface soil moisture estimate from SMOS satellite into a physically-based Soil-Water-Atmosphere-Plant (SWAP) model. An ensemble Kalman filter (EnKF) technique coupled with SWAP model was used for assimilating the satellite soil moisture observation at different spatial scales. The universal triangle concept and artificial intelligence techniques were applied to disaggregate the SMOS satellite monitored near-surface soil moisture at a 40 km resolution to finer scale (1 km resolution), using higher spatial resolution of MODIS derived vegetation indices (NDVI) and land surface temperature (Ts). The disaggregated surface soil moisture were compared to ground-based measurements in diverse landscape using portable impedance probe and gravimetric samples. Simulated root zone soil moisture were compared with continuous soil moisture profile measurements at three monitoring stations. In addition, the impact of projected climate change on root zone soil moisture were also evaluated. The climate change projections of rainfall were analyzed for the Rana watershed from statistically downscaled Global Circulation Models (GCMs). The long-term root zone soil moisture dynamics were estimated by including a rainfall generator of likely scenarios. The predicted long term root zone soil moisture status at finer scale can help in developing efficient agricultural water management schemes to increase crop production, which lead to enhance the water use efficiency.
USDA-ARS?s Scientific Manuscript database
In situ measurements of soil moisture are invaluable for calibrating and validating land surface models and satellite-based soil moisture retrievals. In addition, long-term time series of in situ soil moisture measurements themselves can reveal trends in the water cycle related to climate or land co...
NASA Astrophysics Data System (ADS)
Burgin, M. S.; van Zyl, J. J.
2017-12-01
Traditionally, substantial ancillary data is needed to parametrize complex electromagnetic models to estimate soil moisture from polarimetric radar data. The Soil Moisture Active Passive (SMAP) baseline radar soil moisture retrieval algorithm uses a data cube approach, where a cube of radar backscatter values is calculated using sophisticated models. In this work, we utilize the empirical approach by Kim and van Zyl (2009) which is an optional SMAP radar soil moisture retrieval algorithm; it expresses radar backscatter of a vegetated scene as a linear function of soil moisture, hence eliminating the need for ancillary data. We use 2.5 years of L-band Aquarius radar and radiometer derived soil moisture data to determine two coefficients of a linear model function on a global scale. These coefficients are used to estimate soil moisture with 2.5 months of L-band SMAP and L-band PALSAR-2 data. The estimated soil moisture is compared with the SMAP Level 2 radiometer-only soil moisture product; the global unbiased RMSE of the SMAP derived soil moisture corresponds to 0.06-0.07 cm3/cm3. In this study, we leverage the three diverse L-band radar data sets to investigate the impact of pixel size and pixel heterogeneity on soil moisture estimation performance. Pixel sizes range from 100 km for Aquarius, over 3, 9, 36 km for SMAP, to 10m for PALSAR-2. Furthermore, we observe seasonal variation in the radar sensitivity to soil moisture which allows the identification and quantification of seasonally changing vegetation. Utilizing this information, we further improve the estimation performance. The research described in this paper is supported by the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. Copyright 2017. All rights reserved.
USDA-ARS?s Scientific Manuscript database
The FASST (Fast All Season Strength model, US Army Corps of Engineers), one-dimensional hydrologic model was used to evaluate soil moisture across the USDA-ARS-SEWRL Little River Watershed in south Georgia US. The ultimate goal of this research is to assess the spatial variation of soil moisture acr...
NASA Technical Reports Server (NTRS)
Reichle, Rolf H.; De Lannoy, Gabrielle J. M.
2012-01-01
The Soil Moisture and Ocean Salinity (SMOS) satellite mission provides global measurements of L-band brightness temperatures at horizontal and vertical polarization and a variety of incidence angles that are sensitive to moisture and temperature conditions in the top few centimeters of the soil. These L-band observations can therefore be assimilated into a land surface model to obtain surface and root zone soil moisture estimates. As part of the observation operator, such an assimilation system requires a radiative transfer model (RTM) that converts geophysical fields (including soil moisture and soil temperature) into modeled L-band brightness temperatures. At the global scale, the RTM parameters and the climatological soil moisture conditions are still poorly known. Using look-up tables from the literature to estimate the RTM parameters usually results in modeled L-band brightness temperatures that are strongly biased against the SMOS observations, with biases varying regionally and seasonally. Such biases must be addressed within the land data assimilation system. In this presentation, the estimation of the RTM parameters is discussed for the NASA GEOS-5 land data assimilation system, which is based on the ensemble Kalman filter (EnKF) and the Catchment land surface model. In the GEOS-5 land data assimilation system, soil moisture and brightness temperature biases are addressed in three stages. First, the global soil properties and soil hydraulic parameters that are used in the Catchment model were revised to minimize the bias in the modeled soil moisture, as verified against available in situ soil moisture measurements. Second, key parameters of the "tau-omega" RTM were calibrated prior to data assimilation using an objective function that minimizes the climatological differences between the modeled L-band brightness temperatures and the corresponding SMOS observations. Calibrated parameters include soil roughness parameters, vegetation structure parameters, and the single scattering albedo. After this climatological calibration, the modeling system can provide L-band brightness temperatures with a global mean absolute bias of less than 10K against SMOS observations, across multiple incidence angles and for horizontal and vertical polarization. Third, seasonal and regional variations in the residual biases are addressed by estimating the vegetation optical depth through state augmentation during the assimilation of the L-band brightness temperatures. This strategy, tested here with SMOS data, is part of the baseline approach for the Level 4 Surface and Root Zone Soil Moisture data product from the planned Soil Moisture Active Passive (SMAP) satellite mission.
NASA Technical Reports Server (NTRS)
Wetzel, Peter J.; Chang, Jy-Tai
1988-01-01
Observations of surface heterogeneity of soil moisture from scales of meters to hundreds of kilometers are discussed, and a relationship between grid element size and soil moisture variability is presented. An evapotranspiration model is presented which accounts for the variability of soil moisture, standing surface water, and vegetation internal and stomatal resistance to moisture flow from the soil. The mean values and standard deviations of these parameters are required as input to the model. Tests of this model against field observations are reported, and extensive sensitivity tests are presented which explore the importance of including subgrid-scale variability in an evapotranspiration model.
Comparing soil moisture memory in satellite observations and models
NASA Astrophysics Data System (ADS)
Stacke, Tobias; Hagemann, Stefan; Loew, Alexander
2013-04-01
A major obstacle to a correct parametrization of soil processes in large scale global land surface models is the lack of long term soil moisture observations for large parts of the globe. Currently, a compilation of soil moisture data derived from a range of satellites is released by the ESA Climate Change Initiative (ECV_SM). Comprising the period from 1978 until 2010, it provides the opportunity to compute climatological relevant statistics on a quasi-global scale and to compare these to the output of climate models. Our study is focused on the investigation of soil moisture memory in satellite observations and models. As a proxy for memory we compute the autocorrelation length (ACL) of the available satellite data and the uppermost soil layer of the models. Additional to the ECV_SM data, AMSR-E soil moisture is used as observational estimate. Simulated soil moisture fields are taken from ERA-Interim reanalysis and generated with the land surface model JSBACH, which was driven with quasi-observational meteorological forcing data. The satellite data show ACLs between one week and one month for the greater part of the land surface while the models simulate a longer memory of up to two months. Some pattern are similar in models and observations, e.g. a longer memory in the Sahel Zone and the Arabian Peninsula, but the models are not able to reproduce regions with a very short ACL of just a few days. If the long term seasonality is subtracted from the data the memory is strongly shortened, indicating the importance of seasonal variations for the memory in most regions. Furthermore, we analyze the change of soil moisture memory in the different soil layers of the models to investigate to which extent the surface soil moisture includes information about the whole soil column. A first analysis reveals that the ACL is increasing for deeper layers. However, its increase is stronger in the soil moisture anomaly than in its absolute values and the first even exceeds the latter in the deepest layer. From this we conclude that the seasonal soil moisture variations dominate the memory close to the surface but these are dampened in lower layers where the memory is mainly affected by longer term variations.
Reflection of acoustic wave from the elastic seabed with an overlying gassy poroelastic layer
NASA Astrophysics Data System (ADS)
Chen, Weiyun; Wang, Zhihua; Zhao, Kai; Chen, Guoxing; Li, Xiaojun
2015-10-01
Based on the multiphase poroelasticity theory, the reflection characteristics of an obliquely incident acoustic wave upon a plane interface between overlying water and a gassy marine sediment layer with underlying elastic solid seabed are investigated. The sandwiched gassy layer is modelled as a porous material with finite thickness, which is saturated by two compressible and viscous fluids (liquid and gas). The closed-form expression for the amplitude ratio of the reflected wave, called reflection coefficient, is derived theoretically according to the boundary conditions at the upper and lower interfaces in our proposed model. Using numerical calculation, the influences of layer thickness, incident angle, wave frequency and liquid saturation of sandwiched porous layer on the reflection coefficient are analysed, respectively. It is revealed that the reflection coefficient is closely associated with incident angle and sandwiched layer thickness. Moreover, in different frequency ranges, the dependence of the wave reflection characteristics on moisture (or gas) variations in the intermediate marine sediment layer is distinguishing.
NASA Astrophysics Data System (ADS)
Crow, W. T.; Chen, F.; Reichle, R. H.; Xia, Y.; Liu, Q.
2018-05-01
Accurate partitioning of precipitation into infiltration and runoff is a fundamental objective of land surface models tasked with characterizing the surface water and energy balance. Temporal variability in this partitioning is due, in part, to changes in prestorm soil moisture, which determine soil infiltration capacity and unsaturated storage. Utilizing the National Aeronautics and Space Administration Soil Moisture Active Passive Level-4 soil moisture product in combination with streamflow and precipitation observations, we demonstrate that land surface models (LSMs) generally underestimate the strength of the positive rank correlation between prestorm soil moisture and event runoff coefficients (i.e., the fraction of rainfall accumulation volume converted into stormflow runoff during a storm event). Underestimation is largest for LSMs employing an infiltration-excess approach for stormflow runoff generation. More accurate coupling strength is found in LSMs that explicitly represent subsurface stormflow or saturation-excess runoff generation processes.
Divergent surface and total soil moisture projections under global warming
Berg, Alexis; Sheffield, Justin; Milly, Paul C.D.
2017-01-01
Land aridity has been projected to increase with global warming. Such projections are mostly based on off-line aridity and drought metrics applied to climate model outputs but also are supported by climate-model projections of decreased surface soil moisture. Here we comprehensively analyze soil moisture projections from the Coupled Model Intercomparison Project phase 5, including surface, total, and layer-by-layer soil moisture. We identify a robust vertical gradient of projected mean soil moisture changes, with more negative changes near the surface. Some regions of the northern middle to high latitudes exhibit negative annual surface changes but positive total changes. We interpret this behavior in the context of seasonal changes in the surface water budget. This vertical pattern implies that the extensive drying predicted by off-line drought metrics, while consistent with the projected decline in surface soil moisture, will tend to overestimate (negatively) changes in total soil water availability.
NASA Astrophysics Data System (ADS)
Massman, W. J.
2012-10-01
Heating any soil during a sufficiently intense wildfire or prescribed burn can alter it irreversibly, causing many significant, long-term biological, chemical, and hydrological effects. Given the climate-change-driven increasing probability of wildfires and the increasing use of prescribed burns by land managers, it is important to better understand the dynamics of the coupled heat and moisture transport in soil during these extreme heating events. Furthermore, improved understanding and modeling of heat and mass transport during extreme conditions should provide insights into the associated transport mechanisms under more normal conditions. The present study describes a numerical model developed to simulate soil heat and moisture transport during fires where the surface heating often ranges between 10,000 and 100,000 W m-2 for several minutes to several hours. Basically, the model extends methods commonly used to model coupled heat flow and moisture evaporation at ambient conditions into regions of extreme dryness and heat. But it also incorporates some infrequently used formulations for temperature dependencies of the soil specific heat, thermal conductivity, and the water retention curve, as well as advective effects due to the large changes in volume that occur when liquid water is rapidly volatilized. Model performance is tested against laboratory measurements of soil temperature and moisture changes at several depths during controlled heating events. Qualitatively, the model agrees with the laboratory observations, namely, it simulates an increase in soil moisture ahead of the drying front (due to the condensation of evaporated soil water at the front) and a hiatus in the soil temperature rise during the strongly evaporative stage of the soil drying. Nevertheless, it is shown that the model is incapable of producing a physically realistic solution because it does not (and, in fact, cannot) represent the relationship between soil water potential and soil moisture at extremely low soil moisture contents (i.e., residual or bound water: θ < 0.01 m3 m-3, for example). Diagnosing the model's performance yields important insights into how to make progress on modeling soil evaporation and heating under conditions of high temperatures and very low soil moisture content.
Application of Terrestrial Microwave Remote Sensing to Agricultural Drought Monitoring
NASA Astrophysics Data System (ADS)
Crow, W. T.; Bolten, J. D.
2014-12-01
Root-zone soil moisture information is a valuable diagnostic for detecting the onset and severity of agricultural drought. Current attempts to globally monitor root-zone soil moisture are generally based on the application of soil water balance models driven by observed meteorological variables. Such systems, however, are prone to random error associated with: incorrect process model physics, poor parameter choices and noisy meteorological inputs. The presentation will describe attempts to remediate these sources of error via the assimilation of remotely-sensed surface soil moisture retrievals from satellite-based passive microwave sensors into a global soil water balance model. Results demonstrate the ability of satellite-based soil moisture retrieval products to significantly improve the global characterization of root-zone soil moisture - particularly in data-poor regions lacking adequate ground-based rain gage instrumentation. This success has lead to an on-going effort to implement an operational land data assimilation system at the United States Department of Agriculture's Foreign Agricultural Service (USDA FAS) to globally monitor variations in root-zone soil moisture availability via the integration of satellite-based precipitation and soil moisture information. Prospects for improving the performance of the USDA FAS system via the simultaneous assimilation of both passive and active-based soil moisture retrievals derived from the upcoming NASA Soil Moisture Active/Passive mission will also be discussed.
Assimilation of Spatially Sparse In Situ Soil Moisture Networks into a Continuous Model Domain
NASA Astrophysics Data System (ADS)
Gruber, A.; Crow, W. T.; Dorigo, W. A.
2018-02-01
Growth in the availability of near-real-time soil moisture observations from ground-based networks has spurred interest in the assimilation of these observations into land surface models via a two-dimensional data assimilation system. However, the design of such systems is currently hampered by our ignorance concerning the spatial structure of error afflicting ground and model-based soil moisture estimates. Here we apply newly developed triple collocation techniques to provide the spatial error information required to fully parameterize a two-dimensional (2-D) data assimilation system designed to assimilate spatially sparse observations acquired from existing ground-based soil moisture networks into a spatially continuous Antecedent Precipitation Index (API) model for operational agricultural drought monitoring. Over the contiguous United States (CONUS), the posterior uncertainty of surface soil moisture estimates associated with this 2-D system is compared to that obtained from the 1-D assimilation of remote sensing retrievals to assess the value of ground-based observations to constrain a surface soil moisture analysis. Results demonstrate that a fourfold increase in existing CONUS ground station density is needed for ground network observations to provide a level of skill comparable to that provided by existing satellite-based surface soil moisture retrievals.
Space-time modeling of soil moisture
NASA Astrophysics Data System (ADS)
Chen, Zijuan; Mohanty, Binayak P.; Rodriguez-Iturbe, Ignacio
2017-11-01
A physically derived space-time mathematical representation of the soil moisture field is carried out via the soil moisture balance equation driven by stochastic rainfall forcing. The model incorporates spatial diffusion and in its original version, it is shown to be unable to reproduce the relative fast decay in the spatial correlation functions observed in empirical data. This decay resulting from variations in local topography as well as in local soil and vegetation conditions is well reproduced via a jitter process acting multiplicatively over the space-time soil moisture field. The jitter is a multiplicative noise acting on the soil moisture dynamics with the objective to deflate its correlation structure at small spatial scales which are not embedded in the probabilistic structure of the rainfall process that drives the dynamics. These scales of order of several meters to several hundred meters are of great importance in ecohydrologic dynamics. Properties of space-time correlation functions and spectral densities of the model with jitter are explored analytically, and the influence of the jitter parameters, reflecting variabilities of soil moisture at different spatial and temporal scales, is investigated. A case study fitting the derived model to a soil moisture dataset is presented in detail.
The effect of soil moisture anomalies on maize yield in Germany
NASA Astrophysics Data System (ADS)
Peichl, Michael; Thober, Stephan; Meyer, Volker; Samaniego, Luis
2018-03-01
Crop models routinely use meteorological variations to estimate crop yield. Soil moisture, however, is the primary source of water for plant growth. The aim of this study is to investigate the intraseasonal predictability of soil moisture to estimate silage maize yield in Germany. We also evaluate how approaches considering soil moisture perform compare to those using only meteorological variables. Silage maize is one of the most widely cultivated crops in Germany because it is used as a main biomass supplier for energy production in the course of the German Energiewende (energy transition). Reduced form fixed effect panel models are employed to investigate the relationships in this study. These models are estimated for each month of the growing season to gain insights into the time-varying effects of soil moisture and meteorological variables. Temperature, precipitation, and potential evapotranspiration are used as meteorological variables. Soil moisture is transformed into anomalies which provide a measure for the interannual variation within each month. The main result of this study is that soil moisture anomalies have predictive skills which vary in magnitude and direction depending on the month. For instance, dry soil moisture anomalies in August and September reduce silage maize yield more than 10 %, other factors being equal. In contrast, dry anomalies in May increase crop yield up to 7 % because absolute soil water content is higher in May compared to August due to its seasonality. With respect to the meteorological terms, models using both temperature and precipitation have higher predictability than models using only one meteorological variable. Also, models employing only temperature exhibit elevated effects.
Vegetation function and non-uniqueness of the hydrological response
NASA Astrophysics Data System (ADS)
Ivanov, V. Y.; Fatichi, S.; Kampf, S. K.; Caporali, E.
2012-04-01
Through local moisture uptake vegetation exerts seasonal and longer-term impacts on the watershed hydrological response. However, the role of vegetation may go beyond the conventionally implied and well-understood "sink" function in the basin soil moisture storage equation. We argue that vegetation function imposes a "homogenizing" effect on pre-event soil moisture spatial storage, decreasing the likelihood that a rainfall event will result in a topographically-driven redistribution of soil water and the consequent formation of variable source areas. In combination with vegetation temporal dynamics, this may lead to the non-uniqueness of the hydrological response with respect to the mean basin wetness. This study designs a set of relevant numerical experiments carried out with two physically-based models; one of the models, HYDRUS, resolves variably saturated subsurface flow using a fully three-dimensional formulation, while the other model, tRIBS+VEGGIE, uses a one-dimensional formulation applied in a quasi-three-dimensional framework in combination with the model of vegetation dynamics. We demonstrate that (1) vegetation function modifies spatial heterogeneity in moisture spatial storage by imposing different degrees of subsurface flow connectivity; explore mechanistically (2) how and why a basin with the same mean soil moisture can have distinctly different spatial soil moisture distributions; and demonstrate (2) how these distinct moisture distributions result in a hysteretic runoff response to precipitation. Furthermore, the study argues that near-surface soil moisture is an insufficient indicator of the initial moisture state of a catchment with the implication of its limited effect on hydrological predictability.
Study of moisture absorption by an organoplastic
NASA Astrophysics Data System (ADS)
Aniskevich, A. N.; Yanson, Yu. O.
1991-07-01
A complex experimental study of the state of sorbed moisture in a unidirectionally reinforced organoplastic was conducted. The methods of TG, DSC, DTA, and NMR showed that moisture absorption in OP is reversible up to 8%, the sorbed moisture does not crystallize in the temperature range from -70 to 0 °C, it is finely dispersely distributed and is in the strongly and weakly bound state, and there is almost no free moisture. The results of the sorption experiments conducted on OP and its structural components: microplastic and EDT-10 binder, in a wide range of temperature-humidity conditions and the data from physical studies showed that moisture absorption in the materials basically takes place by diffusion and is satisfactorily described by a phenomenological model based on the Fick equation. A method of accelerated determination of the sorption characteristics of anisotropic composite materials was developed, using the introduced concept of the fictitious diffusion coefficient and the extrapolation method of determining the limiting moisture content. The features of migration of moisture on the interface in a multiphase system were investigated, and the possibility of successive calculation estimation of the sorption characteristics of an organoplastic at different structural levels was demonstrated: components—unidirectionally reinforced composite—model laminated article. The tested phenomenological model of the sorption process and the experimentally obtained values of the characteristics of the material were the basis for a method of calculation determination of the resource of moisture-proofing properties of a model multilayer article of CM in nonstationary external conditions.
Assessment of initial soil moisture conditions for event-based rainfall-runoff modelling
NASA Astrophysics Data System (ADS)
Tramblay, Yves; Bouvier, Christophe; Martin, Claude; Didon-Lescot, Jean-François; Todorovik, Dragana; Domergue, Jean-Marc
2010-06-01
Flash floods are the most destructive natural hazards that occur in the Mediterranean region. Rainfall-runoff models can be very useful for flash flood forecasting and prediction. Event-based models are very popular for operational purposes, but there is a need to reduce the uncertainties related to the initial moisture conditions estimation prior to a flood event. This paper aims to compare several soil moisture indicators: local Time Domain Reflectometry (TDR) measurements of soil moisture, modelled soil moisture through the Interaction-Sol-Biosphère-Atmosphère (ISBA) component of the SIM model (Météo-France), antecedent precipitation and base flow. A modelling approach based on the Soil Conservation Service-Curve Number method (SCS-CN) is used to simulate the flood events in a small headwater catchment in the Cevennes region (France). The model involves two parameters: one for the runoff production, S, and one for the routing component, K. The S parameter can be interpreted as the maximal water retention capacity, and acts as the initial condition of the model, depending on the antecedent moisture conditions. The model was calibrated from a 20-flood sample, and led to a median Nash value of 0.9. The local TDR measurements in the deepest layers of soil (80-140 cm) were found to be the best predictors for the S parameter. TDR measurements averaged over the whole soil profile, outputs of the SIM model, and the logarithm of base flow also proved to be good predictors, whereas antecedent precipitations were found to be less efficient. The good correlations observed between the TDR predictors and the S calibrated values indicate that monitoring soil moisture could help setting the initial conditions for simplified event-based models in small basins.
Spatial Estimation of Soil Moisture Using Synthetic Aperture Radar in Alaska
NASA Astrophysics Data System (ADS)
Meade, N. G.; Hinzman, L. D.; Kane, D. L.
1999-01-01
A spatially distributed Model of Arctic Thermal and Hydrologic processes (MATH) has been developed. One of the attributes of this model is the spatial and temporal prediction of soil moisture in the active layer. The spatially distributed output from this model required verification data obtained through remote sensing to assess performance at the watershed scale independently. Therefore, a neural network was trained to predict soil moisture contents near the ground surface. The input to train the neural network is synthetic aperture radar (SAR) pixel value, and field measurements of soil moisture, and vegetation, which were used as a surrogate for surface roughness. Once the network was trained, soil moisture predictions were made based on SAR pixel value and vegetation. These results were then used for comparison with results from the hydrologic model. The quality of neural network input was less than anticipated. Our digital elevation model (DEM) was not of high enough resolution to allow exact co-registration with soil moisture measurements; therefore, the statistical correlations were not as good as hoped. However, the spatial pattern of the SAR derived soil moisture contents compares favorably with the hydrologic MATH model results. Primary surface parameters that effect SAR include topography, surface roughness, vegetation cover and soil texture. Single parameters that are considered to influence SAR include incident angle of the radar, polarization of the radiation, signal strength and returning signal integration, to name a few. These factors influence the reflectance, but if one adequately quantifies the influences of terrain and roughness, it is considered possible to extract information on soil moisture from SAR imagery analysis and in turn use SAR imagery to validate hydrologic models
Should precipitation influence dust emission in global dust models?
NASA Astrophysics Data System (ADS)
Okin, Gregory
2016-04-01
Soil moisture modulates the threshold shear stress required to initiate aeolian transport and dust emission. Most of the theoretical and laboratory work that has confirmed the impact of soil moisture has appropriately acknowledged that it is the soil moisture of a surface layer a few grain diameters thick that truly controls threshold shear velocity. Global and regional models of dust emission include the effect of soil moisture on transport threshold, but most ignore the fact that only the moisture of the very topmost "active layer" matters. The soil moisture in the active layer can differ greatly from that integrated through the top 2, 5, 10, or 100 cm (surface layers used by various global models) because the top 2 mm of heavy texture soils dries within ~1/2 day while sandy soils dry within less than 2 hours. Thus, in drylands where dust emission occurs, it is likely that this top layer is drier than the underlying soil in the days and weeks after rain. This paper explores, globally, the time between rain events in relation to the time for the active layer to dry and the timing of high wind events. This analysis is carried out using the same coarse reanalyses used in global dust models and is intended to inform the soil moisture controls in these models. The results of this analysis indicate that the timing between events is, in almost all dust-producing areas, significantly longer than the drying time of the active layer, even when considering soil texture differences. Further, the analysis shows that the probability of a high wind event during the period after a rain where the surface is wet is small. Therefore, in coarse global models, there is little reason to include rain-derived soil moisture in the modeling scheme.
NASA Astrophysics Data System (ADS)
Yan, Hongxiang; Moradkhani, Hamid; Abbaszadeh, Peyman
2017-04-01
Assimilation of satellite soil moisture and streamflow data into hydrologic models using has received increasing attention over the past few years. Currently, these observations are increasingly used to improve the model streamflow and soil moisture predictions. However, the performance of this land data assimilation (DA) system still suffers from two limitations: 1) satellite data scarcity and quality; and 2) particle weight degeneration. In order to overcome these two limitations, we propose two possible solutions in this study. First, the general Gaussian geostatistical approach is proposed to overcome the limitation in the space/time resolution of satellite soil moisture products thus improving their accuracy at uncovered/biased grid cells. Secondly, an evolutionary PF approach based on Genetic Algorithm (GA) and Markov Chain Monte Carlo (MCMC), the so-called EPF-MCMC, is developed to further reduce weight degeneration and improve the robustness of the land DA system. This study provides a detailed analysis of the joint and separate assimilation of streamflow and satellite soil moisture into a distributed Sacramento Soil Moisture Accounting (SAC-SMA) model, with the use of recently developed EPF-MCMC and the general Gaussian geostatistical approach. Performance is assessed over several basins in the USA selected from Model Parameter Estimation Experiment (MOPEX) and located in different climate regions. The results indicate that: 1) the general Gaussian approach can predict the soil moisture at uncovered grid cells within the expected satellite data quality threshold; 2) assimilation of satellite soil moisture inferred from the general Gaussian model can significantly improve the soil moisture predictions; and 3) in terms of both deterministic and probabilistic measures, the EPF-MCMC can achieve better streamflow predictions. These results recommend that the geostatistical model is a helpful tool to aid the remote sensing technique and the EPF-MCMC is a reliable and effective DA approach in hydrologic applications.
NASA Astrophysics Data System (ADS)
Saharia, M.; Wood, A.; Clark, M. P.; Bennett, A.; Nijssen, B.; Clark, E.; Newman, A. J.
2017-12-01
Most operational streamflow forecasting systems rely on a forecaster-in-the-loop approach in which some parts of the forecast workflow require an experienced human forecaster. But this approach faces challenges surrounding process reproducibility, hindcasting capability, and extension to large domains. The operational hydrologic community is increasingly moving towards `over-the-loop' (completely automated) large-domain simulations yet recent developments indicate a widespread lack of community knowledge about the strengths and weaknesses of such systems for forecasting. A realistic representation of land surface hydrologic processes is a critical element for improving forecasts, but often comes at the substantial cost of forecast system agility and efficiency. While popular grid-based models support the distributed representation of land surface processes, intermediate-scale Hydrologic Unit Code (HUC)-based modeling could provide a more efficient and process-aligned spatial discretization, reducing the need for tradeoffs between model complexity and critical forecasting requirements such as ensemble methods and comprehensive model calibration. The National Center for Atmospheric Research is collaborating with the University of Washington, the Bureau of Reclamation and the USACE to implement, assess, and demonstrate real-time, over-the-loop distributed streamflow forecasting for several large western US river basins and regions. In this presentation, we present early results from short to medium range hydrologic and streamflow forecasts for the Pacific Northwest (PNW). We employ a real-time 1/16th degree daily ensemble model forcings as well as downscaled Global Ensemble Forecasting System (GEFS) meteorological forecasts. These datasets drive an intermediate-scale configuration of the Structure for Unifying Multiple Modeling Alternatives (SUMMA) model, which represents the PNW using over 11,700 HUCs. The system produces not only streamflow forecasts (using the MizuRoute channel routing tool) but also distributed model states such as soil moisture and snow water equivalent. We also describe challenges in distributed model-based forecasting, including the application and early results of real-time hydrologic data assimilation.
The effect of row structure on soil moisture retrieval accuracy from passive microwave data.
Xingming, Zheng; Kai, Zhao; Yangyang, Li; Jianhua, Ren; Yanling, Ding
2014-01-01
Row structure causes the anisotropy of microwave brightness temperature (TB) of soil surface, and it also can affect soil moisture retrieval accuracy when its influence is ignored in the inversion model. To study the effect of typical row structure on the retrieved soil moisture and evaluate if there is a need to introduce this effect into the inversion model, two ground-based experiments were carried out in 2011. Based on the observed C-band TB, field soil and vegetation parameters, row structure rough surface assumption (Q p model and discrete model), including the effect of row structure, and flat rough surface assumption (Q p model), ignoring the effect of row structure, are used to model microwave TB of soil surface. Then, soil moisture can be retrieved, respectively, by minimizing the difference of the measured and modeled TB. The results show that soil moisture retrieval accuracy based on the row structure rough surface assumption is approximately 0.02 cm(3)/cm(3) better than the flat rough surface assumption for vegetated soil, as well as 0.015 cm(3)/cm(3) better for bare and wet soil. This result indicates that the effect of row structure cannot be ignored for accurately retrieving soil moisture of farmland surface when C-band is used.
Soil moisture retrieval by active/passive microwave remote sensing data
NASA Astrophysics Data System (ADS)
Wu, Shengli; Yang, Lijuan
2012-09-01
This study develops a new algorithm for estimating bare surface soil moisture using combined active / passive microwave remote sensing on the basis of TRMM (Tropical Rainfall Measuring Mission). Tropical Rainfall Measurement Mission was jointly launched by NASA and NASDA in 1997, whose main task was to observe the precipitation of the area in 40 ° N-40 ° S. It was equipped with active microwave radar sensors (PR) and passive sensor microwave imager (TMI). To accurately estimate bare surface soil moisture, precipitation radar (PR) and microwave imager (TMI) are simultaneously used for observation. According to the frequency and incident angle setting of PR and TMI, we first need to establish a database which includes a large range of surface conditions; and then we use Advanced Integral Equation Model (AIEM) to calculate the backscattering coefficient and emissivity. Meanwhile, under the accuracy of resolution, we use a simplified theoretical model (GO model) and the semi-empirical physical model (Qp Model) to redescribe the process of scattering and radiation. There are quite a lot of parameters effecting backscattering coefficient and emissivity, including soil moisture, surface root mean square height, correlation length, and the correlation function etc. Radar backscattering is strongly affected by the surface roughness, which includes the surface root mean square roughness height, surface correlation length and the correlation function we use. And emissivity is differently affected by the root mean square slope under different polarizations. In general, emissivity decreases with the root mean square slope increases in V polarization, and increases with the root mean square slope increases in H polarization. For the GO model, we found that the backscattering coefficient is only related to the root mean square slope and soil moisture when the incident angle is fixed. And for Qp Model, through the analysis, we found that there is a quite good relationship between Qpparameter and root mean square slope. So here, root mean square slope is a parameter that both models shared. Because of its big influence to backscattering and emissivity, we need to throw it out during the process of the combination of GO model and Qp model. The result we obtain from the combined model is the Fresnel reflection coefficient in the normal direction gama(0). It has a good relationship with the soil dielectric constant. In Dobson Model, there is a detailed description about Fresnel reflection coefficient and soil moisture. With the help of Dobson model and gama(0) that we have obtained, we can get the soil moisture that we want. The backscattering coefficient and emissivity data used in combined model is from TRMM/PR, TMI; with this data, we can obtain gama(0); further, we get the soil moisture by the relationship of the two parameters-- gama(0) and soil moisture. To validate the accuracy of the retrieval soil moisture, there is an experiment conducted in Tibet. The soil moisture data which is used to validate the retrieval algorithm is from GAME-Tibet IOP98 Soil Moisture and Temperature Measuring System (SMTMS). There are 9 observing sites in SMTMS to validate soil moisture. Meanwhile, we use the SMTMS soil moisture data obtained by Time Domain Reflectometer (TDR) to do the validation. And the result shows the comparison of retrieval and measured results is very good. Through the analysis, we can see that the retrieval and measured results in D66 is nearly close; and in MS3608, the measured result is a little higher than retrieval result; in MS3637, the retrieval result is a little higher than measured result. According to the analysis of the simulation results, we found that this combined active and passive approach to retrieve the soil moisture improves the retrieval accuracy.
Landscape patterns of CH4 fluxes in an alpine tundra ecosystem
West, A.E.; Brooks, P.D.; Fisk, M.C.; Smith, Lesley K.; Holland, E.A.; Jaeger, C. H.; Babcock, S.; Lai, R.S.; Schmidt, S.K.
1999-01-01
We measured CH4 fluxes from three major plant communities characteristic of alpine tundra in the Colorado Front Range. Plant communities in this ecosystem are determined by soil moisture regimes induced by winter snowpack distribution. Spatial patterns of CH4 flux during the snow-free season corresponded roughly with these plant communities. In Carex-dominated meadows, which receive the most moisture from snowmelt, net CH4 production occurred. However, CH4 production in one Carex site (seasonal mean = +8.45 mg CH4 m-2 d-1) was significantly larger than in the other Carex sites (seasonal means = -0.06 and +0.05 mg CH4 m-2 d-1). This high CH4 flux may have resulted from shallower snowpack during the winter. In Acomastylis meadows, which have an intermediate moisture regime, CH4 oxidation dominated (seasonal mean = -0.43 mg CH4 m-2 d-1). In the windswept Kobresia meadow plant community, which receive the least amount of moisture from snowmelt, only CH4 oxidation was observed (seasonal mean = -0.77 mg CH4 m-2 d-1). Methane fluxes correlated with a different set of environmental factors within each plant community. In the Carex plant community, CH4 emission was limited by soil temperature. In the Acomastylis meadows, CH4 oxidation rates correlated positively with soil temperature and negatively with soil moisture. In the Kobresia community, CH4 oxidation was stimulated by precipitation. Thus, both snow-free season CH4 fluxes and the controls on those CH4 fluxes were related to the plant communities determined by winter snowpack.
NASA Astrophysics Data System (ADS)
Bonfante, A.; Basile, A.; de Mascellis, R.; Manna, P.; Terribile, F.
2009-04-01
Soil classification according to Soil Taxonomy include, as fundamental feature, the estimation of soil moisture regime. The term soil moisture regime refers to the "presence or absence either of ground water or of water held at a tension of less than 1500 kPa in the soil or in specific horizons during periods of the year". In the classification procedure, defining of the soil moisture control section is the primary step in order to obtain the soil moisture regimes classification. Currently, the estimation of soil moisture regimes is carried out through simple calculation schemes, such as Newhall and Billaux models, and only in few cases some authors suggest the use of different more complex models (i.e., EPIC) In fact, in the Soil Taxonomy, the definition of the soil moisture control section is based on the wetting front position in two different conditions: the upper boundary is the depth to which a dry soil will be moistened by 2.5 cm of water within 24 hours and the lower boundary is the depth to which a dry soil will be moistened by 7.5 cm of water within 48 hours. Newhall, Billaux and EPIC models don't use physical laws to describe soil water flows, but they use a simple bucket-like scheme where the soil is divided into several compartments and water moves, instantly, only downward when the field capacity is achieved. On the other side, a large number of one-dimensional hydrological simulation models (SWAP, Cropsyst, Hydrus, MACRO, etc..) are available, tested and successfully used. The flow is simulated according to pressure head gradients through the numerical solution of the Richard's equation. These simulation models can be fruitful used to improve the study of soil moisture regimes. The aims of this work are: (i) analysis of the soil moisture control section concept by a physically based model (SWAP); (ii) comparison of the classification obtained in five different Italian pedoclimatic conditions (Mantova and Lodi in northern Italy; Salerno, Benevento and Caserta in southern Italy) applying the classical models (Newhall e Billaux) and the physically-based models (CropSyst e SWAP), The results have shown that the Soil Taxonomy scheme for the definition of the soil moisture regime is unrealistic for the considered Mediterranean soil hydrological conditions. In fact, the same classifications arise irrespective of the soil type. In this respect some suggestions on how modified the section control boundaries were formulated. Keywords: Soil moisture regimes, Newhall, Swap, Soil Taxonomy
Evaluating Vertical Moisture Structure of the Madden-Julian Oscillation in Contemporary GCMs
NASA Astrophysics Data System (ADS)
Guan, B.; Jiang, X.; Waliser, D. E.
2013-12-01
The Madden-Julian Oscillation (MJO) remains a major challenge in our understanding and modeling of the tropical convection and circulation. Many models have troubles in realistically simulating key characteristics of the MJO, such as the strength, period, and eastward propagation. For models that do simulate aspects of the MJO, it remains to be understood what parameters and processes are the most critical in determining the quality of the simulations. This study focuses on the vertical structure of moisture in MJO simulations, with the aim to identify and understand the relationship between MJO simulation qualities and key parameters related to moisture. A series of 20-year simulations conducted by 26 GCMs are analyzed, including four that are coupled to ocean models and two that have a two-dimensional cloud resolving model embedded (i.e., superparameterized). TRMM precipitation and ERA-Interim reanalysis are used to evaluate the model simulations. MJO simulation qualities are evaluated based on pattern correlations of lead/lag regressions of precipitation - a measure of the model representation of the eastward propagating MJO convection. Models with strongest and weakest MJOs (top and bottom quartiles) are compared in terms of differences in moisture content, moisture convergence, moistening rate, and moist static energy. It is found that models with strongest MJOs have better representations of the observed vertical tilt of moisture. Relative importance of convection, advection, boundary layer, and large scale convection/precipitation are discussed in terms of their contribution to the moistening process. The results highlight the overall importance of vertical moisture structure in MJO simulations. The work contributes to the climatological component of the joint WCRP-WWRP/THORPEX YOTC MJO Task Force and the GEWEX Atmosphere System Study (GASS) global model evaluation project focused on the vertical structure and diabatic processes of the MJO.
Modelling soil water repellency at the daily scale in Portuguese burnt and unburnt eucalypt stands
NASA Astrophysics Data System (ADS)
Nunes, João Pedro; van der Slik, Bart; Marisa Santos, Juliana; Malvar Cortizo, Maruxa; Keizer, Jan Jacob
2014-05-01
Soil water repellency can impact soil hydrology, especially soil wetting. This creates a challenge for hydrological modelling in repellency-prone regions, since current models are generally unable to take it into account. This communication focuses on the development and evaluation of a daily water balance model which takes repellency into account, adapted for eucalypt forest plantations in the north-western Iberian Peninsula. The model was developed and tested using data from three eucalypt stands. Two were burnt in 2005, and the data included bi-weekly measurements of soil moisture and water repellency along a transect, during two years. The third was not burnt, and the data included both weekly measurements of soil water repellency and soil moisture along transects, and continuous measurements of soil moisture at one point, performed for one year between 2011 and 2012. All sites showed low repellency during the wet winter season (although less in the unburnt site, as the winter of 2011/12 was comparatively dry) and high repellency during the dry summer season; this seasonal pattern was strongly related with soil moisture fluctuations. The water balance model was based on the Thornthwaite-Mather method. Interception and tree potential evapotranspiration were estimated using satellite imagery (MODIS NDVI), the first by estimating LAI and applying the Gash interception model, and the second using the SAMIR approach. The model itself was modified by first estimating soil water repellency from soil moisture, using an empirical relation taking into account repellent and non-repellent moisture thresholds for each site; and afterwards using soil water repellency as a limiting factor on soil wettability, by limiting the fraction of infiltration which could replenish soil moisture. Results indicate that this simple approach to simulate repellency can provide adequate model performance and can be easily included in hydrological models.
NASA Astrophysics Data System (ADS)
Lorenz, Ruth; Argüeso, Daniel; Donat, Markus G.; Pitman, Andrew J.; van den Hurk, Bart; Berg, Alexis; Lawrence, David M.; Chéruy, Frédérique; Ducharne, Agnès.; Hagemann, Stefan; Meier, Arndt; Milly, P. C. D.; Seneviratne, Sonia I.
2016-01-01
We examine how soil moisture variability and trends affect the simulation of temperature and precipitation extremes in six global climate models using the experimental protocol of the Global Land-Atmosphere Coupling Experiment of the Coupled Model Intercomparison Project, Phase 5 (GLACE-CMIP5). This protocol enables separate examinations of the influences of soil moisture variability and trends on the intensity, frequency, and duration of climate extremes by the end of the 21st century under a business-as-usual (Representative Concentration Pathway 8.5) emission scenario. Removing soil moisture variability significantly reduces temperature extremes over most continental surfaces, while wet precipitation extremes are enhanced in the tropics. Projected drying trends in soil moisture lead to increases in intensity, frequency, and duration of temperature extremes by the end of the 21st century. Wet precipitation extremes are decreased in the tropics with soil moisture trends in the simulations, while dry extremes are enhanced in some regions, in particular the Mediterranean and Australia. However, the ensemble results mask considerable differences in the soil moisture trends simulated by the six climate models. We find that the large differences between the models in soil moisture trends, which are related to an unknown combination of differences in atmospheric forcing (precipitation, net radiation), flux partitioning at the land surface, and how soil moisture is parameterized, imply considerable uncertainty in future changes in climate extremes.
NASA Astrophysics Data System (ADS)
Shashikumar, C.; Pradhan, R. C.; Mishra, S.
2018-06-01
Shorea robusta (Sal) is mainly harvested and processed for its seed oil, which has diverse application in commercial food and non-food based industries. Before extraction of its oil, seeds undergo into various post-harvest unit operations. Physical and mechanical properties play an important role in the handling and other processing activity. In this study influence of moisture content and compression axis of sal seed on physico-mechanical properties were studied and their application are highlighted. The experiments were conducted at five different moisture levels of 6.38, 10.49, 13.63, 17.64, and 21.95% (d.b) at two different orientations. The first orientation is on major axis (LEN) of the seed, and the other orientation is on intermediate or minor axis (WID), which is right angle to the major axis. It was observed that 68% of sal seeds were of medium size group at initial moisture content of 10.49% (d.b). The mean length and width of sal seed was found to be 26.7 mm and 12.8 mm, respectively. It was found that values of hardness, deformation at hardness, deformation at hardness percentage and energy for rupture were higher in minor axis (WID) as compared to the major axis (LEN). The results provide necessary data that may be useful to engineers, scientists, industries in the design of a suitable post-harvest processing machine.
Variation of meat quality traits among five genotypes of chicken.
Tang, H; Gong, Y Z; Wu, C X; Jiang, J; Wang, Y; Li, K
2009-10-01
The main objective of this study was to examine the diversity of meat quality traits among 5 chicken genotypes. The genotypes included 2 Chinese native breeds (Wenchang,WCH, and Xianju), 1 commercial broiler line (Avian, AV), 1 commercial layer line (Hy-Line Brown, HLB), and 1 Chinese commercial broiler line (Lingnanhuang, LNH) synthesized by exotic and native breeds, which were slaughtered at their market ages: 16, 7, 16, and 8 wk, respectively. The effects of genotype, muscle type, and sex on meat quality traits were examined. Birds from slow-growing genotypes (WCH, Xianju, and HLB) exhibited higher shear value, inosine-5'-monophosphate concentration, lower cook loss, and more fat than those from fast-growing genotypes (AV and LNH). Chickens from WCH possessed the lowest expressible moisture, cook loss, and the highest lipid (%) among the 3 slow-growing genotypes. The HLB birds were intermediate in expressible moisture and cook loss and lowest in lipid among all genotypes. The LNH cross birds were similar to AV broilers in most meat quality parameters, although they had a lower shear force value and higher fat content than AV broilers. Breast muscle had higher expressible moisture, shear force, protein (%), inosine-5'-monophosphate content, lower cook loss, and lipid (%) than leg muscle. Muscles from male chickens had higher expressible moisture than those from the females. Variability of meat quality characteristics is mainly related to genotype and muscle type differences.
NASA Astrophysics Data System (ADS)
Shashikumar, C.; Pradhan, R. C.; Mishra, S.
2018-02-01
Shorea robusta (Sal) is mainly harvested and processed for its seed oil, which has diverse application in commercial food and non-food based industries. Before extraction of its oil, seeds undergo into various post-harvest unit operations. Physical and mechanical properties play an important role in the handling and other processing activity. In this study influence of moisture content and compression axis of sal seed on physico-mechanical properties were studied and their application are highlighted. The experiments were conducted at five different moisture levels of 6.38, 10.49, 13.63, 17.64, and 21.95% (d.b) at two different orientations. The first orientation is on major axis (LEN) of the seed, and the other orientation is on intermediate or minor axis (WID), which is right angle to the major axis. It was observed that 68% of sal seeds were of medium size group at initial moisture content of 10.49% (d.b). The mean length and width of sal seed was found to be 26.7 mm and 12.8 mm, respectively. It was found that values of hardness, deformation at hardness, deformation at hardness percentage and energy for rupture were higher in minor axis (WID) as compared to the major axis (LEN). The results provide necessary data that may be useful to engineers, scientists, industries in the design of a suitable post-harvest processing machine.
Gillespie, Sandra; Long, Rachael; Williams, Neal
2015-12-01
Pollination in crops, as in native ecosystems, is a stepwise process that can be disrupted at any stage. Healthy pollinator populations are critical for adequate visitation, but pollination still might fail if crop management interferes with the attraction and retention of pollinators. Farmers must balance the direct benefits of applying insecticide and managing irrigation rates against their potential to indirectly interfere with the pollination process. We investigated these issues in hybrid onion seed production, where previous research has shown that high insecticide use reduces pollinator attraction. We conducted field surveys of soil moisture, nectar production, pollinator visitation, pollen-stigma interactions, and seed set at multiple commercial fields across 2 yr. We then examined how management actions, such as irrigation rate (approximated by soil moisture), or insecticide use could affect the pollination process. Onions produced maximum nectar at intermediate soil moisture, and high nectar production attracted more pollinators. Insecticide use weakly affected pollinator visitation, but when applied close to bloom reduced pollen germination and pollen tube growth. Ultimately, neither soil moisture nor insecticide use directly affected seed set, but the high correlation between pollinator visitation and seed set suggests that crop management will ultimately affect yields via indirect effects on the pollination process. © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
NASA Technical Reports Server (NTRS)
De Lannoy, Gabrielle; Reichle, Rolf; Gruber, Alexander; Bechtold, Michel; Quets, Jan; Vrugt, Jasper; Wigneron, Jean-Pierre
2018-01-01
The SMOS and SMAP missions have collected a wealth of global L-band Brightness temperature (Tb) observations. The retrieval of surface Soil moisture estimates, and the estimation of other geophysical Variables, such as root-zone soil moisture and temperature, via data Assimilation into land surface models largely depends on accurate Radiative transfer modeling (RTM). This presentation will focus on various configuration aspects of the RTM (i) for the inversion of SMOS Tb to surface soil moisture, and (ii) for the forward modeling as part of a SMOS Tb data assimilation System to estimate a consistent set of geophysical land surface Variables, using the GEOS-5 Catchment Land Surface Model.
Soil moisture observations using L-, C-, and X-band microwave radiometers
NASA Astrophysics Data System (ADS)
Bolten, John Dennis
The purpose of this thesis is to further the current understanding of soil moisture remote sensing under varying conditions using L-, C-, and X-band. Aircraft and satellite instruments are used to investigate the effects of frequency and spatial resolution on soil moisture sensitivity. The specific objectives of the research are to examine multi-scale observed and modeled microwave radiobrightness, evaluate new EOS Aqua Advanced Microwave Scanning Radiometer (AMSR-E) brightness temperature and soil moisture retrievals, and examine future satellite-based technologies for soil moisture sensing. The cycling of Earth's water, energy and carbon is vital to understanding global climate. Over land, these processes are largely dependent on the amount of moisture within the top few centimeters of the soil. However, there are currently no methods available that can accurately characterize Earth's soil moisture layer at the spatial scales or temporal resolutions appropriate for climate modeling. The current work uses ground truth, satellite and aircraft remote sensing data from three large-scale field experiments having different land surface, topographic and climate conditions. A physically-based radiative transfer model is used to simulate the observed aircraft and satellite measurements using spatially and temporally co-located surface parameters. A robust analysis of surface heterogeneity and scaling is possible due to the combination of multiple datasets from a range of microwave frequencies and field conditions. Accurate characterization of spatial and temporal variability of soil moisture during the three field experiments is achieved through sensor calibration and algorithm validation. Comparisons of satellite observations and resampled aircraft observations are made using soil moisture from a Numerical Weather Prediction (NWP) model in order to further demonstrate a soil moisture correlation where point data was unavailable. The influence of vegetation, spatial scaling, and surface heterogeneity on multi-scale soil moisture prediction is presented. This work demonstrates that derived soil moisture using remote sensing provides a better coverage of soil moisture spatial variability than traditional in-situ sensors. Effects of spatial scale were shown to be less significant than frequency on soil moisture sensitivity. Retrievals of soil moisture using the current methods proved inadequate under some conditions; however, this study demonstrates the need for concurrent spaceborne frequencies including L-, C, and X-band.
The impact of fog on soil moisture dynamics in the Namib Desert
NASA Astrophysics Data System (ADS)
Li, Bonan; Wang, Lixin; Kaseke, Kudzai F.; Vogt, Roland; Li, Lin; Seely, Mary K.
2018-03-01
Soil moisture is a crucial component supporting vegetation dynamics in drylands. Despite increasing attention on fog in dryland ecosystems, the statistical characterization of fog distribution and how fog affects soil moisture dynamics have not been seen in literature. To this end, daily fog records over two years (Dec 1, 2014-Nov 1, 2016) from three sites within the Namib Desert were used to characterize fog distribution. Two sites were located within the Gobabeb Research and Training Center vicinity, the gravel plains and the sand dunes. The third site was located at the gravel plains, Kleinberg. A subset of the fog data during rainless period was used to investigate the effect of fog on soil moisture. A stochastic modeling framework was used to simulate the effect of fog on soil moisture dynamics. Our results showed that fog distribution can be characterized by a Poisson process with two parameters (arrival rate λ and average depth α (mm)). Fog and soil moisture observations from eighty (Aug 19, 2015-Nov 6, 2015) rainless days indicated a moderate positive relationship between soil moisture and fog in the Gobabeb gravel plains, a weaker relationship in the Gobabeb sand dunes while no relationship was observed at the Kleinberg site. The modeling results suggested that mean and major peaks of soil moisture dynamics can be captured by the fog modeling. Our field observations demonstrated the effects of fog on soil moisture dynamics during rainless periods at some locations, which has important implications on soil biogeochemical processes. The statistical characterization and modeling of fog distribution are of great value to predict fog distribution and investigate the effects of potential changes in fog distribution on soil moisture dynamics.
The Contribution of Soil Moisture Information to Forecast Skill: Two Studies
NASA Technical Reports Server (NTRS)
Koster, Randal
2010-01-01
This talk briefly describes two recent studies on the impact of soil moisture information on hydrological and meteorological prediction. While the studies utilize soil moisture derived from the integration of large-scale land surface models with observations-based meteorological data, the results directly illustrate the potential usefulness of satellite-derived soil moisture information (e.g., from SMOS and SMAP) for applications in prediction. The first study, the GEWEX- and ClIVAR-sponsored GLACE-2 project, quantifies the contribution of realistic soil moisture initialization to skill in subseasonal forecasts of precipitation and air temperature (out to two months). The multi-model study shows that soil moisture information does indeed contribute skill to the forecasts, particularly for air temperature, and particularly when the initial local soil moisture anomaly is large. Furthermore, the skill contributions tend to be larger where the soil moisture initialization is more accurate, as measured by the density of the observational network contributing to the initialization. The second study focuses on streamflow prediction. The relative contributions of snow and soil moisture initialization to skill in streamflow prediction at seasonal lead, in the absence of knowledge of meteorological anomalies during the forecast period, were quantified with several land surface models using uniquely designed numerical experiments and naturalized streamflow data covering mUltiple decades over the western United States. In several basins, accurate soil moisture initialization is found to contribute significant levels of predictive skill. Depending on the date of forecast issue, the contributions can be significant out to leads of six months. Both studies suggest that improvements in soil moisture initialization would lead to increases in predictive skill. The relevance of SMOS and SMAP satellite-based soil moisture information to prediction are discussed in the context of these studies.
NASA Astrophysics Data System (ADS)
Sure, A.; Dikshit, O.
2017-12-01
Root zone soil moisture (RZSM) is an important element in hydrology and agriculture. The estimation of RZSM provides insight in selecting the appropriate crops for specific soil conditions (soil type, bulk density, etc.). RZSM governs various vadose zone phenomena and subsequently affects the groundwater processes. With various satellite sensors dedicated to estimating surface soil moisture at different spatial and temporal resolutions, estimation of soil moisture at root zone level for Indo - Gangetic basin which inherits complex heterogeneous environment, is quite challenging. This study aims at estimating RZSM and understand its variation at the level of Indo - Gangetic basin with changing land use/land cover, topography, crop cycles, soil properties, temperature and precipitation patterns using two satellite derived soil moisture datasets operating at distinct frequencies with different principles of acquisition. Two surface soil moisture datasets are derived from AMSR-2 (6.9 GHz - `C' Band) and SMOS (1.4 GHz - `L' band) passive microwave sensors with coarse spatial resolution. The Soil Water Index (SWI), accounting for soil moisture from the surface, is derived by considering a theoretical two-layered water balance model and contributes in ascertaining soil moisture at the vadose zone. This index is evaluated against the widely used modelled soil moisture dataset of GLDAS - NOAH, version 2.1. This research enhances the domain of utilising the modelled soil moisture dataset, wherever the ground dataset is unavailable. The coupling between the surface soil moisture and RZSM is analysed for two years (2015-16), by defining a parameter T, the characteristic time length. The study demonstrates that deriving an optimal value of T for estimating SWI at a certain location is a function of various factors such as land, meteorological, and agricultural characteristics.
NASA Astrophysics Data System (ADS)
Hüsami Afşar, M.; Bulut, B.; Yilmaz, M. T.
2017-12-01
Soil moisture is one of the fundamental parameters of the environment that plays a major role in carbon, energy, and water cycles. Spatial distribution and temporal changes of soil moisture is one of the important components in climatic, ecological and natural hazards at global, regional and local levels scales. Therefore retrieval of soil moisture datasets has a great importance in these studies. Given soil moisture can be retrieved through different platforms (i.e., in-situ measurements, numerical modeling, and remote sensing) for the same location and time period, it is often desirable to evaluate these different datasets to assign the most accurate estimates for different purposes. During last decades, efforts have been given to provide evaluations about different soil moisture products based on various statistical analysis of the soil moisture time series (i.e., comparison of correlation, bias, and their error standard deviation). On the other hand, there is still need for the comparisons of the soil moisture products in drought analysis context. In this study, LPRM and NOAH Land Surface Model soil moisture datasets are investigated in drought analysis context using station-based watershed average datasets obtained over four USDA ARS watersheds as ground truth. Here, the drought analysis are performed using the standardized soil moisture datasets (i.e., zero mean and one standard deviation) while the droughts are defined as consecutive negative anomalies less than -1 for longer than 3 months duration. Accordingly, the drought characteristics (duration and severity) and false alarm and hit/miss ratios of LPRM and NOAH datasets are validated using station-based datasets as ground truth. Results showed that although the NOAH soil moisture products have better correlations, LPRM based soil moisture retrievals show better consistency in drought analysis. This project is supported by TUBITAK Project number 114Y676.
Lavado Contador, J F; Maneta, M; Schnabel, S
2006-10-01
The capability of Artificial Neural Network models to forecast near-surface soil moisture at fine spatial scale resolution has been tested for a 99.5 ha watershed located in SW Spain using several easy to achieve digital models of topographic and land cover variables as inputs and a series of soil moisture measurements as training data set. The study methods were designed in order to determining the potentials of the neural network model as a tool to gain insight into soil moisture distribution factors and also in order to optimize the data sampling scheme finding the optimum size of the training data set. Results suggest the efficiency of the methods in forecasting soil moisture, as a tool to assess the optimum number of field samples, and the importance of the variables selected in explaining the final map obtained.
NASA Technical Reports Server (NTRS)
Rose, F. G.
1983-01-01
Modeled temperature data from a one-dimensional, time-dependent, initial value, planetary boundary layer model for 16 separate model runs with varying initial values of moisture availability are applied, by the use of a regression equation, to longwave infrared GOES satellite data to infer moisture availability over a regional area in the central U.S. This was done for several days during the summers of 1978 and 1980 where a large gradient in the antecedent precipitation index (API) represented the boundary between a drought area and a region of near normal precipitation. Correlations between satellite derived moisture availability and API were found to exist. Errors from the presence of clouds, water vapor and other spatial inhomogeneities made the use of the measurement for anything except the relative degree of moisture availability dubious.
NASA Technical Reports Server (NTRS)
Hancock, G. D.; Waite, W. P.
1984-01-01
Two experiments were performed employing swept frequency microwaves for the purpose of investigating the reflectivity from soil volumes containing both discontinuous and continuous changes in subsurface soil moisture content. Discontinuous moisture profiles were artificially created in the laboratory while continuous moisture profiles were induced into the soil of test plots by the environment of an agricultural field. The reflectivity for both the laboratory and field experiments was measured using bi-static reflectometers operated over the frequency ranges of 1.0 to 2.0 GHz and 4.0 to 8.0 GHz. Reflectivity models that considered the discontinuous and continuous moisture profiles within the soil volume were developed and compared with the results of the experiments. This comparison shows good agreement between the smooth surface models and the measurements. In particular the comparison of the smooth surface multi-layer model for continuous moisture profiles and the yield experiment measurements points out the sensitivity of the specular component of the scattered electromagnetic energy to the movement of moisture in the soil.
Toward improving the representation of the water cycle at High Northern Latitudes
NASA Astrophysics Data System (ADS)
Lahoz, William; Svendby, Tove; Hamer, Paul; Blyverket, Jostein; Kristiansen, Jørn; Luijting, Hanneke
2016-04-01
The rapid warming at northern latitude regions in recent decades has resulted in a lengthening of the growing season, greater photosynthetic activity and enhanced carbon sequestration by the ecosystem. These changes are likely to intensify summer droughts, tree mortality and wildfires. A potential major climate change feedback is the release of carbon-bearing compounds from soil thawing. These changes make it important to have information on the land surface (soil moisture and temperature) at high northern latitude regions. The availability of soil moisture measurements from several satellite platforms provides an opportunity to address issues associated with the effects of climate change, e.g., assessing multi-decadal links between increasing temperatures, snow cover, soil moisture variability and vegetation dynamics. The relatively poor information on water cycle parameters for biomes at northern high latitudes make it important that efforts are expended on improving the representation of the water cycle at these latitudes. In a collaboration between NILU and Met Norway, we evaluate the soil moisture observations over Norway from the ESA satellite SMOS (Soil Moisture and Ocean Salinity) using in situ ground based soil moisture measurements, with reference to drought and flood episodes. We will use data assimilation of the quality-controlled SMOS soil moisture observations into a land surface model and a numerical weather prediction model to assess the added value from satellite observations of soil moisture for improving the representation of the water cycle at high northern latitudes. This presentation provides first results from this work. We discuss the evaluation of SMOS soil moisture data (and from other satellites) against ground-based in situ data over Norway; the performance of the SMOS soil moisture data for selected drought and flood conditions over Norway; and the first results from data assimilation experiments with land surface models and numerical weather prediction models. Analyses include information on root zone soil moisture. We provide evidence of the value of satellite soil measurements over Norway, including their fidelity, and their impact at improving the representation of the hydrological cycle over northern high latitudes. We indicate benefits from these results for multi-decadal soil moisture datasets such as that from the ESA CCI for soil moisture.
Modeling Heat and Moisture Transport in Steam-Cured Mortar: Application to Aashto Type Vi Beams.
Hernández-Bautista, E; Sandoval-Torres, S; de J Cano-Barrita, P F; Bentz, D P
2017-10-01
During steam curing of concrete, temperature and moisture gradients are developed, which are difficult to measure experimentally and can adversely affect the durability of concrete. In this research, a model of cement hydration coupled to moisture and heat transport was used to simulate the process of steam curing of mortars with water-to-cement ( w/c ) ratios by mass of 0.30 and 0.45, considering natural convection boundary conditions in mortar and concrete specimens of AASHTO Type VI beams. The primary variables of the model were moisture content, temperature, and degree of hydration. Moisture content profiles of mortar specimens (40 mm in diameter and 50 mm in height) were measured by magnetic resonance imaging. The degree of hydration was obtained by mass-based measurements of loss on ignition to 1000 °C. The results indicate that the model correctly simulates the moisture distribution and degree of hydration in mortar specimens. Application of the model to the steam curing of an AASHTO Type VI beam indicates temperature differences (between the surface and the center) higher than 20 °C during the cooling stage, and internal temperatures higher than 70 °C that may compromise the durability of the concrete.
A simulation study of scene confusion factors in sensing soil moisture from orbital radar
NASA Technical Reports Server (NTRS)
Ulaby, F. T. (Principal Investigator); Dobson, M. C.; Moezzi, S.; Roth, F. T.
1983-01-01
Simulated C-band radar imagery for a 124-km by 108-km test site in eastern Kansas is used to classify soil moisture. Simulated radar resolutions are 100 m by 100 m, 1 km by 1km, and 3 km by 3 km. Distributions of actual near-surface soil moisture are established daily for a 23-day accounting period using a water budget model. Within the 23-day period, three orbital radar overpasses are simulated roughly corresponding to generally moist, wet, and dry soil moisture conditions. The radar simulations are performed by a target/sensor interaction model dependent upon a terrain model, land-use classification, and near-surface soil moisture distribution. The accuracy of soil-moisture classification is evaluated for each single-date radar observation and also for multi-date detection of relative soil moisture change. In general, the results for single-date moisture detection show that 70% to 90% of cropland can be correctly classified to within +/- 20% of the true percent of field capacity. For a given radar resolution, the expected classification accuracy is shown to be dependent upon both the general soil moisture condition and also the geographical distribution of land-use and topographic relief. An analysis of cropland, urban, pasture/rangeland, and woodland subregions within the test site indicates that multi-temporal detection of relative soil moisture change is least sensitive to classification error resulting from scene complexity and topographic effects.
USDA-ARS?s Scientific Manuscript database
Soil moisture plays an integral role in various aspects ranging from multi-scale hydrologic modeling to agricultural decision analysis to multi-scale hydrologic modeling, from climate change assessments to drought prediction and prevention. The broad availability of soil moisture estimates has only...
USDA-ARS?s Scientific Manuscript database
Although there have been efforts to improve existing soil moisture retrieval algorithms, the ability to estimate soil moisture from passive microwave observations is still hampered by problems in accurately modeling the observed microwave signal. This paper focuses on the estimation of effective sur...
Hamzalıoğlu, Aytül; Gökmen, Vural
2018-02-01
In this study, reactions of hydroxymethylfurfural (HMF) with selected amino acids (arginine, cysteine and lysine) were investigated in HMF-amino acid (high moisture) and Coffee-amino acid (low moisture) model systems at 5, 25 and 50°C. The results revealed that HMF reacted efficiently and effectively with amino acids in both high and low moisture model systems. High-resolution mass spectrometry (HRMS) analyses of the reaction mixtures confirmed the formations of Michael adduct and Schiff base of HMF with amino acids. Calculated pseudo-first order reaction rate constants were in the following order; k Cysteine >k Arginine >k Lysine for high moisture model systems. Comparing to these rate constants, the k Cysteine decreased whereas, k Arginine and k Lysine increased under the low moisture conditions of Coffee-amino acid model systems. The temperature dependence of the rate constants was found to obey the Arrhenius law in a temperature range of 5-50°C under both low and high moisture conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.
NASA Technical Reports Server (NTRS)
Paris, J. F.; Arya, L. M.; Davidson, S. A.; Hildreth, W. W.; Richter, J. C.; Rosenkranz, W. A.
1982-01-01
The NASA/JSC ground scatterometer system was used in a row structure and row direction effects experiment to understand these effects on radar remote sensing of soil moisture. Also, a modification of the scatterometer system was begun and is continuing, to allow cross-polarization experiments to be conducted in fiscal years 1982 and 1983. Preprocessing of the 1978 agricultural soil moisture experiment (ASME) data was completed. Preparations for analysis of the ASME data is fiscal year 1982 were completed. A radar image simulation procedure developed by the University of Kansas is being improved. Profile soil moisture model outputs were compared quantitatively for the same soil and climate conditions. A new model was developed and tested to predict the soil moisture characteristic (water tension versus volumetric soil moisture content) from particle-size distribution and bulk density data. Relationships between surface-zone soil moisture, surface flux, and subsurface moisture conditions are being studied as well as the ways in which measured soil moisture (as obtained from remote sensing) can be used for agricultural applications.
The moisture response of soil heterotrophic respiration: Interaction with soil properties.
USDA-ARS?s Scientific Manuscript database
Soil moisture-respiration functions are used to simulate the various mechanisms determining the relations between soil moisture content and carbon mineralization. Soil models used in the simulation of global carbon fluxes often apply simplified functions assumed to represent an average moisture-resp...
Data assimilation to extract soil moisture information from SMAP observations
USDA-ARS?s Scientific Manuscript database
This study compares different methods to extract soil moisture information through the assimilation of Soil Moisture Active Passive (SMAP) observations. Neural Network(NN) and physically-based SMAP soil moisture retrievals were assimilated into the NASA Catchment model over the contiguous United Sta...
Elevated moisture stimulates carbon loss from mineral soils by releasing protected organic matter.
Huang, Wenjuan; Hall, Steven J
2017-11-24
Moisture response functions for soil microbial carbon (C) mineralization remain a critical uncertainty for predicting ecosystem-climate feedbacks. Theory and models posit that C mineralization declines under elevated moisture and associated anaerobic conditions, leading to soil C accumulation. Yet, iron (Fe) reduction potentially releases protected C, providing an under-appreciated mechanism for C destabilization under elevated moisture. Here we incubate Mollisols from ecosystems under C 3 /C 4 plant rotations at moisture levels at and above field capacity over 5 months. Increased moisture and anaerobiosis initially suppress soil C mineralization, consistent with theory. However, after 25 days, elevated moisture stimulates cumulative gaseous C-loss as CO 2 and CH 4 to >150% of the control. Stable C isotopes show that mineralization of older C 3 -derived C released following Fe reduction dominates C losses. Counter to theory, elevated moisture may significantly accelerate C losses from mineral soils over weeks to months-a critical mechanistic deficiency of current Earth system models.
Pu, Yuan-Yuan; Sun, Da-Wen
2015-12-01
Mango slices were dried by microwave-vacuum drying using a domestic microwave oven equipped with a vacuum desiccator inside. Two lab-scale hyperspectral imaging (HSI) systems were employed for moisture prediction. The Page and the Two-term thin-layer drying models were suitable to describe the current drying process with a fitting goodness of R(2)=0.978. Partial least square (PLS) was applied to correlate the mean spectrum of each slice and reference moisture content. With three waveband selection strategies, optimal wavebands corresponding to moisture prediction were identified. The best model RC-PLS-2 (Rp(2)=0.972 and RMSEP=4.611%) was implemented into the moisture visualization procedure. Moisture distribution map clearly showed that the moisture content in the central part of the mango slices was lower than that of other parts. The present study demonstrated that hyperspectral imaging was a useful tool for non-destructively and rapidly measuring and visualizing the moisture content during drying process. Copyright © 2015 Elsevier Ltd. All rights reserved.
Investigation of the Moisture Recycling Ratio over South America: A Modelling Approach using HadCM3
NASA Astrophysics Data System (ADS)
Charan Pattnayak, Kanhu; Gloor, Emanuel; Tindall, Julia; Briener, Roel
2017-04-01
It is a well-known fact that precipitation relies on terrestrial evaporation (moisture recycling). This study makes use of new definitions of moisture recycling from van der Ent, et al. 2010 to study the complete process of continental moisture feedback. Earlier studies have shown that there exist many regions over the globe that relies heavily on recycled moisture as well as that supplies moisture. In South America, the Río de la Plata basin depends on evaporation from the Amazon forest for 70% of its water resources. Stable water isotope (δ18O) can be used, as a good proxy for precipitation and it is a better tool to study convective processes and hydrological cycle. Analysing the δ18O would help to identify the moisture source for precipitation. In this study, we try to explain to the relation between δ18O and the moisture recycling ratio using atmospheric component of Hadley Centre Coupled Climate Model (HadCM3). And also we analyse the impact of land cover change on δ18O and the moisture recycling ratio. Further, we will analyse the changes of moisture recycling pattern from pre-industrial to the present scenario.
Preliminary assessment of soil moisture over vegetation
NASA Technical Reports Server (NTRS)
Carlson, T. N.
1986-01-01
Modeling of surface energy fluxes was combined with in-situ measurement of surface parameters, specifically the surface sensible heat flux and the substrate soil moisture. A vegetation component was incorporated in the atmospheric/substrate model and subsequently showed that fluxes over vegetation can be very much different than those over bare soil for a given surface-air temperature difference. The temperature signatures measured by a satellite or airborne radiometer should be interpreted in conjunction with surface measurements of modeled parameters. Paradoxically, analyses of the large-scale distribution of soil moisture availability shows that there is a very high correlation between antecedent precipitation and inferred surface moisture availability, even when no specific vegetation parameterization is used in the boundary layer model. Preparatory work was begun in streamlining the present boundary layer model, developing better algorithms for relating surface temperatures to substrate moisture, preparing for participation in the French HAPEX experiment, and analyzing aircraft microwave and radiometric surface temperature data for the 1983 French Beauce experiments.
NASA Astrophysics Data System (ADS)
Ťupek, Boris; Launiainen, Samuli; Peltoniemi, Mikko; Heikkinen, Jukka; Lehtonen, Aleksi
2016-04-01
Litter decomposition rates of the most process based soil carbon models affected by environmental conditions are linked with soil heterotrophic CO2 emissions and serve for estimating soil carbon sequestration; thus due to the mass balance equation the variation in measured litter inputs and measured heterotrophic soil CO2 effluxes should indicate soil carbon stock changes, needed by soil carbon management for mitigation of anthropogenic CO2 emissions, if sensitivity functions of the applied model suit to the environmental conditions e.g. soil temperature and moisture. We evaluated the response forms of autotrophic and heterotrophic forest floor respiration to soil temperature and moisture in four boreal forest sites of the International Cooperative Programme on Assessment and Monitoring of Air Pollution Effects on Forests (ICP Forests) by a soil trenching experiment during year 2015 in southern Finland. As expected both autotrophic and heterotrophic forest floor respiration components were primarily controlled by soil temperature and exponential regression models generally explained more than 90% of the variance. Soil moisture regression models on average explained less than 10% of the variance and the response forms varied between Gaussian for the autotrophic forest floor respiration component and linear for the heterotrophic forest floor respiration component. Although the percentage of explained variance of soil heterotrophic respiration by the soil moisture was small, the observed reduction of CO2 emissions with higher moisture levels suggested that soil moisture response of soil carbon models not accounting for the reduction due to excessive moisture should be re-evaluated in order to estimate right levels of soil carbon stock changes. Our further study will include evaluation of process based soil carbon models by the annual heterotrophic respiration and soil carbon stocks.
Why the predictions for monsoon rainfall fail?
NASA Astrophysics Data System (ADS)
Lee, J.
2016-12-01
To be in line with the Global Land/Atmosphere System Study (GLASS) of the Global Energy and Water Cycle Experiment (GEWEX) international research scheme, this study discusses classical arguments about the feedback mechanisms between land surface and precipitation to improve the predictions of African monsoon rainfall. In order to clarify the impact of antecedent soil moisture on subsequent rainfall evolution, several data sets will be presented. First, in-situ soil moisture field measurements acquired by the AMMA field campaign will be shown together with rain gauge data. This data set will validate various model and satellite data sets such as NOAH land surface model, TRMM rainfall, CMORPH rainfall and HadGEM climate models, SMOS soil moisture. To relate soil moisture with precipitation, two approaches are employed: one approach makes a direct comparison between the spatial distributions of soil moisture as an absolute value and rainfall, while the other measures a temporal evolution of the consecutive dry days (i.e. a relative change within the same soil moisture data set over time) and rainfall occurrences. Consecutive dry days shows consistent results of a negative feedback between soil moisture and rainfall across various data sets, contrary to the direct comparison of soil moisture state. This negative mechanism needs attention, as most climate models usually focus on a positive feedback only. The approach of consecutive dry days takes into account the systematic errors in satellite observations, reminding us that it may cause the misinterpretation to directly compare model with satellite data, due to their difference in data retrievals. This finding is significant, as the climate indices employed by the Intergovernmental Panel on Climate Change (IPCC) modelling archive are based on the atmospheric variable rathr than land.
2005-03-01
Reference Strength as a Function of Temperature ........................... Figure 77: Exponent of Reference Strength as a Function of Temperature...relationship in terms of moisture content for the coefficient and/or the exponent in the 104 area fraction of embrittlement equation developed by Morscher...appears in almost all of the terms of Equations 35 and 37 either as a coefficient, an exponent , or both. This variable is a fitting parameter that
Spatio-Temporal Distribution of Bark and Ambrosia Beetles in a Brazilian Tropical Dry Forest
de Novais, Samuel Matos Antunes; Monteiro, Graziela França; Flechtmann, Carlos Alberto Hector; de Faria, Maurício Lopes; Neves, Frederico de Siqueira
2016-01-01
Bark and the ambrosia beetles dig into host plants and live most of their lives in concealed tunnels. We assessed beetle community dynamics in tropical dry forest sites in early, intermediate, and late successional stages, evaluating the influence of resource availability and seasonal variations in guild structure. We collected a total of 763 beetles from 23 species, including 14 bark beetle species, and 9 ambrosia beetle species. Local richness of bark and ambrosia beetles was estimated at 31 species. Bark and ambrosia composition was similar over the successional stages gradient, and beta diversity among sites was primarily determined by species turnover, mainly in the bark beetle community. Bark beetle richness and abundance were higher at intermediate stages; availability of wood was the main spatial mechanism. Climate factors were effectively non-seasonal. Ambrosia beetles were not influenced by successional stages, however the increase in wood resulted in increased abundance. We found higher richness at the end of the dry and wet seasons, and abundance increased with air moisture and decreased with higher temperatures and greater rainfall. In summary, bark beetle species accumulation was higher at sites with better wood production, while the needs of fungi (host and air moisture), resulted in a favorable conditions for species accumulation of ambrosia. The overall biological pattern among guilds differed from tropical rain forests, showing patterns similar to dry forest areas. PMID:27271969
Advances in modeling sorption and diffusion of moisture in porous reactive materials.
Harley, Stephen J; Glascoe, Elizabeth A; Lewicki, James P; Maxwell, Robert S
2014-06-23
Water-vapor-uptake experiments were performed on a silica-filled poly(dimethylsiloxane) (PDMS) network and modeled by using two different approaches. The data was modeled by using established methods and the model parameters were used to predict moisture uptake in a sample. The predictions are reasonably good, but not outstanding; many of the shortcomings of the modeling are discussed. A high-fidelity modeling approach is derived and used to improve the modeling of moisture uptake and diffusion. Our modeling approach captures the physics and kinetics of diffusion and adsorption/desorption, simultaneously. It predicts uptake better than the established method; more importantly, it is also able to predict outgassing. The material used for these studies is a filled-PDMS network; physical interpretations concerning the sorption and diffusion of moisture in this network are discussed. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
William Massman
2015-01-01
Increased use of prescribed fire by land managers and the increasing likelihood of wildfires due to climate change require an improved modeling capability of extreme heating of soils during fires. This issue is addressed here by developing and testing the soil (heat-moisture-vapor) HMVmodel, a 1-D (one-dimensional) non-equilibrium (liquid- vapor phase change)...
Concerning the relationship between evapotranspiration and soil moisture
NASA Technical Reports Server (NTRS)
Wetzel, Peter J.; Chang, Jy-Tai
1987-01-01
The relationship between the evapotranspiration and soil moisture during the drying, supply-limited phase is studied. A second scaling parameter, based on the evapotranspirational supply and demand concept of Federer (1982), is defined; the parameter, referred to as the threshold evapotranspiration, occurs in vegetation-covered surfaces just before leaf stomata close and when surface tension restricts moisture release from bare soil pores. A simple model for evapotranspiration is proposed. The effects of natural soil heterogeneities on evapotranspiration computed from the model are investigated. It is observed that the natural variability in soil moisture, caused by the heterogeneities, alters the relationship between regional evapotranspiration and the area average soil moisture.
Wagner, Wolfgang; Pathe, Carsten; Doubkova, Marcela; Sabel, Daniel; Bartsch, Annett; Hasenauer, Stefan; Blöschl, Günter; Scipal, Klaus; Martínez-Fernández, José; Löw, Alexander
2008-01-01
The high spatio-temporal variability of soil moisture is the result of atmospheric forcing and redistribution processes related to terrain, soil, and vegetation characteristics. Despite this high variability, many field studies have shown that in the temporal domain soil moisture measured at specific locations is correlated to the mean soil moisture content over an area. Since the measurements taken by Synthetic Aperture Radar (SAR) instruments are very sensitive to soil moisture it is hypothesized that the temporally stable soil moisture patterns are reflected in the radar backscatter measurements. To verify this hypothesis 73 Wide Swath (WS) images have been acquired by the ENVISAT Advanced Synthetic Aperture Radar (ASAR) over the REMEDHUS soil moisture network located in the Duero basin, Spain. It is found that a time-invariant linear relationship is well suited for relating local scale (pixel) and regional scale (50 km) backscatter. The observed linear model coefficients can be estimated by considering the scattering properties of the terrain and vegetation and the soil moisture scaling properties. For both linear model coefficients, the relative error between observed and modelled values is less than 5 % and the coefficient of determination (R2) is 86 %. The results are of relevance for interpreting and downscaling coarse resolution soil moisture data retrieved from active (METOP ASCAT) and passive (SMOS, AMSR-E) instruments. PMID:27879759
NASA Astrophysics Data System (ADS)
Baker, I. T.; Prihodko, L.; Vivoni, E. R.; Denning, A. S.
2017-12-01
Arid and semiarid regions represent a large fraction of global land, with attendant importance of surface energy and trace gas flux to global totals. These regions are characterized by strong seasonality, especially in precipitation, that defines the level of ecosystem stress. Individual plants have been observed to respond non-linearly to increasing soil moisture stress, where plant function is generally maintained as soils dry down to a threshold at which rapid closure of stomates occurs. Incorporating this nonlinear mechanism into landscape-scale models can result in unrealistic binary "on-off" behavior that is especially problematic in arid landscapes. Subsequently, models have `relaxed' their simulation of soil moisture stress on evapotranspiration (ET). Unfortunately, these relaxations are not physically based, but are imposed upon model physics as a means to force a more realistic response. Previously, we have introduced a new method to represent soil moisture regulation of ET, whereby the landscape is partitioned into `BINS' of soil moisture wetness, each associated with a fractional area of the landscape or grid cell. A physically- and observationally-based nonlinear soil moisture stress function is applied, but when convolved with the relative area distribution represented by wetness BINS the system has the emergent property of `smoothing' the landscape-scale response without the need for non-physical impositions on model physics. In this research we confront BINS simulations of Bowen ratio, soil moisture variability and trace gas flux with soil moisture and eddy covariance observations taken at the Jornada LTER dryland site in southern New Mexico. We calculate the mean annual wetting cycle and associated variability about the mean state and evaluate model performance against this variability and time series of land surface fluxes from the highly instrumented Tromble Weir watershed. The BINS simulations capture the relatively rapid reaction to wetting events and more prolonged response to drying cycles, as opposed to binary behavior in the control.
Phase Sensitiveness to Soil Moisture in Controlled Anechoic Chamber: Measurements and First Results
NASA Astrophysics Data System (ADS)
Ben Khadhra, K.; Nolan, M.; Hounam, D.; Boerner, T.
2005-12-01
To date many radar methods and models have been reported for the estimation of soil moisture, such as the Oh-model or the Dubois model. Those models, which use only the magnitude of the backscattered signal, show results with 5 to 10 % accuracy. In the last two decades SAR Interferometry (InSAR) and differential InSAR (DInSAR), which uses the phase of the backscattered signal, has been shown to be a useful tool for the creation of Digital Elevation Models (DEMs), and temporal changes due to earthquakes, subsidence, and other ground motions. Nolan (2003) also suggested the possibility to use DINSAR penetration depth as a proxy to estimate the soil moisture. The principal is based on the relationship between the penetration depth and the permittivity, which varies as a function of soil moisture. In this paper we will present new interferometric X-band laboratory measurements, which have been carried out in the Bistatic Measurement Facility at the DLR Oberpfaffenhofen, Microwaves and Radar Institute in Germany. The bistatic geometry enables us to have interferometric pairs with different baseline and different soil moistures controlled by a TDR (Time Domain Reflectivity) system. After calibration of the measuring system using a large metal plate, the sensitivity of phase and reflectivity with regard to moisture variation and therefore the penetration depth was evaluated. The effect of the surface roughness has been also reported. Current results demonstrate a non-linear relationship between the signal phase and the soil moisture, as expected, confirming the possibility of using DInSAR to measure variations in soil moisture.
A mechanistic model for the prediction of in-use moisture uptake by packaged dosage forms.
Remmelgas, Johan; Simonutti, Anne-Laure; Ronkvist, Asa; Gradinarsky, Lubomir; Löfgren, Anders
2013-01-30
A mechanistic model for the prediction of in-use moisture uptake of solid dosage forms in bottles is developed. The model considers moisture transport into the bottle and moisture uptake by the dosage form both when the bottle is closed and when it is open. Experiments are carried out by placing tablets and desiccant canisters in bottles and monitoring their moisture content. Each bottle is opened once a day to remove one tablet or desiccant canister. Opening the bottle to remove a tablet or canister also causes some exchange of air between the bottle headspace and the environment. In order to ascertain how this air exchange might depend on the customer, tablets and desiccant canisters are removed from the bottles by either carefully removing only one or by pouring all of the tablets or desiccant canisters out of the bottle, removing one, and pouring the remaining ones back into the bottle. The predictions of the model are found to be in good agreement with experimental data for moisture sorption by desiccant canisters. Moreover, it is found experimentally that the manner in which the tablets or desiccant canisters were removed does not appreciably affect their moisture content. Copyright © 2012 Elsevier B.V. All rights reserved.
NASA Technical Reports Server (NTRS)
Reichle, Rolf H.; Liu, Qing; Bindlish, Rajat; Cosh, Michael H.; Crow, Wade T.; deJeu, Richard; DeLannoy, Gabrielle J. M.; Huffman, George J.; Jackson, Thomas J.
2011-01-01
The contributions of precipitation and soil moisture observations to the skill of soil moisture estimates from a land data assimilation system are assessed. Relative to baseline estimates from the Modern Era Retrospective-analysis for Research and Applications (MERRA), the study investigates soil moisture skill derived from (i) model forcing corrections based on large-scale, gauge- and satellite-based precipitation observations and (ii) assimilation of surface soil moisture retrievals from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). Soil moisture skill is measured against in situ observations in the continental United States at 44 single-profile sites within the Soil Climate Analysis Network (SCAN) for which skillful AMSR-E retrievals are available and at four CalVal watersheds with high-quality distributed sensor networks that measure soil moisture at the scale of land model and satellite estimates. The average skill (in terms of the anomaly time series correlation coefficient R) of AMSR-E retrievals is R=0.39 versus SCAN and R=0.53 versus CalVal measurements. The skill of MERRA surface and root-zone soil moisture is R=0.42 and R=0.46, respectively, versus SCAN measurements, and MERRA surface moisture skill is R=0.56 versus CalVal measurements. Adding information from either precipitation observations or soil moisture retrievals increases surface soil moisture skill levels by IDDeltaR=0.06-0.08, and root zone soil moisture skill levels by DeltaR=0.05-0.07. Adding information from both sources increases surface soil moisture skill levels by DeltaR=0.13, and root zone soil moisture skill by DeltaR=0.11, demonstrating that precipitation corrections and assimilation of satellite soil moisture retrievals contribute similar and largely independent amounts of information.
NASA Astrophysics Data System (ADS)
McNally, Amy L.
Agricultural drought is characterized by shortages in precipitation, large differences between actual and potential evapotranspiration, and soil water deficits that impact crop growth and pasture productivity. Rainfall and other agrometeorological gauge networks in Sub-Saharan Africa are inadequate for drought early warning systems and hence, satellite-based estimates of rainfall and vegetation greenness provide the main sources of information. While a number of studies have described the empirical relationship between rainfall and vegetation greenness, these studies lack a process based approach that includes soil moisture storage. In Chapters I and II, I modeled soil moisture using satellite rainfall inputs and developed a new method for estimating soil moisture with NDVI calibrated to in situ and microwave soil moisture observations. By transforming both NDVI and rainfall into estimates of soil moisture I was able to easily compare these two datasets in a physically meaningful way. In Chapter II, I also show how the new NDVI derived soil moisture can be assimilated into a water balance model that calculates an index of crop water stress. Compared to the analogous rainfall derived estimates of soil moisture and crop stress the NDVI derived estimates were better correlated with millet yields. In Chapter III, I developed a metric for defining growing season drought events that negatively impact millet yields. This metric is based on the data and models used in the Chapters I and II. I then use this metric to evaluate the ability of a sophisticated land surface model to detect drought events. The analysis showed that this particular land surface model's soil moisture estimates do have the potential to benefit the food security and drought early warning communities. With a focus on soil moisture, this dissertation introduced new methods that utilized a variety of data and models for agricultural drought monitoring applications. These new methods facilitate a more quantitative, transparent `convergence of evidence' approach to identifying agricultural drought events that lead to food insecurity. Ideally, these new methods will contribute to better famine early warning and the timely delivery of food aid to reduce the human suffering caused by drought.
Modelling of Space-Time Soil Moisture in Savannas and its Relation to Vegetation Patterns
NASA Astrophysics Data System (ADS)
Rodriguez-Iturbe, I.; Mohanty, B.; Chen, Z.
2017-12-01
A physically derived space-time representation of the soil moisture field is presented. It includes the incorporation of a "jitter" process acting over the space-time soil moisture field and accounting for the short distance heterogeneities in topography, soil, and vegetation characteristics. The modelling scheme allows for the representation of spatial random fluctuations of soil moisture at small spatial scales and reproduces quite well the space-time correlation structure of soil moisture from a field study in Oklahoma. It is shown that the islands of soil moisture above different thresholds have sizes which follow power distributions over an extended range of scales. A discussion is provided about the possible links of this feature with the observed power law distributions of the clusters of trees in savannas.
NASA Technical Reports Server (NTRS)
Vandegriend, A. A.; Oneill, P. E.
1986-01-01
Using the De Vries models for thermal conductivity and heat capacity, thermal inertia was determined as a function of soil moisture for 12 classes of soil types ranging from sand to clay. A coupled heat and moisture balance model was used to describe the thermal behavior of the top soil, while microwave remote sensing was used to estimate the soil moisture content of the same top soil. Soil hydraulic parameters are found to be very highly correlated with the combination of soil moisture content and thermal inertia at the same moisture content. Therefore, a remotely sensed estimate of the thermal behavior of the soil from diurnal soil temperature observations and an independent remotely sensed estimate of soil moisture content gives the possibility of estimating soil hydraulic properties by remote sensing.
Evaluation of Crops Moisture Provision by Space Remote Sensing Data
NASA Astrophysics Data System (ADS)
Ilienko, Tetiana
2016-08-01
The article is focused on theoretical and experimental rationale for the use of space data to determine the moisture provision of agricultural landscapes and agricultural plants. The improvement of space remote sensing methods to evaluate plant moisture availability is the aim of this research.It was proved the possibility of replacement of satellite imagery of high spatial resolution on medium spatial resolution which are freely available to determine crop moisture content at the local level. The mathematical models to determine the moisture content of winter wheat plants by spectral indices were developed based on the results of experimental field research and satellite (Landsat, MODIS/Terra, RapidEye, SICH-2) data. The maps of the moisture content in winter wheat plants in test sites by obtained models were constructed using modern GIS technology.
The COsmic-ray Soil Moisture Interaction Code (COSMIC) for use in data assimilation
NASA Astrophysics Data System (ADS)
Shuttleworth, J.; Rosolem, R.; Zreda, M.; Franz, T.
2013-08-01
Soil moisture status in land surface models (LSMs) can be updated by assimilating cosmic-ray neutron intensity measured in air above the surface. This requires a fast and accurate model to calculate the neutron intensity from the profiles of soil moisture modeled by the LSM. The existing Monte Carlo N-Particle eXtended (MCNPX) model is sufficiently accurate but too slow to be practical in the context of data assimilation. Consequently an alternative and efficient model is needed which can be calibrated accurately to reproduce the calculations made by MCNPX and used to substitute for MCNPX during data assimilation. This paper describes the construction and calibration of such a model, COsmic-ray Soil Moisture Interaction Code (COSMIC), which is simple, physically based and analytic, and which, because it runs at least 50 000 times faster than MCNPX, is appropriate in data assimilation applications. The model includes simple descriptions of (a) degradation of the incoming high-energy neutron flux with soil depth, (b) creation of fast neutrons at each depth in the soil, and (c) scattering of the resulting fast neutrons before they reach the soil surface, all of which processes may have parameterized dependency on the chemistry and moisture content of the soil. The site-to-site variability in the parameters used in COSMIC is explored for 42 sample sites in the COsmic-ray Soil Moisture Observing System (COSMOS), and the comparative performance of COSMIC relative to MCNPX when applied to represent interactions between cosmic-ray neutrons and moist soil is explored. At an example site in Arizona, fast-neutron counts calculated by COSMIC from the average soil moisture profile given by an independent network of point measurements in the COSMOS probe footprint are similar to the fast-neutron intensity measured by the COSMOS probe. It was demonstrated that, when used within a data assimilation framework to assimilate COSMOS probe counts into the Noah land surface model at the Santa Rita Experimental Range field site, the calibrated COSMIC model provided an effective mechanism for translating model-calculated soil moisture profiles into aboveground fast-neutron count when applied with two radically different approaches used to remove the bias between data and model.
Investigation of remote sensing techniques of measuring soil moisture
NASA Technical Reports Server (NTRS)
Newton, R. W. (Principal Investigator); Blanchard, A. J.; Nieber, J. L.; Lascano, R.; Tsang, L.; Vanbavel, C. H. M.
1981-01-01
Major activities described include development and evaluation of theoretical models that describe both active and passive microwave sensing of soil moisture, the evaluation of these models for their applicability, the execution of a controlled field experiment during which passive microwave measurements were acquired to validate these models, and evaluation of previously acquired aircraft microwave measurements. The development of a root zone soil water and soil temperature profile model and the calibration and evaluation of gamma ray attenuation probes for measuring soil moisture profiles are considered. The analysis of spatial variability of soil information as related to remote sensing is discussed as well as the implementation of an instrumented field site for acquisition of soil moisture and meteorologic information for use in validating the soil water profile and soil temperature profile models.
NASA Astrophysics Data System (ADS)
Rajesh, P. V.; Pattnaik, S.; Mohanty, U. C.; Rai, D.; Baisya, H.; Pandey, P. C.
2017-12-01
Monsoon depressions (MDs) constitute a large fraction of the total rainfall during the Indian summer monsoon season. In this study, the impact of high-resolution land state is addressed by assessing the evolution of inland moving depressions formed over the Bay of Bengal using a mesoscale modeling system. Improved land state is generated using High Resolution Land Data Assimilation System employing Noah-MP land-surface model. Verification of soil moisture using Soil Moisture and Ocean Salinity (SMOS) and soil temperature using tower observations demonstrate promising results. Incorporating high-resolution land state yielded least root mean squared errors with higher correlation coefficient in the surface and mid tropospheric parameters. Rainfall forecasts reveal that simulations are spatially and quantitatively in accordance with observations and provide better skill scores. The improved land surface characteristics have brought about the realistic evolution of surface, mid-tropospheric parameters, vorticity and moist static energy that facilitates the accurate MDs dynamics in the model. Composite moisture budget analysis reveals that the surface evaporation is negligible compared to moisture flux convergence of water vapor, which supplies moisture into the MDs over land. The temporal relationship between rainfall and moisture convergence show high correlation, suggesting a realistic representation of land state help restructure the moisture inflow into the system through rainfall-moisture convergence feedback.
NASA Technical Reports Server (NTRS)
Spar, J.; Cohen, C.
1981-01-01
The effects of terrain elevation, soil moisture, and zonal variations in sea/surface temperature on the mean daily precipitation rates over Australia, Africa, and South America in January were evaluated. It is suggested that evaporation of soil moisture may either increase or decrease the model generated precipitation, depending on the surface albedo. It was found that a flat, dry continent model best simulates the January rainfall over Australia and South America, while over Africa the simulation is improved by the inclusion of surface physics, specifically soil moisture and albedo variations.
Automatic pattern identification of rock moisture based on the Staff-RF model
NASA Astrophysics Data System (ADS)
Zheng, Wei; Tao, Kai; Jiang, Wei
2018-04-01
Studies on the moisture and damage state of rocks generally focus on the qualitative description and mechanical information of rocks. This method is not applicable to the real-time safety monitoring of rock mass. In this study, a musical staff computing model is used to quantify the acoustic emission signals of rocks with different moisture patterns. Then, the random forest (RF) method is adopted to form the staff-RF model for the real-time pattern identification of rock moisture. The entire process requires only the computing information of the AE signal and does not require the mechanical conditions of rocks.
NASA Astrophysics Data System (ADS)
Tawfik, Ahmed B.
The atmospheric component is described by rapid fluctuations in typical state variables, such as temperature and water vapor, on timescales of hours to days and the land component evolves on daily to yearly timescales. This dissertation examines the connection between soil moisture and atmospheric tracers under varying degrees of soil moisture-atmosphere coupling. Land-atmosphere coupling is defined over the United States using a regional climate model. A newly examined soil moisture-precipitation feedback is identified for winter months extending the previous summer feedback to colder temperature climates. This feedback is driven by the freezing and thawing of soil moisture, leading to coupled land-atmosphere conditions near the freezing line. Soil moisture can also affect the composition of the troposphere through modifying biogenic emissions of isoprene (C5H8). A novel first-order Taylor series decomposition indicates that isoprene emissions are jointly driven by temperature and soil moisture in models. These compounds are important precursors for ozone formation, an air pollutant and a short-lived forcing agent for climate. A mechanistic description of commonly observed relationships between ground-level ozone and meteorology is presented using the concept of soil moisture-temperature coupling regimes. The extent of surface drying was found to be a better predictor of ozone concentrations than temperature or humidity for the Eastern U.S. This relationship is evaluated in a coupled regional chemistry-climate model under several land-atmosphere coupling and isoprene emissions cases. The coupled chemistry-climate model can reproduce the observed soil moisture-temperature coupling pattern, yet modeled ozone is insensitive to changes in meteorology due to the balance between isoprene and the primary atmospheric oxidant, the hydroxyl radical (OH). Overall, this work highlights the importance of soil moisture-atmosphere coupling for previously neglected cold climate regimes, controlling isoprene emissions variability, and providing a processed-based description of observed ozone-meteorology relationships. From the perspective of ozone air quality, the lack of sensitivity of ozone to meteorology suggests a systematic deficiency in chemistry models in high isoprene emission regions. This shortcoming must be addressed to better estimate tropospheric ozone radiative forcing and to understanding how ozone air quality may respond to future warming.
NASA Astrophysics Data System (ADS)
Mishra, V.; Cruise, J.; Mecikalski, J. R.
2012-12-01
Soil Moisture is a key component in the hydrological process, affects surface and boundary layer energy fluxes and is the driving factor in agricultural production. Multiple in situ soil moisture measuring instruments such as Time-domain Reflectrometry (TDR), Nuclear Probes etc. are in use along with remote sensing methods like Active and Passive Microwave (PM) sensors. In situ measurements, despite being more accurate, can only be obtained at discrete points over small spatial scales. Remote sensing estimates, on the other hand, can be obtained over larger spatial domains with varying spatial and temporal resolutions. Soil moisture profiles derived from satellite based thermal infrared (TIR) imagery can overcome many of the problems associated with laborious in-situ observations over large spatial domains. An area where soil moisture observation and assimilation is receiving increasing attention is agricultural crop modeling. This study revolves around the use of the Decision Support System for Agrotechnology Transfer (DSSAT) crop model to simulate corn yields under various forcing scenarios. First, the model was run and calibrated using observed precipitation and model generated soil moisture dynamics. Next, the modeled soil moisture was updated using estimates derived from satellite based TIR imagery and the Atmospheric Land Exchange Inverse (ALEXI) model. We selected three climatically different locations to test the concept. Test Locations were selected to represent varied climatology. Bell Mina, Alabama - South Eastern United States, representing humid subtropical climate. Nabb, Indiana - Mid Western United States, representing humid continental climate. Lubbok, Texas - Southern United States, representing semiarid steppe climate. A temporal (2000-2009) correlation analysis of the soil moisture values from both DSSAT and ALEXI were performed and validated against the Land Information System (LIS) soil moisture dataset. The results clearly show strong correlation (R = 73%) between ALEXI and DSSAT at Bell Mina. At Nabb and Lubbock the correlation was 50-60%. Further, multiple experiments were conducted for each location: a) a DSSAT rain-fed 10 year sequential run forced with daymet precipitation; b) a DSSAT sequential run with no precipitation data; and c) a DSSAT run forced with ALEXI soil moisture estimates alone. The preliminary results of all the experiments are quantified through soil moisture correlations and yield comparisons. In general, the preliminary results strongly suggest that DSSAT forced with ALEXI can provide significant information especially at locations where no significant precipitation data exists.
USDA-ARS?s Scientific Manuscript database
Soil moisture measurements are required to improve our understanding of hydrological processes, ecosystem functions, and linkages between the Earth’s water, energy, and carbon cycles. The efficient retrieval of soil moisture depends on various factors in which soil dielectric mixing models are consi...
Estimating error cross-correlations in soil moisture data sets using extended collocation analysis
USDA-ARS?s Scientific Manuscript database
Consistent global soil moisture records are essential for studying the role of hydrologic processes within the larger earth system. Various studies have shown the benefit of assimilating satellite-based soil moisture data into water balance models or merging multi-source soil moisture retrievals int...
Applicability of common stomatal conductance models in maize under varying soil moisture conditions.
Wang, Qiuling; He, Qijin; Zhou, Guangsheng
2018-07-01
In the context of climate warming, the varying soil moisture caused by precipitation pattern change will affect the applicability of stomatal conductance models, thereby affecting the simulation accuracy of carbon-nitrogen-water cycles in ecosystems. We studied the applicability of four common stomatal conductance models including Jarvis, Ball-Woodrow-Berry (BWB), Ball-Berry-Leuning (BBL) and unified stomatal optimization (USO) models based on summer maize leaf gas exchange data from a soil moisture consecutive decrease manipulation experiment. The results showed that the USO model performed best, followed by the BBL model, BWB model, and the Jarvis model performed worst under varying soil moisture conditions. The effects of soil moisture made a difference in the relative performance among the models. By introducing a water response function, the performance of the Jarvis, BWB, and USO models improved, which decreased the normalized root mean square error (NRMSE) by 15.7%, 16.6% and 3.9%, respectively; however, the performance of the BBL model was negative, which increased the NRMSE by 5.3%. It was observed that the models of Jarvis, BWB, BBL and USO were applicable within different ranges of soil relative water content (i.e., 55%-65%, 56%-67%, 37%-79% and 37%-95%, respectively) based on the 95% confidence limits. Moreover, introducing a water response function, the applicability of the Jarvis and BWB models improved. The USO model performed best with or without introducing the water response function and was applicable under varying soil moisture conditions. Our results provide a basis for selecting appropriate stomatal conductance models under drought conditions. Copyright © 2018 Elsevier B.V. All rights reserved.
Lorenz, Ruth; Argueso, Daniel; Donat, Markus G.; Pitman, Andrew J.; van den Hurk, Bart; Berg, Alexis; Lawrence, David M.; Cheruy, Frederique; Ducharne, Agnes; Hagemann, Stefan; Meier, Arndt; Milly, Paul C.D.; Seneviratne, Sonia I
2016-01-01
We examine how soil moisture variability and trends affect the simulation of temperature and precipitation extremes in six global climate models using the experimental protocol of the Global Land-Atmosphere Coupling Experiment of the Coupled Model Intercomparison Project, Phase 5 (GLACE-CMIP5). This protocol enables separate examinations of the influences of soil moisture variability and trends on the intensity, frequency, and duration of climate extremes by the end of the 21st century under a business-as-usual (Representative Concentration Pathway 8.5) emission scenario. Removing soil moisture variability significantly reduces temperature extremes over most continental surfaces, while wet precipitation extremes are enhanced in the tropics. Projected drying trends in soil moisture lead to increases in intensity, frequency, and duration of temperature extremes by the end of the 21st century. Wet precipitation extremes are decreased in the tropics with soil moisture trends in the simulations, while dry extremes are enhanced in some regions, in particular the Mediterranean and Australia. However, the ensemble results mask considerable differences in the soil moisture trends simulated by the six climate models. We find that the large differences between the models in soil moisture trends, which are related to an unknown combination of differences in atmospheric forcing (precipitation, net radiation), flux partitioning at the land surface, and how soil moisture is parameterized, imply considerable uncertainty in future changes in climate extremes.
Rong, Yaoguang; Hou, Xiaomeng; Hu, Yue; Mei, Anyi; Liu, Linfeng; Wang, Ping; Han, Hongwei
2017-01-01
Organometal lead halide perovskites have been widely used as the light harvester for high-performance solar cells. However, typical perovskites of methylammonium lead halides (CH3NH3PbX3, X=Cl, Br, I) are usually sensitive to moisture in ambient air, and thus require an inert atmosphere to process. Here we demonstrate a moisture-induced transformation of perovskite crystals in a triple-layer scaffold of TiO2/ZrO2/Carbon to fabricate printable mesoscopic solar cells. An additive of ammonium chloride (NH4Cl) is employed to assist the crystallization of perovskite, wherein the formation and transition of intermediate CH3NH3X·NH4PbX3(H2O)2 (X=I or Cl) enables high-quality perovskite CH3NH3PbI3 crystals with preferential growth orientation. Correspondingly, the intrinsic perovskite devices based on CH3NH3PbI3 achieve an efficiency of 15.6% and a lifetime of over 130 days in ambient condition with 30% relative humidity. This ambient-processed printable perovskite solar cell provides a promising prospect for mass production, and will promote the development of perovskite-based photovoltaics. PMID:28240286
Qiu, Jinya Jack; Westerdahl, Becky B; Pryor, Alan
2009-09-01
Ozone gas (O₃) is a reactive oxidizing agent with biocidal properties. Because of the current phasing out of methyl bromide, investigations on the use of ozone gas as a soil-fumigant were conducted. Ozone gas was produced at a concentration of 1% in air by a conventional electrical discharge O₃ generator. Two O₃ dosages and three gas flow rates were tested on a sandy loam soil collected from a tomato field that had a resident population of root knot nematodes, Meloidogyne javanica. At dosages equivalent to 50 and 250 kg of O₃/ha, M. javanica were reduced by 24% and 68%, and free-living nematodes by 19% and 52%, respectively. The reduction for both M. javanica and free-living nematodes was dosage dependent and flow rate independent. The rates of O₃ mass transfer (OMT) through three soils of different texture were greater at low and high moisture levels than at intermediate ones. At any one soil moisture level, the OMT rate varied with soil texture and soil organic matter content. Results suggest that soil texture, moisture, and organic matter content should be considered in determining O₃ dosage needed for effective nematode control.
NASA Astrophysics Data System (ADS)
Swenson, S. C.; Lawrence, D. M.
2017-12-01
Partitioning the vertically integrated water storage variations estimated from GRACE satellite data into the components of which it is comprised requires independent information. Land surface models, which simulate the transfer and storage of moisture and energy at the land surface, are often used to estimate water storage variability of snow, surface water, and soil moisture. To obtain an estimate of changes in groundwater, the estimates of these storage components are removed from GRACE data. Biases in the modeled water storage components are therefore present in the residual groundwater estimate. In this study, we examine how soil moisture variability, estimated using the Community Land Model (CLM), depends on the vertical structure of the model. We then explore the implications of this uncertainty in the context of estimating groundwater variations using GRACE data.
NASA Astrophysics Data System (ADS)
Flores, Alejandro N.; Bras, Rafael L.; Entekhabi, Dara
2012-08-01
Soil moisture information is critical for applications like landslide susceptibility analysis and military trafficability assessment. Existing technologies cannot observe soil moisture at spatial scales of hillslopes (e.g., 100 to 102 m) and over large areas (e.g., 102 to 105 km2) with sufficiently high temporal coverage (e.g., days). Physics-based hydrologic models can simulate soil moisture at the necessary spatial and temporal scales, albeit with error. We develop and test a data assimilation framework based on the ensemble Kalman filter for constraining uncertain simulated high-resolution soil moisture fields to anticipated remote sensing products, specifically NASA's Soil Moisture Active-Passive (SMAP) mission, which will provide global L band microwave observation approximately every 2-3 days. The framework directly assimilates SMAP synthetic 3 km radar backscatter observations to update hillslope-scale bare soil moisture estimates from a physics-based model. Downscaling from 3 km observations to hillslope scales is achieved through the data assimilation algorithm. Assimilation reduces bias in near-surface soil moisture (e.g., top 10 cm) by approximately 0.05 m3/m3and expected root-mean-square errors by at least 60% in much of the watershed, relative to an open loop simulation. However, near-surface moisture estimates in channel and valley bottoms do not improve, and estimates of profile-integrated moisture throughout the watershed do not substantially improve. We discuss the implications of this work, focusing on ongoing efforts to improve soil moisture estimation in the entire soil profile through joint assimilation of other satellite (e.g., vegetation) and in situ soil moisture measurements.
Land surface dynamics monitoring using microwave passive satellite sensors
NASA Astrophysics Data System (ADS)
Guijarro, Lizbeth Noemi
Soil moisture, surface temperature and vegetation are variables that play an important role in our environment. There is growing demand for accurate estimation of these geophysical parameters for the research of global climate models (GCMs), weather, hydrological and flooding models, and for the application to agricultural assessment, land cover change, and a wide variety of other uses that meet the needs for the study of our environment. The different studies covered in this dissertation evaluate the capabilities and limitations of microwave passive sensors to monitor land surface dynamics. The first study evaluates the 19 GHz channel of the SSM/I instrument with a radiative transfer model and in situ datasets from the Illinois stations and the Oklahoma Mesonet to retrieve land surface temperature and surface soil moisture. The surface temperatures were retrieved with an average error of 5 K and the soil moisture with an average error of 6%. The results show that the 19 GHz channel can be used to qualitatively predict the spatial and temporal variability of surface soil moisture and surface temperature at regional scales. In the second study, in situ observations were compared with sensor observations to evaluate aspects of low and high spatial resolution at multiple frequencies with data collected from the Southern Great Plains Experiment (SGP99). The results showed that the sensitivity to soil moisture at each frequency is a function of wavelength and amount of vegetation. The results confirmed that L-band is more optimal for soil moisture, but each sensor can provide soil moisture information if the vegetation water content is low. The spatial variability of the emissivities reveals that resolution suffers considerably at higher frequencies. The third study evaluates C- and X-bands of the AMSR-E instrument. In situ datasets from the Soil Moisture Experiments (SMEX03) in South Central Georgia were utilized to validate the AMSR-E soil moisture product and to derive surface soil moisture with a radiative transfer model. The soil moisture was retrieved with an average error of 2.7% at X-band and 6.7% at C-band. The AMSR-E demonstrated its ability to successfully infer soil moisture during the SMEX03 experiment.
NASA Technical Reports Server (NTRS)
Hollahan, J. R.; Wydeven, T.
1975-01-01
The need for protective coatings on critical optical surfaces, such as halide crystal windows or lenses used in spectroscopy, has long been recognized. It has been demonstrated that thin, one micron, organic coatings produced by polymerization of flourinated monomers in low temperature gas discharge (plasma) exhibit very high degrees of moisture resistence, e.g., hundreds of hours protection for cesium iodide vs. minutes before degradation sets in for untreated surfaces. The index of refraction of these coatings is intermediate between that of the halide substrate and air, a condition for anti-reflection, another desirable property of optical coatings. Thus, the organic coatings not only offer protection, but improved transmittance as well. The polymer coating is non-absorbing over the range 0.4 to 40 microns with an exception at 8.0 microns, the expected absorption for C-F bonds.
NASA Astrophysics Data System (ADS)
Yoshida, N.; Oki, T.
2016-12-01
Appropriate initial condition of soil moisture and water table depth are important factors to reduce uncertainty in hydrological simulations. Approaches to determine the initial water table depth have been developed because of difficulty to get information on global water table depth and soil moisture distributions. However, how is equilibrium soil moisture determined by climate conditions? We try to discuss this issue by using land surface model with representation of water table dynamics (MAT-GW). First, the global pattern of water table depth at equilibrium soil moisture in MAT-GW was verified. The water table depth in MAT-GW was deeper than the previous one at fundamentally arid region because the negative recharge and continuous baseflow made water table depth deeper. It indicated that the hydraulic conductivity used for estimating recharge and baseflow need to be reassessed in MAT-GW. In soil physics field, it is revealed that proper hydraulic property models for water retention and unsaturated hydraulic conductivity should be selected for each soil type. So, the effect of selecting hydraulic property models on terrestrial soil moisture and water table depth were examined.Clapp and Hornburger equation(CH eq.) and Van Genuchten equation(VG eq.) were used as representative hydraulic property models. Those models were integrated on MAT-GW and equilibrium soil moisture and water table depth with using each model were compared. The water table depth and soil moisture at grids which reached equilibrium in both simulations were analyzed. The equilibrium water table depth were deeper in VG eq. than CH eq. in most grids due to shape of hydraulic property models. Then, total soil moisture were smaller in VG eq. than CH eq. at almost all grids which water table depth reached equilibrium. It is interesting that spatial patterns which water table depth reached equilibrium or not were basically similar in both simulations but reverse patterns were shown in east and west part of America. Selection of each hydraulic property model based on soil types may compensate characteristic of models in initialization.
NASA Technical Reports Server (NTRS)
Crosson, William L.; Laymon, Charles A.; Inguva, Ramarao; Schamschula, Marius; Caulfield, John
1998-01-01
Knowledge of the amount of water in the soil is of great importance to many earth science disciplines. Soil moisture is a key variable in controlling the exchange of water and energy between the land surface and the atmosphere. Thus, soil moisture information is valuable in a wide range of applications including weather and climate, runoff potential and flood control, early warning of droughts, irrigation, crop yield forecasting, soil erosion, reservoir management, geotechnical engineering, and water quality. Despite the importance of soil moisture information, widespread and continuous measurements of soil moisture are not possible today. Although many earth surface conditions can be measured from satellites, we still cannot adequately measure soil moisture from space. Research in soil moisture remote sensing began in the mid 1970s shortly after the surge in satellite development. Recent advances in remote sensing have shown that soil moisture can be measured, at least qualitatively, by several methods. Quantitative measurements of moisture in the soil surface layer have been most successful using both passive and active microwave remote sensing, although complications arise from surface roughness and vegetation type and density. Early attempts to measure soil moisture from space-borne microwave instruments were hindered by what is now considered sub-optimal wavelengths (shorter than 5 cm) and the coarse spatial resolution of the measurements. L-band frequencies between 1 and 3 GHz (10-30 cm) have been deemed optimal for detection of soil moisture in the upper few centimeters of soil. The Electronically Steered Thinned Array Radiometer (ESTAR), an aircraft-based instrument operating a 1,4 GHz, has shown great promise for soil moisture determination. Initiatives are underway to develop a similar instrument for space. Existing space-borne synthetic aperture radars (SARS) operating at C- and L-band have also shown some potential to detect surface wetness. The advantage of radar is its much higher resolution than passive microwave systems, but it is currently hampered by surface roughness effects and the lack of a good algorithm based on a single frequency and single polarization. In addition, its repeat frequency is generally low (about 40 days). In the meantime, two new radiometers offer some hope for remote sensing of soil moisture from space. The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), launched in November 1997, possesses a 10.65 GHz channel and the Advanced Microwave Scanning Radiometer (AMSR) on both the ADEOS-11 and Earth Observing System AM-1 platforms to be launched in 1999 possesses a 6.9 GHz channel. Aside from issues about interference from vegetation, the coarse resolution of these data will provide considerable challenges pertaining to their application. The resolution of TMI is about 45 km and that of AMSR is about 70 km. These resolutions are grossly inconsistent with the scale of soil moisture processes and the spatial variability of factors that control soil moisture. Scale disparities such as these are forcing us to rethink how we assimilate data of various scales in hydrologic models. Of particular interest is how to assimilate soil moisture data by reconciling the scale disparity between what we can expect from present and future remote sensing measurements of soil moisture and modeling soil moisture processes. It is because of this disparity between the resolution of space-based sensors and the scale of data needed for capturing the spatial variability of soil moisture and related properties that remote sensing of soil moisture has not met with more widespread success. Within a single footprint of current sensors at the wavelengths optimal for this application, in most cases there is enormous heterogeneity in soil moisture created by differences in landcover, soils and topography, as well as variability in antecedent precipitation. It is difficult to interpret the meaning of 'mean' soil moisture under such conditions and even more difficult to apply such a value. Because of the non-linear relationships between near-surface soil moisture and other variables of interest, such as surface energy fluxes and runoff, mean soil moisture has little applicability at such large scales. It is for these reasons that the use of remote sensing in conjunction with a hydrologic model appears to be of benefit in capturing the complete spatial and temporal structure of soil moisture. This paper is Part I of a four-part series describing a method for intermittently assimilating remotely-sensed soil moisture information to improve performance of a distributed land surface hydrology model. The method, summarized in section II, involves the following components, each of which is detailed in the indicated section of the paper or subsequent papers in this series: Forward radiative transfer model methods (section II and Part IV); Use of a Kalman filter to assimilate remotely-sensed soil moisture estimates with the model profile (section II and Part IV); Application of a soil hydrology model to capture the continuous evolution of the soil moisture profile within and below the root zone (section III); Statistical aggregation techniques (section IV and Part II); Disaggregation techniques using a neural network approach (section IV and Part III); and Maximum likelihood and Bayesian algorithms for inversely solving for the soil moisture profile in the upper few cm (Part IV).
NASA Astrophysics Data System (ADS)
Mishra, V.; Cruise, J.; Mecikalski, J. R.
2017-12-01
Much effort has been expended recently on the assimilation of remotely sensed soil moisture into operational land surface models (LSM). These efforts have normally been focused on the use of data derived from the microwave bands and results have often shown that improvements to model simulations have been limited due to the fact that microwave signals only penetrate the top 2-5 cm of the soil surface. It is possible that model simulations could be further improved through the introduction of geostationary satellite thermal infrared (TIR) based root zone soil moisture in addition to the microwave deduced surface estimates. In this study, root zone soil moisture estimates from the TIR based Atmospheric Land Exchange Inverse (ALEXI) model were merged with NASA Soil Moisture Active Passive (SMAP) based surface estimates through the application of informational entropy. Entropy can be used to characterize the movement of moisture within the vadose zone and accounts for both advection and diffusion processes. The Principle of Maximum Entropy (POME) can be used to derive complete soil moisture profiles and, fortuitously, only requires a surface boundary condition as well as the overall mean moisture content of the soil column. A lower boundary can be considered a soil parameter or obtained from the LSM itself. In this study, SMAP provided the surface boundary while ALEXI supplied the mean and the entropy integral was used to tie the two together and produce the vertical profile. However, prior to the merging, the coarse resolution (9 km) SMAP data were downscaled to the finer resolution (4.7 km) ALEXI grid. The disaggregation scheme followed the Soil Evaporative Efficiency approach and again, all necessary inputs were available from the TIR model. The profiles were then assimilated into a standard agricultural crop model (Decision Support System for Agrotechnology, DSSAT) via the ensemble Kalman Filter. The study was conducted over the Southeastern United States for the growing seasons from 2015-2017. Soil moisture profiles compared favorably to in situ data and simulated crop yields compared well with observed yields.
Remote Sensing of Soil Moisture: A Comparison of Optical and Thermal Methods
NASA Astrophysics Data System (ADS)
Foroughi, H.; Naseri, A. A.; Boroomandnasab, S.; Sadeghi, M.; Jones, S. B.; Tuller, M.; Babaeian, E.
2017-12-01
Recent technological advances in satellite and airborne remote sensing have provided new means for large-scale soil moisture monitoring. Traditional methods for soil moisture retrieval require thermal and optical RS observations. In this study we compared the traditional trapezoid model parameterized based on the land surface temperature - normalized difference vegetation index (LST-NDVI) space with the recently developed optical trapezoid model OPTRAM parameterized based on the shortwave infrared transformed reflectance (STR)-NDVI space for an extensive sugarcane field located in Southwestern Iran. Twelve Landsat-8 satellite images were acquired during the sugarcane growth season (April to October 2016). Reference in situ soil moisture data were obtained at 22 locations at different depths via core sampling and oven-drying. The obtained results indicate that the thermal/optical and optical prediction methods are comparable, both with volumetric moisture content estimation errors of about 0.04 cm3 cm-3. However, the OPTRAM model is more efficient because it does not require thermal data and can be universally parameterized for a specific location, because unlike the LST-soil moisture relationship, the reflectance-soil moisture relationship does not significantly vary with environmental variables (e.g., air temperature, wind speed, etc.).
NASA Technical Reports Server (NTRS)
Koster, Randal D.; Mahanama, P. P.
2012-01-01
Key to translating soil moisture memory into subseasonal precipitation and air temperature forecast skill is a realistic treatment of evaporation in the forecast system used - in particular, a realistic treatment of how evaporation responds to variations in soil moisture. The inherent soil moisture-evaporation relationships used in today's land surface models (LSMs), however, arguably reflect little more than guesswork given the lack of evaporation and soil moisture data at the spatial scales represented by regional and global models. Here we present a new approach for evaluating this critical aspect of LSMs. Seasonally averaged precipitation is used as a proxy for seasonally-averaged soil moisture, and seasonally-averaged air temperature is used as a proxy for seasonally-averaged evaporation (e.g., more evaporative cooling leads to cooler temperatures) the relationship between historical precipitation and temperature measurements accordingly mimics in certain important ways nature's relationship between soil moisture and evaporation. Additional information on the relationship is gleaned from joint analysis of precipitation and streamflow measurements. An experimental framework that utilizes these ideas to guide the development of an improved soil moisture-evaporation relationship is described and demonstrated.
Towards soil property retrieval from space: Proof of concept using in situ observations
NASA Astrophysics Data System (ADS)
Bandara, Ranmalee; Walker, Jeffrey P.; Rüdiger, Christoph
2014-05-01
Soil moisture is a key variable that controls the exchange of water and energy fluxes between the land surface and the atmosphere. However, the temporal evolution of soil moisture is neither easy to measure nor monitor at large scales because of its high spatial variability. This is mainly a result of the local variation in soil properties and vegetation cover. Thus, land surface models are normally used to predict the evolution of soil moisture and yet, despite their importance, these models are based on low-resolution soil property information or typical values. Therefore, the availability of more accurate and detailed soil parameter data than are currently available is vital, if regional or global soil moisture predictions are to be made with the accuracy required for environmental applications. The proposed solution is to estimate the soil hydraulic properties via model calibration to remotely sensed soil moisture observation, with in situ observations used as a proxy in this proof of concept study. Consequently, the feasibility is assessed, and the level of accuracy that can be expected determined, for soil hydraulic property estimation of duplex soil profiles in a semi-arid environment using near-surface soil moisture observations under naturally occurring conditions. The retrieved soil hydraulic parameters were then assessed by their reliability to predict the root zone soil moisture using the Joint UK Land Environment Simulator model. When using parameters that were retrieved using soil moisture observations, the root zone soil moisture was predicted to within an accuracy of 0.04 m3/m3, which is an improvement of ∼0.025 m3/m3 on predictions that used published values or pedo-transfer functions.
Impact of the assimilation of satellite soil moisture and LST on the hydrological cycle
NASA Astrophysics Data System (ADS)
Laiolo, Paola; Gabellani, Simone; Delogu, Fabio; Silvestro, Francesco; Rudari, Roberto; Campo, Lorenzo; Boni, Giorgio
2014-05-01
The reliable estimation of hydrological variables (e.g. soil moisture, evapotranspiration, surface temperature) in space and time is of fundamental importance in operational hydrology to improve the forecast of the rainfall-runoff response of catchments and, consequently, flood predictions. Nowadays remote sensing can offer a chance to provide good space-time estimates of several hydrological variables and then improve hydrological model performances especially in environments with scarce ground based data. The aim of this work is to investigate the impacts on the performances of a distributed hydrological model (Continuum) of the assimilation of satellite-derived soil moisture products and Land Surface (LST). In this work three different soil moisture (SM) products, derived by ASCAT sensor, are used. These data are provided by the EUMETSAT's H-SAF (Satellite Application Facility on Support to Operational Hydrology and Water Management) program. The considered soil moisture products are: large scale surface soil moisture (SM OBS 1 - H07), small scale surface soil moisture (SM OBS 2 - H08) and profile index in the roots region (SM DAS 2 - H14). These data are compared with soil moisture estimated by Continuum model on the Orba catchment (800 km2), in the northern part of Italy, for the period July 2012-June 2013. Different assimilation experiments have been performed. The first experiment consists in the assimilation of the SM products by using a simple Nudging technique; the second one is the assimilation of only LST data, derived from MSG satellite, and the third is the assimilation of both SM products and LST. The benefits on the model predictions of discharge, LST and soil moisture dynamics were tested.
NASA Technical Reports Server (NTRS)
Srivastava, Prashant K.; Han, Dawei; Rico-Ramirez, Miguel A.; O'Neill, Peggy; Islam, Tanvir; Gupta, Manika
2014-01-01
Soil Moisture and Ocean Salinity (SMOS) is the latest mission which provides flow of coarse resolution soil moisture data for land applications. However, the efficient retrieval of soil moisture for hydrological applications depends on optimally choosing the soil and vegetation parameters. The first stage of this work involves the evaluation of SMOS Level 2 products and then several approaches for soil moisture retrieval from SMOS brightness temperature are performed to estimate Soil Moisture Deficit (SMD). The most widely applied algorithm i.e. Single channel algorithm (SCA), based on tau-omega is used in this study for the soil moisture retrieval. In tau-omega, the soil moisture is retrieved using the Horizontal (H) polarisation following Hallikainen dielectric model, roughness parameters, Fresnel's equation and estimated Vegetation Optical Depth (tau). The roughness parameters are empirically calibrated using the numerical optimization techniques. Further to explore the improvement in retrieval models, modifications have been incorporated in the algorithms with respect to the sources of the parameters, which include effective temperatures derived from the European Center for Medium-Range Weather Forecasts (ECMWF) downscaled using the Weather Research and Forecasting (WRF)-NOAH Land Surface Model and Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) while the s is derived from MODIS Leaf Area Index (LAI). All the evaluations are performed against SMD, which is estimated using the Probability Distributed Model following a careful calibration and validation integrated with sensitivity and uncertainty analysis. The performance obtained after all those changes indicate that SCA-H using WRF-NOAH LSM downscaled ECMWF LST produces an improved performance for SMD estimation at a catchment scale.
Use of satellite and modeled soil moisture data for predicting event soil loss at plot scale
NASA Astrophysics Data System (ADS)
Todisco, F.; Brocca, L.; Termite, L. F.; Wagner, W.
2015-09-01
The potential of coupling soil moisture and a Universal Soil Loss Equation-based (USLE-based) model for event soil loss estimation at plot scale is carefully investigated at the Masse area, in central Italy. The derived model, named Soil Moisture for Erosion (SM4E), is applied by considering the unavailability of in situ soil moisture measurements, by using the data predicted by a soil water balance model (SWBM) and derived from satellite sensors, i.e., the Advanced SCATterometer (ASCAT). The soil loss estimation accuracy is validated using in situ measurements in which event observations at plot scale are available for the period 2008-2013. The results showed that including soil moisture observations in the event rainfall-runoff erosivity factor of the USLE enhances the capability of the model to account for variations in event soil losses, the soil moisture being an effective alternative to the estimated runoff, in the prediction of the event soil loss at Masse. The agreement between observed and estimated soil losses (through SM4E) is fairly satisfactory with a determination coefficient (log-scale) equal to ~ 0.35 and a root mean square error (RMSE) of ~ 2.8 Mg ha-1. These results are particularly significant for the operational estimation of soil losses. Indeed, currently, soil moisture is a relatively simple measurement at the field scale and remote sensing data are also widely available on a global scale. Through satellite data, there is the potential of applying the SM4E model for large-scale monitoring and quantification of the soil erosion process.
Use of satellite and modelled soil moisture data for predicting event soil loss at plot scale
NASA Astrophysics Data System (ADS)
Todisco, F.; Brocca, L.; Termite, L. F.; Wagner, W.
2015-03-01
The potential of coupling soil moisture and a~USLE-based model for event soil loss estimation at plot scale is carefully investigated at the Masse area, in Central Italy. The derived model, named Soil Moisture for Erosion (SM4E), is applied by considering the unavailability of in situ soil moisture measurements, by using the data predicted by a soil water balance model (SWBM) and derived from satellite sensors, i.e. the Advanced SCATterometer (ASCAT). The soil loss estimation accuracy is validated using in situ measurements in which event observations at plot scale are available for the period 2008-2013. The results showed that including soil moisture observations in the event rainfall-runoff erosivity factor of the RUSLE/USLE, enhances the capability of the model to account for variations in event soil losses, being the soil moisture an effective alternative to the estimated runoff, in the prediction of the event soil loss at Masse. The agreement between observed and estimated soil losses (through SM4E) is fairly satisfactory with a determination coefficient (log-scale) equal to of ~ 0.35 and a root-mean-square error (RMSE) of ~ 2.8 Mg ha-1. These results are particularly significant for the operational estimation of soil losses. Indeed, currently, soil moisture is a relatively simple measurement at the field scale and remote sensing data are also widely available on a global scale. Through satellite data, there is the potential of applying the SM4E model for large-scale monitoring and quantification of the soil erosion process.
NASA Astrophysics Data System (ADS)
Shi, Y.; Davis, K. J.; Eissenstat, D. M.; Kaye, J. P.; Duffy, C.; Yu, X.; He, Y.
2014-12-01
Belowground carbon processes are affected by soil moisture and soil temperature, but current biogeochemical models are 1-D and cannot resolve topographically driven hill-slope soil moisture patterns, and cannot simulate the nonlinear effects of soil moisture on carbon processes. Coupling spatially-distributed physically-based hydrologic models with biogeochemical models may yield significant improvements in the representation of topographic influence on belowground C processes. We will couple the Flux-PIHM model to the Biome-BGC (BBGC) model. Flux-PIHM is a coupled physically-based land surface hydrologic model, which incorporates a land-surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model. Because PIHM is capable of simulating lateral water flow and deep groundwater, Flux-PIHM is able to represent the link between groundwater and the surface energy balance, as well as the land surface heterogeneities caused by topography. The coupled Flux-PIHM-BBGC model will be tested at the Susquehanna/Shale Hills critical zone observatory (SSHCZO). The abundant observations, including eddy covariance fluxes, soil moisture, groundwater level, sap flux, stream discharge, litterfall, leaf area index, above ground carbon stock, and soil carbon efflux, make SSHCZO an ideal test bed for the coupled model. In the coupled model, each Flux-PIHM model grid will couple a BBGC cell. Flux-PIHM will provide BBGC with soil moisture and soil temperature information, while BBGC provides Flux-PIHM with leaf area index. Preliminary results show that when Biome- BGC is driven by PIHM simulated soil moisture pattern, the simulated soil carbon is clearly impacted by topography.
NASA Astrophysics Data System (ADS)
DY, C. Y.; Fung, J. C. H.
2016-08-01
A meteorological model requires accurate initial conditions and boundary conditions to obtain realistic numerical weather predictions. The land surface controls the surface heat and moisture exchanges, which can be determined by the physical properties of the soil and soil state variables, subsequently exerting an effect on the boundary layer meteorology. The initial and boundary conditions of soil moisture are currently obtained via National Centers for Environmental Prediction FNL (Final) Operational Global Analysis data, which are collected operationally in 1° by 1° resolutions every 6 h. Another input to the model is the soil map generated by the Food and Agriculture Organization of the United Nations - United Nations Educational, Scientific and Cultural Organization (FAO-UNESCO) soil database, which combines several soil surveys from around the world. Both soil moisture from the FNL analysis data and the default soil map lack accuracy and feature coarse resolutions, particularly for certain areas of China. In this study, we update the global soil map with data from Beijing Normal University in 1 km by 1 km grids and propose an alternative method of soil moisture initialization. Simulations of the Weather Research and Forecasting model show that spinning-up the soil moisture improves near-surface temperature and relative humidity prediction using different types of soil moisture initialization. Explanations of that improvement and improvement of the planetary boundary layer height in performing process analysis are provided.
Simulation of the modern arctic climate by the NCAR CCM1
NASA Technical Reports Server (NTRS)
Bromwich, David H.; Tzeng, Ren-Yow; Parish, Thomas, R.
1994-01-01
The National Center of Atmospheric Research (NCAR) Community Climate Model Version 1 (CCM1's) simulation of the modern arctic climate is evaluated by comparing a five-year seasonal cycle simulation with the European Center for Medium-Range Weather Forecasts (ECMWF) global analyses. The sea level pressure (SLP), storm tracks, vertical cross section of height, 500-hPa height, total energy budget, and moisture budget are analyzed to investigate the biases in the simulated arctic climate. The results show that the model simulates anomalously low SLP, too much storm activity, and anomalously strong baroclinicity to the west of Greenland and vice versa to the east of Greenland. This bias is mainly attributed to the model's topographic representation of Greenland. First, the broadened Greenland topography in the model distorts the path of cyclone waves over the North Atlantic Ocean. Second, the model oversimulates the ridge over Greenland, which intensifies its blocking effect and steers the cyclone waves clockwise around it and hence produces an artificial circum-Greenland trough. These biases are significantly alleviated when the horizontal resolution increases to T42. Over the Arctic basin, the model simulates large amounts of low-level (stratus) clouds in winter and almost no stratus in summer, which is opposite to the observations. This bias is mainly due to the location of the simulated SLP features and the negative anomaly of storm activity, which prevent the transport of moisture into this region during summer but favor this transport in winter. The moisture budget analysis shows that the model's net annual precipitation (P-E) between 70 deg N and the North Pole is 6.6 times larger than the observations and the model transports six times more moisture into this region. The bias in the advection term is attributed to the positive moisture fixer scheme and the distorted flow pattern. However, the excessive moisture transport into the Arctic basin does not solely result from the advection term. The contribution by the moisture fixer is as large as from advection. By contrast, the semi-Lagrangian transport scheme used in the CCM2 significantly improves the moisture simulation for this region; however, globally the error is as serious as for the positive moisture fixer scheme. Finally, because the model has such serious problems in simulating the present arctic climate, its simulations of past and future climate change for this region are questionable.
Soil Moisture Estimate under Forest using a Semi-empirical Model at P-Band
NASA Astrophysics Data System (ADS)
Truong-Loi, M.; Saatchi, S.; Jaruwatanadilok, S.
2013-12-01
In this paper we show the potential of a semi-empirical algorithm to retrieve soil moisture under forests using P-band polarimetric SAR data. In past decades, several remote sensing techniques have been developed to estimate the surface soil moisture. In most studies associated with radar sensing of soil moisture, the proposed algorithms are focused on bare or sparsely vegetated surfaces where the effect of vegetation can be ignored. At long wavelengths such as L-band, empirical or physical models such as the Small Perturbation Model (SPM) provide reasonable estimates of surface soil moisture at depths of 0-5cm. However for densely covered vegetated surfaces such as forests, the problem becomes more challenging because the vegetation canopy is a complex scattering environment. For this reason there have been only few studies focusing on retrieving soil moisture under vegetation canopy in the literature. Moghaddam et al. developed an algorithm to estimate soil moisture under a boreal forest using L- and P-band SAR data. For their studied area, double-bounce between trunks and ground appear to be the most important scattering mechanism. Thereby, they implemented parametric models of radar backscatter for double-bounce using simulations of a numerical forest scattering model. Hajnsek et al. showed the potential of estimating the soil moisture under agricultural vegetation using L-band polarimetric SAR data and using polarimetric-decomposition techniques to remove the vegetation layer. Here we use an approach based on physical formulation of dominant scattering mechanisms and three parameters that integrates the vegetation and soil effects at long wavelengths. The algorithm is a simplification of a 3-D coherent model of forest canopy based on the Distorted Born Approximation (DBA). The simplified model has three equations and three unknowns, preserving the three dominant scattering mechanisms of volume, double-bounce and surface for three polarized backscattering coefficients: σHH, σVV and σHV. The inversion process, which is not an ill-posed problem, uses the non-linear optimization method of Levenberg-Marquardt and estimates the three model parameters: vegetation aboveground biomass, average soil moisture and surface roughness. The model analytical formulation will be first recalled and sensitivity analyses will be shown. Then some results obtained with real SAR data will be presented and compared to ground estimates.
NASA Astrophysics Data System (ADS)
Bircher, Simone; Richaume, Philippe; Mahmoodi, Ali; Mialon, Arnaud; Fernandez-Moran, Roberto; Wigneron, Jean-Pierre; Demontoux, François; Jonard, François; Weihermüller, Lutz; Andreasen, Mie; Rautiainen, Kimmo; Ikonen, Jaakko; Schwank, Mike; Drusch, Mattias; Kerr, Yann H.
2017-04-01
From the passive L-band microwave radiometer onboard the Soil Moisture and Ocean Salinity (SMOS) space mission global surface soil moisture data is retrieved every 2 - 3 days. Thus far, the empirical L-band Microwave Emission of the Biosphere (L-MEB) radiative transfer model applied in the SMOS soil moisture retrieval algorithm is exclusively calibrated over test sites in dry and temperate climate zones. Furthermore, the included dielectric mixing model relating soil moisture to relative permittivity accounts only for mineral soils. However, soil moisture monitoring over the higher Northern latitudes is crucial since these regions are especially sensitive to climate change. A considerable positive feedback is expected if thawing of these extremely organic soils supports carbon decomposition and release to the atmosphere. Due to differing structural characteristics and thus varying bound water fractions, the relative permittivity of organic material is lower than that of the most mineral soils at a given water content. This assumption was verified by means of L-band relative permittivity laboratory measurements of organic and mineral substrates from various sites in Denmark, Finland, Scotland and Siberia using a resonant cavity. Based on these data, a simple empirical dielectric model for organic soils was derived and implemented in the SMOS Soil Moisture Level 2 Prototype Processor (SML2PP). Unfortunately, the current SMOS retrieved soil moisture product seems to show unrealistically low values compared to in situ soil moisture data collected from organic surface layers in North America, Europe and the Tibetan Plateau so that the impact of the dielectric model for organic soils cannot really be tested. A simplified SMOS processing scheme yielding higher soil moisture levels has recently been proposed and is presently under investigation. Furthermore, recalibration of the model parameters accounting for vegetation and roughness effects that were thus far only evaluated using the default dielectric model for mineral soils is ongoing for the "organic" L-MEB version. Additionally, in order to decide where a soil moisture retrieval using the "organic" dielectric model should be triggered, information on soil organic matter content in the soil surface layer has to be considered in the retrieval algorithm. For this purpose, SoilGrids (www.soilgrids.org) providing soil organic carbon content (SOCC) in g/kg is under study. A SOCC threshold based on the relation between the SoilGrids' SOCC and the presence of organic soil surface layers (relevant to alter the microwave L-band emissions from the land surface) in the SoilGrids' source soil profile information has to be established. In this communication, we present the current status of the above outlined studies with the objective to advance towards an improved soil moisture retrieval for organic-rich soils from SMOS passive microwave L-band observations.
Sensitivity of transpiration to subsurface properties: Exploration with a 1-D model
NASA Astrophysics Data System (ADS)
Vrettas, Michail D.; Fung, Inez Y.
2017-06-01
The amount of moisture transpired by vegetation is critically tied to the moisture supply accessible to the root zone. In a Mediterranean climate, integrated evapotranspiration (ET) is typically greater in the dry summer when there is an uninterrupted period of high insolation. We present a 1-D model to explore the subsurface factors that may sustain ET through the dry season. The model includes a stochastic parameterization of hydraulic conductivity, root water uptake efficiency, and hydraulic redistribution by plant roots. Model experiments vary the precipitation, the magnitude and seasonality of ET demand, as well as rooting profiles and rooting depths of the vegetation. The results show that the amount of subsurface moisture remaining at the end of the wet winter is determined by the competition among abundant precipitation input, fast infiltration, and winter ET demand. The weathered bedrock retains ˜30% of the winter rain and provides a substantial moisture reservoir that may sustain ET of deep-rooted (>8 m) trees through the dry season. A small negative feedback exists in the root zone, where the depletion of moisture by ET decreases hydraulic conductivity and enhances the retention of moisture. Hence, hydraulic redistribution by plant roots is impactful in a dry season, or with a less conductive subsurface. Suggestions for implementing the model in the CESM are discussed.
Stream Flow Prediction by Remote Sensing and Genetic Programming
NASA Technical Reports Server (NTRS)
Chang, Ni-Bin
2009-01-01
A genetic programming (GP)-based, nonlinear modeling structure relates soil moisture with synthetic-aperture-radar (SAR) images to present representative soil moisture estimates at the watershed scale. Surface soil moisture measurement is difficult to obtain over a large area due to a variety of soil permeability values and soil textures. Point measurements can be used on a small-scale area, but it is impossible to acquire such information effectively in large-scale watersheds. This model exhibits the capacity to assimilate SAR images and relevant geoenvironmental parameters to measure soil moisture.
NASA Astrophysics Data System (ADS)
Polcher, Jan; Barella-Ortiz, Anaïs; Aires, Filipe; Balsamo, Gianpaolo; Gelati, Emiliano; Rodríguez-Fernández, Nemesio
2015-04-01
Soil moisture is a key state variable of the hydrological cycle. It conditions runoff, infiltration and evaporation over continental surfaces, and is key for forecasting droughts and floods. It plays thus an important role in surface-atmosphere interactions. Surface Soil Moisture (SSM) can be measured by in situ measurements, by satellite observations or modelled using land surface models. As a complementary tool, data assimilation can be used to combine both modelling and satellite observations. The work presented here is an inter-comparison of retrieved and modelled SSM data, for the 2010 - 2012 period, over the Iberian Peninsula. The region has been chosen because its vegetation cover is not very dense and includes strong contrasts in the rainfall regimes and thus a diversity of behaviours for SSM. Furthermore this semi-arid region is strongly dependent on a good management of its water resources. Satellite observations correspond to the Soil Moisture and Ocean Salinity (SMOS) retrievals: the L2 product from an optimal interpolation retrieval, and 3 other products using Neural Network retrievals with different input information: SMOS time indexes, purely SMOS data, or addition of the European Advanced Scaterometer (ASCAT) backscattering, and the Moderate-Resolution Imaging Spectrometer (MODIS) surface temperature information. The modelled soil moistures have been taken from the ORCHIDEE (ORganising Carbon and Hydrology In Dynamic EcosystEms) and the HTESSEL (Hydrology-Tiled ECMWF Scheme for Surface Exchanges over Land) land surface models. Both models are forced with the same atmospheric conditions (as part of the Earth2Observe FP7 project) over the period but they represent the surface soil moisture with very different degrees of complexity. ORCHIDEE has 5 levels in the top 5 centimetres of soil while in HTESSEL this variable is part of the top soil moisture level. The two types of SMOS retrievals are compared to the model outputs in their spatial and temporal characteristics. The comparison with the model helps to identify which retrieval configuration is most consistent with our understanding of surface soil moisture in this region. In particular we have determined how each of the soil moisture products is related to the spatio-temporal variations of rainfall. In large parts of the Iberian Peninsula the co-variance of remote sensed SSM and rainfall is consistent with that of the models. But for some regions questions are raised. The variability of SSM observed by SMOS in the North West of the Iberian Peninsula is similar to that of rainfall, at least this relation of SSM and rainfall is closer than suggested by the two models.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sun, Rui, E-mail: Sunsr@hit.edu.cn; Ismail, Tamer M., E-mail: temoil@aucegypt.edu; Ren, Xiaohan
Highlights: • The effects of moisture content on the burning process of MSW are investigated. • A two-dimensional mathematical model was built to simulate the combustion process. • Temperature distributions, process rates, gas species were measured and simulated. • The The conversion ratio of C/CO and N/NO in MSW are inverse to moisture content. - Abstract: In order to reveal the features of the combustion process in the porous bed of a waste incinerator, a two-dimensional unsteady state model and experimental study were employed to investigate the combustion process in a fixed bed of municipal solid waste (MSW) on themore » combustion process in a fixed bed reactor. Conservation equations of the waste bed were implemented to describe the incineration process. The gas phase turbulence was modeled using the k–ε turbulent model and the particle phase was modeled using the kinetic theory of granular flow. The rate of moisture evaporation, devolatilization rate, and char burnout was calculated according to the waste property characters. The simulation results were then compared with experimental data for different moisture content of MSW, which shows that the incineration process of waste in the fixed bed is reasonably simulated. The simulation results of solid temperature, gas species and process rate in the bed are accordant with experimental data. Due to the high moisture content of fuel, moisture evaporation consumes a vast amount of heat, and the evaporation takes up most of the combustion time (about 2/3 of the whole combustion process). The whole bed combustion process reduces greatly as MSW moisture content increases. The experimental and simulation results provide direction for design and optimization of the fixed bed of MSW.« less
NASA Astrophysics Data System (ADS)
Blyverket, J.; Hamer, P.; Bertino, L.; Lahoz, W. A.
2017-12-01
The European Space Agency Climate Change Initiative for soil moisture (ESA CCI SM) was initiated in 2012 for a period of six years, the objective for this period was to produce the most complete and consistent global soil moisture data record based on both active and passive sensors. The ESA CCI SM products consist of three surface soil moisture datasets: The ACTIVE product and the PASSIVE product were created by fusing scatterometer and radiometer soil moisture data, respectively. The COMBINED product is a blended product based on the former two datasets. In this study we assimilate globally both the ACTIVE and PASSIVE product at a 25 km spatial resolution. The different satellite platforms have different overpass times, an observation is mapped to the hours 00.00, 06.00, 12.00 or 18.00 if it falls within a 3 hour window centred at these times. We use the SURFEX land surface model with the ISBA diffusion scheme for the soil hydrology. For the assimilation routine we apply the Ensemble Transform Kalman Filter (ETKF). The land surface model is driven by perturbed MERRA-2 atmospheric forcing data, which has a temporal resolution of one hour and is mapped to the SURFEX model grid. Bias between the land surface model and the ESA CCI product is removed by cumulative distribution function (CDF) matching. This work is a step towards creating a global root zone soil moisture product from the most comprehensive satellite surface soil moisture product available. As a first step we consider the period from 2010 - 2016. This allows for comparison against other global root zone soil moisture products (SMAP Level 4, which is independent of the ESA CCI SM product).
Howard Evan Canfield; Vicente L. Lopes
2000-01-01
A process-based, simulation model for evaporation, soil water and streamflow (BROOK903) was used to estimate soil moisture change on a semiarid rangeland watershed in southeastern Arizona. A sensitivity analysis was performed to select parameters affecting ET and soil moisture for calibration. Automatic parameter calibration was performed using a procedure based on a...
One-dimensional simulation of temperature and moisture in atmospheric and soil boundary layers
NASA Technical Reports Server (NTRS)
Bornstein, R. D.; Santhanam, K.
1981-01-01
Meteorologists are interested in modeling the vertical flow of heat and moisture through the soil in order to better simulate the vertical and temporal variations of the atmospheric boundary layer. The one dimensional planetary boundary layer model of is modified by the addition of transport equations to be solved by a finite difference technique to predict soil moisture.
NASA Astrophysics Data System (ADS)
Boisserie, Marie
The goal of this dissertation research is to produce empirical soil moisture initial conditions (soil moisture analysis) and investigate its impact on the short-term (2 weeks) to subseasonal (2 months) forecasting skill of 2-m air temperature and precipitation. Because of soil moisture has a long memory and plays a role in controlling the surface water and energy budget, an accurate soil moisture analysis is today widely recognized as having the potential to increase summertime climate forecasting skill. However, because of a lack of global observations of soil moisture, there has been no scientific consensus on the importance of the contribution of a soil moisture initialization as close to the truth as possible to climate forecasting skill. In this study, the initial conditions are generated using a Precipitation Assimilation Reanalysis (PAR) technique to produce a soil moisture analysis. This technique consists mainly of nudging precipitation in the atmosphere component of a land-atmosphere model by adjusting the vertical air humidity profile based on the difference between the rate of the model-derived precipitation rate and the observed rate. The unique aspects of the PAR technique are the following: (1) based on the PAR technique, the soil moisture analysis is generated using a coupled land-atmosphere forecast model; therefore, no bias between the initial conditions and the forecast model (spinup problem) is encountered; and (2) the PAR technique is physically consistent; the surface and radiative fluxes remains in conjunction with the soil moisture analysis. To our knowledge, there has been no attempt to use a physically consistent soil moisture land assimilation system into a land-atmosphere model in a coupled mode. The effect of the PAR technique on the model soil moisture estimates is evaluated using the Global Soil Wetness Project Phase 2 (GSWP-2) multimodel analysis product (used as a proxy for global soil moisture observations) and actual in-situ observations from the state of Illinois. The results show that overall the PAR technique is effective; across most of the globe, the seasonal and anomaly variability of the model soil moisture estimates well reproduce the values of GSWP-2 in the top 1.5 m soil layer; by comparing to in-situ observations in Illinois, we find that the seasonal and anomaly soil moisture variability is also well represented deep into the soil. Therefore, in this study, we produce a new global soil moisture analysis dataset that can be used for many land surface studies (crop modeling, water resource management, soil erosion, etc.). Then, the contribution of the resulting soil moisture analysis (used as initial conditions) on air temperature and precipitation forecasts are investigated. For this, we follow the experimental set up of a model intercomparison study over the time period 1986-1995, the Global Land-Atmosphere Coupling Experiment second phase (GLACE-2), in which the FSU/COAPS climate model has participated. The results of the summertime air temperature forecasts show a significant increase in skill across most of the U.S. at short-term to subseasonal time scales. No increase in summertime precipitation forecasting skill is found at short-term to subseasonal time scales between 1986 and 1995, except for the anomalous drought year of 1988. We also analyze the forecasts of two extreme hydrological events, the 1988 U.S. drought and the 1993 U.S. flood. In general, the comparison of these two extreme hydrological event forecasts shows greater improvement for the summertime of 1988 than that of 1993, suggesting that soil moisture contributes more to the development of a drought than a flood. This result is consistent with Dirmeyer and Brubaker [1999] and Weaver et al. [2009]. By analyzing the evaporative sources of these two extreme events using the back-trajectory methodology of Dirmeyer and Brubaker [1999], we find similar results as this latter paper; the soil moisture-precipitation feedback mechanism seems to play a greater role during the drought year of 1988 than the flood year of 1993. Finally, the accuracy of this soil moisture initialization depends upon the quality of the precipitation dataset that is assimilated. Because of the lack of observed precipitation at a high temporal resolution (3-hourly) for the study period (1986-1995), a reanalysis product is used for precipitation assimilation in this study. It is important to keep in mind that precipitation data in reanalysis sometimes differ significantly from observations since precipitation is often not assimilated into the reanalysis model. In order to investigate that aspect, a similar analysis to that we performed in this study could be done using the 3-hourly Tropical Rainfall Measuring Mission (TRMM) dataset available for a the time period 1998-present. Then, since the TRMM dataset is a fully observational dataset, we expect the soil moisture initialization to be improved over that obtained in this study, which, in turn, may further increase the forecast skill.
NASA Astrophysics Data System (ADS)
Kempe, Michael D.
2016-09-01
Photovoltaic devices are often sensitive to moisture and must be packaged in such a way as to limit moisture ingress for 25 years or more. Typically, this is accomplished through the use of impermeable front and backsheets (e.g., glass sheets or metal foils). However, this will still allow moisture ingress between the sheets from the edges. Attempts to hermetically seal with a glass frit or similarly welded bonds at the edge have had problems with costs and mechanical strength. Because of this, low diffusivity polyisobutylene materials filled with desiccant are typically used. Although it is well known that these materials will substantially delay moisture ingress, correlating that to outdoor exposure has been difficult. Here, we use moisture ingress measurements at different temperatures and relative humidities to find fit parameters for a moisture ingress model for an edge-seal material. Then, using meteorological data, a finite element model is used to predict the moisture ingress profiles for hypothetical modules deployed in different climates and mounting conditions, assuming no change in properties of the edge-seal as a function of aging.
Effect of clothing material on thermal responses of the human body
NASA Astrophysics Data System (ADS)
Fengzhi, Li; Yi, Li
2005-09-01
The influence of clothing material on thermal responses of the human body are investigated by using an integrated model of a clothed thermoregulatory human body. A modified 25-nodes model considering the sweat accumulation on the skin surface is applied to simulate the human physiological regulatory responses. The heat and moisture coupled transfer mechanisms, including water vapour diffusion, the moisture evaporation/condensation, the moisture sorbtion/desorption by fibres, liquid sweat transfer under capillary pressure, and latent heat absorption/release due to phase change, are considered in the clothing model. On comparing prediction results with the experimental data in the literature, the proposed model seems able to predict dynamic heat and moisture transfer between the human body and the clothing system. The human body's thermal responses and clothing temperature and moisture variations are compared for different clothing materials during transient periods. We concluded that the hygroscopicity of clothing materials influences the human thermoregulation process significantly during environmental transients.
NASA Astrophysics Data System (ADS)
Yang, Yang; Dou, Yanxing; Liu, Dong; An, Shaoshan
2017-07-01
Spatial pattern and heterogeneity of soil moisture is important for the hydrological process on the Loess Plateau. This study combined the classical and geospatial statistical techniques to examine the spatial pattern and heterogeneity of soil moisture along a transect scale (e.g. land use types and topographical attributes) on the Loess Plateau. The average values of soil moisture were on the order of farmland > orchard > grassland > abandoned land > shrubland > forestland. Vertical distribution characteristics of soil moisture (0-500 cm) were similar among land use types. Highly significant (p < 0.01) negative correlations were found between soil moisture and elevation (h) except for shrubland (p > 0.05), whereas no significant correlations were found between soil moisture and plan curvature (Kh), stream power index (SPI), compound topographic index (CTI) (p > 0.05), indicating that topographical attributes (mainly h) have a negative effect on the soil moisture spatial heterogeneity. Besides, soil moisture spatial heterogeneity decreased from forestland to grassland and farmland, accompanied by a decline from 15° to 1° alongside upper to lower slope position. This study highlights the importance of land use types and topographical attributes on the soil moisture spatial heterogeneity from a combined analysis of the structural equation model (SEM) and generalized additive models (GAMs), and the relative contribution of land use types to the soil moisture spatial heterogeneity was higher than that of topographical attributes, which provides insights for researches focusing on soil moisture varitions on the Loess Plateau.
Evaluation of uncertainty in field soil moisture estimations by cosmic-ray neutron sensing
NASA Astrophysics Data System (ADS)
Scheiffele, Lena Maria; Baroni, Gabriele; Schrön, Martin; Ingwersen, Joachim; Oswald, Sascha E.
2017-04-01
Cosmic-ray neutron sensing (CRNS) has developed into a valuable, indirect and non-invasive method to estimate soil moisture at the field scale. It provides continuous temporal data (hours to days), relatively large depth (10-70 cm), and intermediate spatial scale measurements (hundreds of meters), thereby overcoming some of the limitations in point measurements (e.g., TDR/FDR) and of remote sensing products. All these characteristics make CRNS a favorable approach for soil moisture estimation, especially for applications in cropped fields and agricultural water management. Various studies compare CRNS measurements to soil sensor networks and show a good agreement. However, CRNS is sensitive to more characteristics of the land-surface, e.g. additional hydrogen pools, soil bulk density, and biomass. Prior to calibration the standard atmospheric corrections are accounting for the effects of air pressure, humidity and variations in incoming neutrons. In addition, the standard calibration approach was further extended to account for hydrogen in lattice water and soil organic material. Some corrections were also proposed to account for water in biomass. Moreover, the sensitivity of the probe was found to decrease with distance and a weighting procedure for the calibration datasets was introduced to account for the sensors' radial sensitivity. On the one hand, all the mentioned corrections showed to improve the accuracy in estimated soil moisture values. On the other hand, they require substantial additional efforts in monitoring activities and they could inherently contribute to the overall uncertainty of the CRNS product. In this study we aim (i) to quantify the uncertainty in the field soil moisture estimated by CRNS and (ii) to understand the role of the different sources of uncertainty. To this end, two experimental sites in Germany were equipped with a CRNS probe and compared to values of a soil moisture network. The agricultural fields were cropped with winter wheat (Pforzheim, 2013) and maize (Braunschweig, 2014) and differ in soil type and management. The results confirm a general good agreement between soil moisture estimated by CRNS and the soil moisture network. However, several sources of uncertainty were identified i.e., overestimation of dry conditions, strong effects of the additional hydrogen pools and an influence of the vertical soil moisture profile. Based on that, a global sensitivity analysis based on Monte Carlo sampling can be performed and evaluated in terms of soil moisture and footprint characteristics. The results allow quantifying the role of the different factors and identifying further improvements in the method.
Spatial-temporal variability of soil moisture and its estimation across scales
NASA Astrophysics Data System (ADS)
Brocca, L.; Melone, F.; Moramarco, T.; Morbidelli, R.
2010-02-01
The soil moisture is a quantity of paramount importance in the study of hydrologic phenomena and soil-atmosphere interaction. Because of its high spatial and temporal variability, the soil moisture monitoring scheme was investigated here both for soil moisture retrieval by remote sensing and in view of the use of soil moisture data in rainfall-runoff modeling. To this end, by using a portable Time Domain Reflectometer, a sequence of 35 measurement days were carried out within a single year in seven fields located inside the Vallaccia catchment, central Italy, with area of 60 km2. Every sampling day, soil moisture measurements were collected at each field over a regular grid with an extension of 2000 m2. The optimization of the monitoring scheme, with the aim of an accurate mean soil moisture estimation at the field and catchment scale, was addressed by the statistical and the temporal stability. At the field scale, the number of required samples (NRS) to estimate the field-mean soil moisture within an accuracy of 2%, necessary for the validation of remotely sensed soil moisture, ranged between 4 and 15 for almost dry conditions (the worst case); at the catchment scale, this number increased to nearly 40 and it refers to almost wet conditions. On the other hand, to estimate the mean soil moisture temporal pattern, useful for rainfall-runoff modeling, the NRS was found to be lower. In fact, at the catchment scale only 10 measurements collected in the most "representative" field, previously determined through the temporal stability analysis, can reproduce the catchment-mean soil moisture with a determination coefficient, R2, higher than 0.96 and a root-mean-square error, RMSE, equal to 2.38%. For the "nonrepresentative" fields the accuracy in terms of RMSE decreased, but similar R2 coefficients were found. This insight can be exploited for the sampling in a generic field when it is sufficient to know an index of soil moisture temporal pattern to be incorporated in conceptual rainfall-runoff models. The obtained results can address the soil moisture monitoring network design from which a reliable soil moisture temporal pattern at the catchment scale can be derived.
The impact of non-isothermal soil moisture transport on evaporation fluxes in a maize cropland
NASA Astrophysics Data System (ADS)
Shao, Wei; Coenders-Gerrits, Miriam; Judge, Jasmeet; Zeng, Yijian; Su, Ye
2018-06-01
The process of evaporation interacts with the soil, which has various comprehensive mechanisms. Multiphase flow models solve air, vapour, water, and heat transport equations to simulate non-isothermal soil moisture transport of both liquid water and vapor flow, but are only applied in non-vegetated soils. For (sparsely) vegetated soils often energy balance models are used, however these lack the detailed information on non-isothermal soil moisture transport. In this study we coupled a multiphase flow model with a two-layer energy balance model to study the impact of non-isothermal soil moisture transport on evaporation fluxes (i.e., interception, transpiration, and soil evaporation) for vegetated soils. The proposed model was implemented at an experimental agricultural site in Florida, US, covering an entire maize-growing season (67 days). As the crops grew, transpiration and interception became gradually dominated, while the fraction of soil evaporation dropped from 100% to less than 20%. The mechanisms of soil evaporation vary depending on the soil moisture content. After precipitation the soil moisture content increased, exfiltration of the liquid water flow could transport sufficient water to sustain evaporation from soil, and the soil vapor transport was not significant. However, after a sufficient dry-down period, the soil moisture content significantly reduced, and the soil vapour flow significantly contributed to the upward moisture transport in topmost soil. A sensitivity analysis found that the simulations of moisture content and temperature at the soil surface varied substantially when including the advective (i.e., advection and mechanical dispersion) vapour transport in simulation, including the mechanism of advective vapour transport decreased soil evaporation rate under wet condition, while vice versa under dry condition. The results showed that the formulation of advective soil vapor transport in a soil-vegetation-atmosphere transfer continuum can affect the simulated evaporation fluxes, especially under dry condition.
2008-10-01
bacterial inactivation ( Hiraki , 2000 and Hiraki et al., 2003). The exact mechanism of action is not well understood. Purasal®P is a combination of...coli O157:H7, Slamonella typhimurium and Listeria monocytogenes Journal of Food Science 70: M404-M408. Hiraki J. 2000. ε-polylysine; its...development and utilization. Fine Chem 29: 18-25. Hiraki J., Takafumi I., Ninomiya S., Seki H., Uohama K., Seki H., Kimura S., Yangimoto Y. and Barnett J
Estimating Soil Moisture Using Polsar Data: a Machine Learning Approach
NASA Astrophysics Data System (ADS)
Khedri, E.; Hasanlou, M.; Tabatabaeenejad, A.
2017-09-01
Soil moisture is an important parameter that affects several environmental processes. This parameter has many important functions in numerous sciences including agriculture, hydrology, aerology, flood prediction, and drought occurrence. However, field procedures for moisture calculations are not feasible in a vast agricultural region territory. This is due to the difficulty in calculating soil moisture in vast territories and high-cost nature as well as spatial and local variability of soil moisture. Polarimetric synthetic aperture radar (PolSAR) imaging is a powerful tool for estimating soil moisture. These images provide a wide field of view and high spatial resolution. For estimating soil moisture, in this study, a model of support vector regression (SVR) is proposed based on obtained data from AIRSAR in 2003 in C, L, and P channels. In this endeavor, sequential forward selection (SFS) and sequential backward selection (SBS) are evaluated to select suitable features of polarized image dataset for high efficient modeling. We compare the obtained data with in-situ data. Output results show that the SBS-SVR method results in higher modeling accuracy compared to SFS-SVR model. Statistical parameters obtained from this method show an R2 of 97% and an RMSE of lower than 0.00041 (m3/m3) for P, L, and C channels, which has provided better accuracy compared to other feature selection algorithms.
Moisture sorption isotherms and thermodynamic properties of mexican mennonite-style cheese.
Martinez-Monteagudo, Sergio I; Salais-Fierro, Fabiola
2014-10-01
Moisture adsorption isotherms of fresh and ripened Mexican Mennonite-style cheese were investigated using the static gravimetric method at 4, 8, and 12 °C in a water activity range (aw) of 0.08-0.96. These isotherms were modeled using GAB, BET, Oswin and Halsey equations through weighed non-linear regression. All isotherms were sigmoid in shape, showing a type II BET isotherm, and the data were best described by GAB model. GAB model coefficients revealed that water adsorption by cheese matrix is a multilayer process characterized by molecules that are strongly bound in the monolayer and molecules that are slightly structured in a multilayer. Using the GAB model, it was possible to estimate thermodynamic functions (net isosteric heat, differential entropy, integral enthalpy and entropy, and enthalpy-entropy compensation) as function of moisture content. For both samples, the isosteric heat and differential entropy decreased with moisture content in exponential fashion. The integral enthalpy gradually decreased with increasing moisture content after reached a maximum value, while the integral entropy decreased with increasing moisture content after reached a minimum value. A linear compensation was found between integral enthalpy and entropy suggesting enthalpy controlled adsorption. Determination of moisture content and aw relationship yields to important information of controlling the ripening, drying and storage operations as well as understanding of the water state within a cheese matrix.
NASA Astrophysics Data System (ADS)
Laiolo, Paola; Gabellani, Simone; Rudari, Roberto; Boni, Giorgio; Puca, Silvia
2013-04-01
Soil moisture plays a fundamental role in the partitioning of mass and energy fluxes between land surface and atmosphere, thereby influencing climate and weather, and it is important in determining the rainfall-runoff response of catchments; moreover, in hydrological modelling and flood forecasting, a correct definition of moisture conditions is a key factor for accurate predictions. Different sources of information for the estimation of the soil moisture state are currently available: satellite data, point measurements and model predictions. All are affected by intrinsic uncertainty. Among different satellite sensors that can be used for soil moisture estimation three major groups can be distinguished: passive microwave sensors (e.g., SSMI), active sensors (e.g. SAR, Scatterometers), and optical sensors (e.g. Spectroradiometers). The last two families, mainly because of their temporal and spatial resolution seem the most suitable for hydrological applications In this work soil moisture point measurements from 10 sensors in the Italian territory are compared of with the satellite products both from the HSAF project SM-OBS-2, derived from the ASCAT scatterometer, and from ACHAB, an operative energy balance model that assimilate LST data derived from MSG and furnishes daily an evaporative fraction index related to soil moisture content for all the Italian region. Distributed comparison of the ACHAB and SM-OBS-2 on the whole Italian territory are performed too.
Role of Subsurface Physics in the Assimilation of Surface Soil Moisture Observations
NASA Technical Reports Server (NTRS)
Reichle, R. H.
2010-01-01
Root zone soil moisture controls the land-atmosphere exchange of water and energy and exhibits memory that may be useful for climate prediction at monthly scales. Assimilation of satellite-based surface soil moisture observations into a land surface model is an effective way to estimate large-scale root zone soil moisture. The propagation of surface information into deeper soil layers depends on the model-specific representation of subsurface physics that is used in the assimilation system. In a suite of experiments we assimilate synthetic surface soil moisture observations into four different models (Catchment, Mosaic, Noah and CLM) using the Ensemble Kalman Filter. We demonstrate that identical twin experiments significantly overestimate the information that can be obtained from the assimilation of surface soil moisture observations. The second key result indicates that the potential of surface soil moisture assimilation to improve root zone information is higher when the surface to root zone coupling is stronger. Our experiments also suggest that (faced with unknown true subsurface physics) overestimating surface to root zone coupling in the assimilation system provides more robust skill improvements in the root zone compared with underestimating the coupling. When CLM is excluded from the analysis, the skill improvements from using models with different vertical coupling strengths are comparable for different subsurface truths. Finally, the skill improvements through assimilation were found to be sensitive to the regional climate and soil types.
NASA Astrophysics Data System (ADS)
Ansari Amoli, Abdolreza; Lopez-Baeza, Ernesto; Mahmoudi, Ali; Mahmoodi, Ali
2016-07-01
Synergistic Use of SMOS Measurements with SMAP Derived and In-situ Data over the Valencia Anchor Station by Using a Downscaling Technique Ansari Amoli, A.(1),Mahmoodi, A.(2) and Lopez-Baeza, E.(3) (1) Department of Earth Physics and Thermodynamics, University of Valencia, Spain (2) Centre d'Etudes Spatiales de la BIOsphère (CESBIO), France (3) Department of Earth Physics and Thermodynamics, University of Valencia, Spain Soil moisture products from active sensors are not operationally available. Passive remote sensors return more accurate estimates, but their resolution is much coarser. One solution to overcome this problem is the synergy between radar and radiometric data by using disaggregation (downscaling) techniques. Few studies have been conducted to merge high resolution radar and coarse resolution radiometer measurements in order to obtain an intermediate resolution product. In this paper we present an algorithm using combined available SMAP (Soil Moisture Active and Passive) radar and SMOS (Soil Moisture and Ocean Salinity) radiometer measurements to estimate surface soil moisture over the Valencia Anchor Station (VAS), Valencia, Spain. The goal is to combine the respective attributes of the radar and radiometer observations to estimate soil moisture at a resolution of 3 km. The algorithm disaggregates the coarse resolution SMOS (15 km) radiometer brightness temperature product based on the spatial variation of the high resolution SMAP (3 km) radar backscatter. The disaggregation of the radiometer brightness temperature uses the radar backscatter spatial patterns within the radiometer footprint that are inferred from the radar measurements. For this reason the radar measurements within the radiometer footprint are scaled by parameters that are derived from the temporal fluctuations in the radar and radiometer measurements.
Modeling heat and moisture transport in firefighter protective clothing during flash fire exposure
NASA Astrophysics Data System (ADS)
Chitrphiromsri, Patirop; Kuznetsov, Andrey V.
2005-01-01
In this paper, a model of heat and moisture transport in firefighter protective clothing during a flash fire exposure is presented. The aim of this study is to investigate the effect of coupled heat and moisture transport on the protective performance of the garment. Computational results show the distribution of temperature and moisture content in the fabric during the exposure to the flash fire as well as during the cool-down period. Moreover, the duration of the exposure during which the garment protects the firefighter from getting second and third degree burns from the flash fire exposure is numerically predicted. A complete model for the fire-fabric-air gap-skin system is presented.
Muiti-Sensor Historical Climatology of Satellite-Derived Global Land Surface Moisture
NASA Technical Reports Server (NTRS)
Owe, Manfred; deJeu, Richard; Holmes, Thomas
2007-01-01
A historical climatology of continuous satellite derived global land surface soil moisture is being developed. The data set consists of surface soil moisture retrievals from observations of both historical and currently active satellite microwave sensors, including Nimbus-7 SMMR, DMSP SSM/I, TRMM TMI, and AQUA AMSR-E. The data sets span the period from November 1978 through the end of 2006. The soil moisture retrievals are made with the Land Parameter Retrieval Model, a physically-based model which was developed jointly by researchers from the above institutions. These data are significant in that they are the longest continuous data record of observational surface soil moisture at a global scale. Furthermore, while previous reports have intimated that higher frequency sensors such as on SSM/I are unable to provide meaningful information on soil moisture, our results indicate that these sensors do provide highly useful soil moisture data over significant parts of the globe, and especially in critical areas located within the Earth's many arid and semi-arid regions.
A model of the thermal-spike mechanism in graphite/epoxy laminates
NASA Technical Reports Server (NTRS)
Adamson, M. J.
1982-01-01
The influence of a thermal spike on a moisture-saturated graphite/epoxy composite was studied in detail. A single thermal spike from 25 C to 132 C was found to produce damage as evidenced by a significant increase in the level of moisture saturation in the composite. Approximately half of this increase remained after a vacuum anneal at 150 C for 7 days, suggesting the presence of an irreversible damage component. Subsequent thermal spikes created less and less additional moisture absorption, with the cumulative effect being a maximum or limiting moisture capacity of the composite. These observations are explained in terms of a model previously developed to explain the reverse thermal effect of moisture absorption in epoxy and epoxy matrix composites. This model, based on the inverse temperature dependence of free volume, contributes an improved understanding of thermal-spike effects in graphite/epoxy composites.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Staliulionis, Ž.; Jabbari, M.; Hattel, J. H.
The number of electronics used in outdoor environment is constantly growing. The humidity causes about 19 % of all electronics failures and, especially, moisture increases these problems due to the ongoing process of miniaturization and lower power consumption of electronic components. Moisture loads are still not understood well by design engineers, therefore this field has become one of the bottlenecks in the electronics system design. The objective of this paper is to model moisture ingress into an electronics enclosure under isothermal conditions. The moisture diffusion model is based on a 1D quasi-steady state (QSS) approximation for Fick’s second law. Thismore » QSS approach is also described with an electrical analogy which gives a fast tool in modelling of the moisture response. The same QSS method is applied to ambient water vapour variations. The obtained results are compared to an analytical solution and very good agreement is found.« less
FPL roof temperature and moisture model : description and verification
A. TenWolde
This paper describes a mathematical model developed by the Forest Products Laboratory to predict attic temperatures, relative humidities, and roof sheathing moisture content. Comparison of data from model simulation and measured data provided limited validation of the model and led to the following conclusions: (1) the model can...
Mesoscale research activities with the LAMPS model
NASA Technical Reports Server (NTRS)
Kalb, M. W.
1985-01-01
Researchers achieved full implementation of the LAMPS mesoscale model on the Atmospheric Sciences Division computer and derived balanced and real wind initial states for three case studies: March 6, April 24, April 26, 1982. Numerical simulations were performed for three separate studies: (1) a satellite moisture data impact study using Vertical Atmospheric Sounder (VAS) precipitable water as a constraint on model initial state moisture analyses; (2) an evaluation of mesoscale model precipitation simulation accuracy with and without convective parameterization; and (3) the sensitivity of model precipitation to mesoscale detail of moisture and vertical motion in an initial state.
NASA Astrophysics Data System (ADS)
Kearney, Michael R.; Maino, James L.
2018-06-01
Accurate models of soil moisture are vital for solving core problems in meteorology, hydrology, agriculture and ecology. The capacity for soil moisture modelling is growing rapidly with the development of high-resolution, continent-scale gridded weather and soil data together with advances in modelling methods. In particular, the GlobalSoilMap.net initiative represents next-generation, depth-specific gridded soil products that may substantially increase soil moisture modelling capacity. Here we present an implementation of Campbell's infiltration and redistribution model within the NicheMapR microclimate modelling package for the R environment, and use it to assess the predictive power provided by the GlobalSoilMap.net product Soil and Landscape Grid of Australia (SLGA, ∼100 m) as well as the coarser resolution global product SoilGrids (SG, ∼250 m). Predictions were tested in detail against 3 years of root-zone (3-75 cm) soil moisture observation data from 35 monitoring sites within the OzNet project in Australia, with additional tests of the finalised modelling approach against cosmic-ray neutron (CosmOz, 0-50 cm, 9 sites from 2011 to 2017) and satellite (ASCAT, 0-2 cm, continent-wide from 2007 to 2009) observations. The model was forced by daily 0.05° (∼5 km) gridded meteorological data. The NicheMapR system predicted soil moisture to within experimental error for all data sets. Using the SLGA or the SG soil database, the OzNet soil moisture could be predicted with a root mean square error (rmse) of ∼0.075 m3 m-3 and a correlation coefficient (r) of 0.65 consistently through the soil profile without any parameter tuning. Soil moisture predictions based on the SLGA and SG datasets were ≈ 17% closer to the observations than when using a chloropleth-derived soil data set (Digital Atlas of Australian Soils), with the greatest improvements occurring for deeper layers. The CosmOz observations were predicted with similar accuracy (r = 0.76 and rmse of ∼0.085 m3 m-3). Comparisons at the continental scale to 0-2 cm satellite data (ASCAT) showed that the SLGA/SG datasets increased model fit over simulations using the DAAS soil properties (r ∼ 0.63 &rmse 15% vs. r 0.48 &rmse 18%, respectively). Overall, our results demonstrate the advantages of using GlobalSoilMap.net products in combination with gridded weather data for modelling soil moisture at fine spatial and temporal resolution at the continental scale.
Liu, Ya; Pan, Xianzhang; Wang, Changkun; Li, Yanli; Shi, Rongjie
2015-01-01
Robust models for predicting soil salinity that use visible and near-infrared (vis–NIR) reflectance spectroscopy are needed to better quantify soil salinity in agricultural fields. Currently available models are not sufficiently robust for variable soil moisture contents. Thus, we used external parameter orthogonalization (EPO), which effectively projects spectra onto the subspace orthogonal to unwanted variation, to remove the variations caused by an external factor, e.g., the influences of soil moisture on spectral reflectance. In this study, 570 spectra between 380 and 2400 nm were obtained from soils with various soil moisture contents and salt concentrations in the laboratory; 3 soil types × 10 salt concentrations × 19 soil moisture levels were used. To examine the effectiveness of EPO, we compared the partial least squares regression (PLSR) results established from spectra with and without EPO correction. The EPO method effectively removed the effects of moisture, and the accuracy and robustness of the soil salt contents (SSCs) prediction model, which was built using the EPO-corrected spectra under various soil moisture conditions, were significantly improved relative to the spectra without EPO correction. This study contributes to the removal of soil moisture effects from soil salinity estimations when using vis–NIR reflectance spectroscopy and can assist others in quantifying soil salinity in the future. PMID:26468645
Effects of moisture controlled charcoal on indoor thermal and air environments
NASA Astrophysics Data System (ADS)
Matsumoto, Hiroshi; Yokogoshi, Midori; Nabeshima, Yuki
2017-10-01
It is crucial to remove and control indoor moisture in Japan, especially in hot and humid summers, in order to improve thermal comfort and save energy in buildings. Charcoal for moisture control made from the waste of wood material has attracted attention among many control strategies to control indoor moisture, and it is beginning to be used in houses. However, the basic characteristics of the charcoal to control moisture and remove chemical compounds in indoor air have not been investigated sufficiently. The objective of this study is to clarify the effect of moisture control charcoal on indoor thermal and air environments by a long-term field measurement using two housing scale models with/without charcoal in Toyohashi, Japan. The comparative experiments to investigate the effect of the charcoal on air temperature and humidity for two models with/without charcoal were conducted from 2015 to 2016. Also, the removal performance of volatile organic compound (VOCs) was investigated in the summer of 2015. Four bags of packed charcoal were set on the floor in the attic for one model during the experiment. As a result of the experiments, a significant effect of moisture control was observed in hot and humid season, and the efficient effect of moisture adsorption was obtained by the periodic humidification experiment using a humidifier. Furthermore, the charcoal showed a remarkable performance of VOC removal from indoor air by the injection experiment of formaldehyde.
An overview of the measurements of soil moisture and modeling of moisture flux in FIFE
NASA Technical Reports Server (NTRS)
Wang, J. R.
1992-01-01
Measurements of soil moisture and calculations of moisture transfer in the soil medium and at the air-soil interface were performed over a 15-km by 15-km test site during FIFE in 1987 and 1989. The measurements included intensive soil moisture sampling at the ground level and surveys at aircraft altitudes by several passive and active microwave sensors as well as a gamma radiation device.
NASA Astrophysics Data System (ADS)
Seo, Eunkyo; Lee, Myong-In; Jeong, Jee-Hoon; Koster, Randal D.; Schubert, Siegfried D.; Kim, Hye-Mi; Kim, Daehyun; Kang, Hyun-Suk; Kim, Hyun-Kyung; MacLachlan, Craig; Scaife, Adam A.
2018-05-01
This study uses a global land-atmosphere coupled model, the land-atmosphere component of the Global Seasonal Forecast System version 5, to quantify the degree to which soil moisture initialization could potentially enhance boreal summer surface air temperature forecast skill. Two sets of hindcast experiments are performed by prescribing the observed sea surface temperature as the boundary condition for a 15-year period (1996-2010). In one set of the hindcast experiments (noINIT), the initial soil moisture conditions are randomly taken from a long-term simulation. In the other set (INIT), the initial soil moisture conditions are taken from an observation-driven offline Land Surface Model (LSM) simulation. The soil moisture conditions from the offline LSM simulation are calibrated using the forecast model statistics to minimize the inconsistency between the LSM and the land-atmosphere coupled model in their mean and variability. Results show a higher boreal summer surface air temperature prediction skill in INIT than in noINIT, demonstrating the potential benefit from an accurate soil moisture initialization. The forecast skill enhancement appears especially in the areas in which the evaporative fraction—the ratio of surface latent heat flux to net surface incoming radiation—is sensitive to soil moisture amount. These areas lie in the transitional regime between humid and arid climates. Examination of the extreme 2003 European and 2010 Russian heat wave events reveal that the regionally anomalous soil moisture conditions during the events played an important role in maintaining the stationary circulation anomalies, especially those near the surface.
Comparison of experimental data with results of some drying models for regularly shaped products
NASA Astrophysics Data System (ADS)
Kaya, Ahmet; Aydın, Orhan; Dincer, Ibrahim
2010-05-01
This paper presents an experimental and theoretical investigation of drying of moist slab, cylinder and spherical products to study dimensionless moisture content distributions and their comparisons. Experimental study includes the measurement of the moisture content distributions of slab and cylindrical carrot, slab and cylindrical pumpkin and spherical blueberry during drying at various temperatures (e.g., 30, 40, 50 and 60°C) at specific constant velocity ( U = 1 m/s) and the relative humidity φ = 30%. In theoretical analysis, two moisture transfer models are used to determine drying process parameters (e.g., drying coefficient and lag factor) and moisture transfer parameters (e.g., moisture diffusivity and moisture transfer coefficient), and to calculate the dimensionless moisture content distributions. The calculated results are then compared with the experimental moisture data. A considerably high agreement is obtained between the calculations and experimental measurements for the cases considered. The effective diffusivity values were evaluated between 0.741 × 10-5 and 5.981 × 10-5 m2/h for slab products, 0.818 × 10-5 and 6.287 × 10-5 m2/h for cylindrical products and 1.213 × 10-7 and 7.589 × 10-7 m2/h spherical products using the Model-I and 0.316 × 10-5-5.072 × 10-5 m2/h for slab products, 0.580 × 10-5-9.587 × 10-5 m2/h for cylindrical products and 1.408 × 10-7-13.913 × 10-7 m2/h spherical products using the Model-II.
NASA Technical Reports Server (NTRS)
Baker, David R.; Lynn, Barry H.; Boone, Aaron; Tao, Wei-Kuo; Simpson, Joanne
2000-01-01
Idealized numerical simulations are performed with a coupled atmosphere/land-surface model to identify the roles of initial soil moisture, coastline curvature, and land breeze circulations on sea breeze initiated precipitation. Data collected on 27 July 1991 during the Convection and Precipitation Electrification Experiment (CAPE) in central Florida are used. The 3D Goddard Cumulus Ensemble (GCE) cloud resolving model is coupled with the Goddard Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) land surface model, thus providing a tool to simulate more realistically land-surface/atmosphere interaction and convective initiation. Eight simulations are conducted with either straight or curved coast-lines, initially homogeneous soil moisture or initially variable soil moisture, and initially homogeneous horizontal winds or initially variable horizontal winds (land breezes). All model simulations capture the diurnal evolution and general distribution of sea-breeze initiated precipitation over central Florida. The distribution of initial soil moisture influences the timing, intensity and location of subsequent precipitation. Soil moisture acts as a moisture source for the atmosphere, increases the connectively available potential energy, and thus preferentially focuses heavy precipitation over existing wet soil. Strong soil moisture-induced mesoscale circulations are not evident in these simulations. Coastline curvature has a major impact on the timing and location of precipitation. Earlier low-level convergence occurs inland of convex coastlines, and subsequent precipitation occurs earlier in simulations with curved coastlines. The presence of initial land breezes alone has little impact on subsequent precipitation. however, simulations with both coastline curvature and initial land breezes produce significantly larger peak rain rates due to nonlinear interactions.
Western US high June 2015 temperatures and their relation to global warming and soil moisture
NASA Astrophysics Data System (ADS)
Philip, Sjoukje Y.; Kew, Sarah F.; Hauser, Mathias; Guillod, Benoit P.; Teuling, Adriaan J.; Whan, Kirien; Uhe, Peter; Oldenborgh, Geert Jan van
2018-04-01
The Western US states Washington (WA), Oregon (OR) and California (CA) experienced extremely high temperatures in June 2015. The temperature anomalies were so extreme that they cannot be explained with global warming alone. We investigate the hypothesis that soil moisture played an important role as well. We use a land surface model and a large ensemble from the weather@home modelling effort to investigate the coupling between soil moisture and temperature in a warming world. Both models show that May was anomalously dry, satisfying a prerequisite for the extreme heat wave, and they indicate that WA and OR are in a wet-to-dry transitional soil moisture regime. We use two different land surface-atmosphere coupling metrics to show that there was strong coupling between temperature, latent heat flux and the effect of soil moisture deficits on the energy balance in June 2015 in WA and OR. June temperature anomalies conditioned on wet/dry conditions show that both the mean and extreme temperatures become hotter for dry soils, especially in WA and OR. Fitting a Gaussian model to temperatures using soil moisture as a covariate shows that the June 2015 temperature values fit well in the extrapolated empirical temperature/drought lines. The high temperature anomalies in WA and OR are thus to be expected, given the dry soil moisture conditions and that those regions are in the transition from a wet to a dry regime. CA is already in the dry regime and therefore the necessity of taking soil moisture into account is of lower importance.
Modeling of the Assiniboine Delta Aquifer (ADA) of Manitoba using the Groundwater Storage from GRACE
NASA Astrophysics Data System (ADS)
Yirdaw-Zeleke, S.; Snelgrove, K.
2007-12-01
This paper investigates the use of GRACE (Gravity Recovery and Climate Experiment) moisture storages for modeling of the Assiniboine Delta Aquifer (ADA) of Manitoba, Canada. There are great promises from GRACE in capturing regional groundwater storages that are potentially used for modeling application. However, it is well known that these storages are difficult to measure over the scales needed for hydrological model applications. Therefore, prior to modeling the aquifer using GRACE moisture storages, the storages need to be downscaled in to regional groundwater storages using the measured groundwater head data available in the area. Previous studies in the ADA have shown that the downscaled moisture storage estimates compared favorably with the measured groundwater storage over the area. This study focuses on the modeling of the ADA aquifer using the downscaled GRACE moisture storages. These storages will be used to initialize, calibration and potentially steer the hydrologic simulation. The calibrated model then will be validated independently using the measured data. These validations will hopefully provide better explanations for the underlying reasons for the differences in model predictions and measurements. This will identify some of the key assumptions and uncertainties in predicting moisture storage, and so highlight topics for further discussion and research.
Seasonal-to-Interannual Variability and Land Surface Processes
NASA Technical Reports Server (NTRS)
Koster, Randal
2004-01-01
Atmospheric chaos severely limits the predictability of precipitation on subseasonal to interannual timescales. Hope for accurate long-term precipitation forecasts lies with simulating atmospheric response to components of the Earth system, such as the ocean, that can be predicted beyond a couple of weeks. Indeed, seasonal forecasts centers now rely heavily on forecasts of ocean circulation. Soil moisture, another slow component of the Earth system, is relatively ignored by the operational seasonal forecasting community. It is starting, however, to garner more attention. Soil moisture anomalies can persist for months. Because these anomalies can have a strong impact on evaporation and other surface energy fluxes, and because the atmosphere may respond consistently to anomalies in the surface fluxes, an accurate soil moisture initialization in a forecast system has the potential to provide additional forecast skill. This potential has motivated a number of atmospheric general circulation model (AGCM) studies of soil moisture and its contribution to variability in the climate system. Some of these studies even suggest that in continental midlatitudes during summer, oceanic impacts on precipitation are quite small relative to soil moisture impacts. The model results, though, are strongly model-dependent, with some models showing large impacts and others showing almost none at all. A validation of the model results with observations thus naturally suggests itself, but this is exceedingly difficult. The necessary contemporaneous soil moisture, evaporation, and precipitation measurements at the large scale are virtually non-existent, and even if they did exist, showing statistically that soil moisture affects rainfall would be difficult because the other direction of causality - wherein rainfall affects soil moisture - is unquestionably active and is almost certainly dominant. Nevertheless, joint analyses of observations and AGCM results do reveal some suggestions of land-atmosphere feedback in the observational record, suggestions that soil moisture can affect precipitation over seasonal timescales and across certain large continental areas. The strength of this observed feedback in nature is not large but is still significant enough to be potentially useful, e.g., for forecasts. This talk will address all of these issues. It will begin with a brief overview of land surface modeling in atmospheric models but will then focus on recent research - using both observations and models - into the impact of land surface processes on variability in the climate system.
Simha, H V Vikram; Pushpadass, Heartwin A; Franklin, Magdaline Eljeeva Emerald; Kumar, P Arun; Manimala, K
2016-06-01
Moisture sorption isotherms of spray-dried milk-foxtail millet powder were determined at 10, 25 and 40 °C. Sorption data was fitted using classical and soft-computing approaches. The isotherms were of type II, and equilibrium moisture content (EMC) was temperature dependent. The BET monolayer moisture content decreased from 3.30 to 2.67 % as temperature increased from 10 to 40 °C. Amongst the classical models, Ferro-Fontan gave the best fit of EMC-aw data. However, the Sugeno-type adaptive neuro-fuzzy inference system (ANFIS) with generalized bell-shaped membership function performed better than artificial neural network and classical models with RMSE as low as 0.0099. The isosteric heat of sorption decreased from 150.32 kJ mol(-1) at 1 % moisture content to 44.11 kJ mol(-1) at 15 % moisture. The enthalpy-entropy compensation theory was validated, and the isokinetic and harmonic mean temperatures were determined as 333.1 and 297.5 K, respectively.
Experimental evidence and modelling of drought induced alternative stable soil moisture states
NASA Astrophysics Data System (ADS)
Robinson, David; Jones, Scott; Lebron, Inma; Reinsch, Sabine; Dominguez, Maria; Smith, Andrew; Marshal, Miles; Emmett, Bridget
2017-04-01
The theory of alternative stable states in ecosystems is well established in ecology; however, evidence from manipulation experiments supporting the theory is limited. Developing the evidence base is important because it has profound implications for ecosystem management. Here we show evidence of the existence of alternative stable soil moisture states induced by drought in an upland wet heath. We used a long-term (15 yrs) climate change manipulation experiment with moderate sustained drought, which reduced the ability of the soil to retain soil moisture by degrading the soil structure, reducing moisture retention. Moreover, natural intense droughts superimposed themselves on the experiment, causing an unexpected additional alternative soil moisture state to develop, both for the drought manipulation and control plots; this impaired the soil from rewetting in winter. Our results show the coexistence of three stable states. Using modelling with the Hydrus 1D software package we are able to show the circumstances under which shifts in soil moisture states are likely to occur. Given the new understanding it presents a challenge of how to incorporate feedbacks, particularly related to soil structure, into soil flow and transport models?
NASA Astrophysics Data System (ADS)
Kara, Cem; Doymaz, İbrahim
2015-07-01
Drying of apple pomace representing by-products from apple juice processing was studied. The results obtained show that moisture content of the pomace decreases with time and temperature. The Midilli et al. model was selected as the best mathematical model for describing the drying kinetics of the apple pomace. The effective moisture diffusivity varied from 1.73 × 10-10 to 4.40 × 10-10 m2/s and the activation energy was calculated to be 29.65 kJ/mol.
Adeeb A. Rahman; Thomas J. Urbanik; Mustafa Mahamid
2003-01-01
Collapse of fiberboard packaging boxes, in the shipping industry, due to rise in humidity conditions is common and very costly. A 3D FE nonlinear model is developed to predict the moisture flow throughout a corrugated packaging fiberboard sandwich structure. The model predicts how the moisture diffusion will permeate through the layers of a fiberboard (medium and...
Validation of SMAP soil moisture for the SMAPVEX15 field campaign using a hyper-resolution model
USDA-ARS?s Scientific Manuscript database
Accurate global mapping of soil moisture is the goal of the Soil Moisture Active Passive (SMAP) mission, which is expected to improve the estimation of water, energy, and carbon exchanges between the land and the atmosphere. Like other satellite products, the SMAP soil moisture retrievals need to be...
NASA Astrophysics Data System (ADS)
Bradford, J. B.; Schlaepfer, D.; Palmquist, K. A.; Lauenroth, W.
2017-12-01
Climate projections for western North America suggest temperature increases that are relatively consistent across climate models. However, precipitation projections are less consistent, especially in the Southwest, promoting uncertainty about the future of soil moisture and drought. We utilized a daily time-step ecosystem water balance model to characterize soil temperature and moisture patterns at a 10-km resolution across western North America for historical (1980-2010), mid-century (2020-2050), and late century (2070-2100). We simulated soil moisture and temperature under two representative concentration pathways and eleven climate models (selected strategically to represent the range of variability in projections among the full set of models in the CMIP5 database and perform well in hind-cast comparisons for the region), and we use the results to identify areas with robust projections, e.g. areas where the large majority of models agree in the direction of change in long-term average soil moisture or temperature. Rising air temperatures will increase average soil temperatures across western North America and expand the area of mesic and thermic soil temperature regimes while decreasing the area of cryic and frigid regimes. Future soil moisture conditions are relatively consistent across climate models for much of the region, including many areas with variable precipitation trajectories. Consistent projections for drier soils are expected in most of Arizona and New Mexico, similar to previous studies. Other regions with projections for declining soil moisture include the central and southern U.S. Great Plains and large parts of southern British Columbia. By contrast, areas with robust projections for increasing soil moisture include northeastern Montana, southern Alberta and Saskatchewan, and many areas in the intermountain west dominated by big sagebrush. In addition, seasonal moisture patterns in much of the western US drylands are expected to shift toward cool-season water availability, with potentially important consequences for ecosystem structure and function. These results provide a framework for coping with variability in climate projections and assessing climate change impacts on dryland ecosystems.
NASA Astrophysics Data System (ADS)
Moore, A. W.; Small, E. E.; Owen, S. E.; Hardman, S. H.; Wong, C.; Freeborn, D. J.; Larson, K. M.
2016-12-01
GNSS Interferometric Reflectometry (GNSS-IR) uses GNSS signals reflected off the land to infer changes in the near-antenna environment and monitor fluctuations in soil moisture, as well as other related hydrologic variables: snow depth/snow water equivalent (SWE), vegetation water content, and water level [Larson and Small, 2013; McCreight, et al., 2014; Larson et al., 2013]. GNSS instruments installed by geoscientists and surveyors to measure land motions can measure soil moisture fluctuations with accuracy (RMSE <0.04 cm3/cm3 [Small et al., 2016]) and latency sufficient for many applications (e.g., weather forecasting, climate studies, satellite validation). The soil moisture products have a unique and complementary footprint intermediate in scale between satellite and standard in situ sensors. Variations in vegetation conditions introduce considerable errors, but algorithms have been developed to address this issue [Small et al., 2016]. A pilot project (PBO H2O) using 100+ GPS sites in the western U.S. (Figure 1) from a single network (the Plate Boundary Observatory) has been operated by the University of Colorado (CU) at http://xenon.colorado.edu/portal since October 2012. JPL and CU are funded by NASA ESTO to refactor the PBO H2O software within an Apache OODT framework for robust operational analysis of soil moisture data and auto-configuration when new stations are added. We will report progress on the new GNSS H2O analysis portal, and plans to expand to global networks and from GPS to other GNSS signals. ReferencesLarson, K. M., & Small, E. E. (2013) Eos, 94(52), 505-512. McCreight, J. L., Small, E. E., & Larson, K. M. (2014). Water Resour. Res., 50(8), 6892-6909. Larson, K. M., Ray, R. D., Nievinski, F. G., & Freymueller, J. T. (2013). IEEE Geosci Remote S, 10(5), 1200-1204. Small, E. E., Larson, K. M., Chew, C. C., Dong, J., & Ochsner, T. E. (2016). IEEE J Sel. Top. Appl. PP(39). Figure 1: (R) Western U.S. GPS-IR soil moisture sites. (L): Products derived from GNSS reflection data for (clockwise from upper left) vegetation water content, SWE, sea level, and volumetric soil moisture.
Evaluation of a Soil Moisture Data Assimilation System Over the Conterminous United States
NASA Astrophysics Data System (ADS)
Bolten, J. D.; Crow, W. T.; Zhan, X.; Reynolds, C. A.; Jackson, T. J.
2008-12-01
A data assimilation system has been designed to integrate surface soil moisture estimates from the EOS Advanced Microwave Scanning Radiometer (AMSR-E) with an online soil moisture model used by the USDA Foreign Agriculture Service for global crop estimation. USDA's International Production Assessment Division (IPAD) of the Office of Global Analysis (OGA) ingests global soil moisture within a Crop Assessment Data Retrieval and Evaluation (CADRE) Decision Support System (DSS) to provide nowcasts of crop conditions and agricultural-drought. This information is primarily used to derive mid-season crop yield estimates for the improvement of foreign market access for U.S. agricultural products. The CADRE is forced by daily meteorological observations (precipitation and temperature) provided by the Air Force Weather Agency (AFWA) and World Meteorological Organization (WMO). The integration of AMSR-E observations into the two-layer soil moisture model employed by IPAD can potentially enhance the reliability of the CADRE soil moisture estimates due to AMSR-E's improved repeat time and greater spatial coverage. Assimilation of the AMSR-E soil moisture estimates is accomplished using a 1-D Ensemble Kalman filter (EnKF) at daily time steps. A diagnostic calibration of the filter is performed using innovation statistics by accurately weighting the filter observation and modeling errors for three ranges of vegetation biomass density estimated using historical data from the Advanced Very High Resolution Radiometer (AVHRR). Assessment of the AMSR-E assimilation has been completed for a five year duration over the conterminous United States. To evaluate the ability of the filter to compensate for incorrect precipitation forcing into the model, a data denial approach is employed by comparing soil moisture results obtained from separate model simulations forced with precipitation products of varying uncertainty. An analysis of surface and root-zone anomalies is presented for each model simulation over the conterminous United States, as well as statistical assessments for each simulation over various land cover types.
NASA Astrophysics Data System (ADS)
Dominguez, Francina
This study is the first to analyze the mechanisms that drive precipitation recycling variability at the daily to intraseasonal timescale. A new Dynamic Precipitation Recycling model is developed which, unlike previous models, includes the moisture storage term in the equation of conservation of atmospheric moisture. As shown using scaling analysis, the moisture storage term is non-negligible at small time scales, so the new model enables us to analyze precipitation recycling variability at shorter timescales than traditional models. The daily to intraseasonal analysis enables us to uncover key relationships between recycling and the moisture and energy fluxes. In the second phase of this work, a spatiotemporal analysis of daily precipitation recycling is performed over two regions of North America: the Midwestern United States, and the North American Monsoon System (NAMS) region. These regions were chosen because they present contrasting land-atmosphere interactions. Different physical mechanisms drive precipitation recycling in each region. In the Midwestern United States, evapotranspiration is not significantly affected by soil moisture anomalies, and there is a high recycling ratio during periods of reduced total precipitation. The reason is that, during periods of drier atmospheric conditions, transpiration will continue to provide moisture to the overlying atmosphere and contribute to total rainfall. Consequently, precipitation recycling variability in not driven by changes in evapotranspiration. Precipitable water, sensible heat and moisture fluxes are the main drivers of recycling variability in the Midwest. However, the drier soil moisture conditions over the NAMS region limit evapotranspiration, which will drive recycling variability. In this region, evapotranspiration becomes an important contribution to precipitation after Monsoon onset when total precipitation and evapotranspiration are highest. The precipitation recycling process in the NAMS region relocates moisture from regions of high evapotranspiration like the seasonally dry tropical forests of Mexico to drier regions downwind. During long monsoons, when soil moisture is abundant for a prolonged period of time, precipitation recycling significantly contributes to precipitation during periods of reduced total rainfall. In both the moisture abundant Midwestern region and the drier NAMS region, precipitation recycling plays an important role in maintaining a favorable hydroclimatological environment for vegetation.
NASA Astrophysics Data System (ADS)
Khedun, C. P.; Mishra, A. K.; Bolten, J. D.; Giardino, J. R.; Singh, V. P.
2010-12-01
Soil moisture is an important component of the hydrological cycle. Climate variability patterns, such as the Pacific Decadal Oscillation (PDO), El Niño Southern Oscillation (ENSO), and Atlantic Multidecadal Oscillation (AMO) are determining factors on surface water availability and soil moisture. Understanding this complex relationship and the phase and lag times between climate events and soil moisture variability is important for agricultural management and water planning. In this study we look at the effect of these climate teleconnection patterns on the soil moisture across the Rio Grande/Río Bravo del Norte basin. The basin is transboundary between the US and Mexico and has a varied climatology - ranging from snow dominated in its headwaters in Colorado, to an arid and semi-arid region in its middle reach and a tropical climate in the southern section before it discharges into the Gulf of Mexico. Agricultural activities in the US and in northern Mexico are highly dependent on the Rio Grande and are extremely vulnerable to climate extremes. The treaty between the two countries does not address climate related events. The soil moisture is generated using the community NOAH land surface model (LSM). The LSM is a 1-D column model that runs in coupled or uncoupled mode, and it simulates soil moisture, soil temperature, skin temperature, snowpack depth, snow water equivalent, canopy water content, and energy flux and water flux of the surface energy and water balance. The North American Land Data Assimilation Scheme 2 (NLDAS2) is used to drive the model. The model is run for the period 1979 to 2009. The soil moisture output is validated against measured values from the different Soil Climate Analysis Network (SCAN) sites within the basin. The spatial and temporal variability of the modeled soil moisture is then analyzed using marginal entropy to investigate monthly, seasonal, and annual variability. Wavelet transform is used to determine the relation, phase difference, and lag times between climate teleconnection events and soil moisture. The results from this study will help agricultural scientists and water planners in both the US and Mexico in better managing the dwindling water resources of this transboundary basin.
Developing a model for moisture in saltcake waste tanks: Progress report
DOE Office of Scientific and Technical Information (OSTI.GOV)
Simmons, C.S.; Aimo, N.; Fayer, M.J.
1997-07-01
This report describes a modeling effort to provide a computer simulation capability for estimating the distribution and movement of moisture in the saltcake-type waste contained in Hanford`s single-shell radioactive waste storage tanks. This moisture model goes beyond an earlier version because it describes water vapor movement as well as the interstitial liquid held in a saltcake waste. The work was performed by Pacific Northwest National Laboratory to assist Duke Engineering and Services Hanford with the Organic Tank Safety Program. The Organic Tank Safety Program is concerned whether saltcake waste, when stabilized by jet pumping, will retain sufficient moisture near themore » surface to preclude any possibility of an accidental ignition and propagation of burning. The nitrate/nitrite saltcake, which might also potentially include combustible organic chemicals might not always retain enough moisture near the surface to preclude any such accident. Draining liquid from a tank by pumping, coupled with moisture evaporating into a tank`s head space, may cause a dry waste surface that is not inherently safe. The moisture model was devised to help examine this safety question. The model accounts for water being continually cycled by evaporation into the head space and returned to the waste by condensation or partly lost through venting to the external atmosphere. Water evaporation occurs even in a closed tank, because it is driven by the transfer to the outside of the heat load generated by radioactivity within the waste. How dry a waste may become over time depends on the particular hydraulic properties of a saltcake, and the model uses those properties to describe the capillary flow of interstitial liquid as well as the water vapor flow caused by thermal differences within the porous waste.« less
Trends in soil moisture and real evapotranspiration in Douro River for the period 1980-2010
NASA Astrophysics Data System (ADS)
García-Valdecasas-Ojeda, Matilde; de Franciscis, Sebastiano; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María
2017-04-01
This study analyzes the evolution of different hydrological variables, such as soil moisture and real evapotranspiration, for the last 30 years, in the Douro Basin, the most extensive basin in the Iberian Peninsula. The different components of the real evaporation, connected to the soil moisture content, can be important when analyzing the intensity of droughts and heat waves, and particularly relevant for the study of the climate change impacts. The real evapotranspiration and soil moisture data are provided by simulations obtained using the Variable Infiltration Capacity (VIC) hydrological model. This model is a large-scale hydrologic model and allows estimates of different variables in the hydrological system of a basin. Land surface is modeled as a grid of large and uniform cells with sub-grid heterogeneity (e.g. land cover), while water influx is local, only depending from the interaction between grid cells and local atmosphere environment. Observational data of temperature and precipitation from Spain02 dataset are used as input variables for VIC model. The simulations have a spatial resolution of about 9 km, and the analysis is carried out on a seasonal time-scale. Additionally, we compare these results with those obtained from a dynamical downscaling driven by ERA-Interim data using the Weather Research and Forecasting (WRF) model, with the same spatial resolution. The results obtained from Spain02 data show a decrease in soil moisture at different parts of the basin during spring and summer, meanwhile soil moisture seems to be increased for autumn. No significant changes are found for real evapotranspiration. Keywords: real evapotranspiration, soil moisture, Douro Basin, trends, VIC, WRF. Acknowledgements: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).
Patz, J A; Strzepek, K; Lele, S; Hedden, M; Greene, S; Noden, B; Hay, S I; Kalkstein, L; Beier, J C
1998-10-01
While malaria transmission varies seasonally, large inter-annual heterogeneity of malaria incidence occurs. Variability in entomological parameters, biting rates and entomological inoculation rates (EIR) have been strongly associated with attack rates in children. The goal of this study was to assess the weather's impact on weekly biting and EIR in the endemic area of Kisian, Kenya. Entomological data collected by the U.S. Army from March 1986 through June 1988 at Kisian, Kenya was analysed with concurrent weather data from nearby Kisumu airport. A soil moisture model of surface-water availability was used to combine multiple weather parameters with landcover and soil features to improve disease prediction. Modelling soil moisture substantially improved prediction of biting rates compared to rainfall; soil moisture lagged two weeks explained up to 45% of An. gambiae biting variability, compared to 8% for raw precipitation. For An. funestus, soil moisture explained 32% variability, peaking after a 4-week lag. The interspecies difference in response to soil moisture was significant (P < 0.00001). A satellite normalized differential vegetation index (NDVI) of the study site yielded a similar correlation (r = 0.42 An. gambiae). Modelled soil moisture accounted for up to 56% variability of An. gambiae EIR, peaking at a lag of six weeks. The relationship between temperature and An. gambiae biting rates was less robust; maximum temperature r2 = -0.20, and minimum temperature r2 = 0.12 after lagging one week. Benefits of hydrological modelling are compared to raw weather parameters and to satellite NDVI. These findings can improve both current malaria risk assessments and those based on El Niño forecasts or global climate change model projections.
NASA Technical Reports Server (NTRS)
Carlson, Toby N.
1988-01-01
Using model development, image analysis and micrometeorological measurements, the object is to push beyond the present limitations of using the infrared temperature method for remotely determining surface energy fluxes and soil moisture over vegetation. Model development consists of three aspects: (1) a more complex vegetation formulation which is more flexible and realistic; (2) a method for modeling the fluxes over patchy vegetation cover; and (3) a method for inferring a two-layer soil vertical moisture gradient from analyses of horizontal variations in surface temperatures. HAPEX and FIFE satellite data will be used along with aircraft thermal infrared and solar images as input for the models. To test the models, moisture availability and bulk canopy resistances will be calculated from data collected locally at the Rock Springs experimental field site and, eventually, from the FIFE project.
NASA Astrophysics Data System (ADS)
van Wesemael, Bas; Nocita, Marco
2016-04-01
One of the problems for mapping of soil organic carbon (SOC) at large-scale based on visible - near and short wave infrared (VIS-NIR-SWIR) remote sensing techniques is the spatial variation of topsoil moisture when the images are collected. Soil moisture is certainly an aspect causing biased SOC estimations, due to the problems in discriminating reflectance differences due to either variations in organic matter or soil moisture, or their combination. In addition, the difficult validation procedures make the accurate estimation of soil moisture from optical airborne a major challenge. After all, the first millimeters of the soil surface reflect the signal to the airborne sensor and show a large spatial, vertical and temporal variation in soil moisture. Hence, the difficulty of assessing the soil moisture of this thin layer at the same moment of the flight. The creation of a soil moisture proxy, directly retrievable from the hyperspectral data is a priority to improve the large-scale prediction of SOC. This paper aims to verify if the application of the normalized soil moisture index (NSMI) to Airborne Prima Experiment (APEX) hyperspectral images could improve the prediction of SOC. The study area was located in the loam region of Wallonia, Belgium. About 40 samples were collected from bare fields covered by the flight lines, and analyzed in the laboratory. Soil spectra, corresponding to the sample locations, were extracted from the images. Once the NSMI was calculated for the bare fields' pixels, spatial patterns, presumably related to within field soil moisture variations, were revealed. SOC prediction models, built using raw and pre-treated spectra, were generated from either the full dataset (general model), or pixels belonging to one of the two classes of NSMI values (NSMI models). The best result, with a RMSE after validation of 1.24 g C kg-1, was achieved with a NSMI model, compared to the best general model, characterized by a RMSE of 2.11 g C kg-1. These results confirmed the advantage to controlling the effect of soil moisture on the detection of SOC. The NSMI proved to be a flexible concept, due to the possible use of different SWIR wavelengths, and ease of use, because measurements of soil moisture by other techniques are not needed. However, in the future, it will be important to assess the effectiveness of the NSMI for different soil types, and other hyperspectral sensors.
Further experimentation on bubble generation during transformer overload
DOE Office of Scientific and Technical Information (OSTI.GOV)
Oommen, T.V.
1992-03-01
This report covers additional work done during 1990 and 1991 on gas bubble generation under overload conditions. To improve visual bubble detection, a single disc coil was used. To further improve detection, a corona device was also used which signaled the onset of corona activity in the early stages of bubble formation. A total of fourteen model tests were conducted, half of which used the Inertaire system, and the remaining, a conservator (COPS). Moisture content of paper in the coil varied from 1.0% to 8.0%; gas (nitrogen) content varied from 1.0% to 8.8%. The results confirmed earlier observations that themore » mathematical bubble prediction model was not valid for high gas content model with relatively low moisture levels in the coil. An empirical relationship was formulated to accurately predict bubble evolution temperatures from known moisture and gas content values. For low moisture content models (below 2%), the simple Piper relationship was sufficient to predict bubble evolution temperatures, regardless of gas content. Moisture in the coil appears to be the key factor in bubble generation. Gas blanketed (Inertaire) systems do not appear to be prone to premature bubble generation from overloads as previously thought. The new bubble prediction model reveals that for a coil with 2% moisture, the bubble evolution temperature would be about 140{degrees}C. Since old transformers in service may have as much as 2% moisture in paper, the 140{degrees}C bubble evolution temperature may be taken as the lower limit of bubble evolution temperature under overload conditions for operating transformers. Drier insulation would raise the bubble evolution temperature.« less
SMAP Data Assimilation at NASA SPoRT
NASA Technical Reports Server (NTRS)
Blankenship, Clay B.; Case, Jonathan L.; Zavodsky, Bradley T.
2016-01-01
The NASA Short-Term Prediction Research and Transition (SPoRT) Center maintains a near-real- time run of the Noah Land Surface Model within the Land Information System (LIS) at 3-km resolution. Soil moisture products from this model are used by several NOAA/National Weather Service Weather Forecast Offices for flood and drought situational awareness. We have implemented assimilation of soil moisture retrievals from the Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active/ Passive (SMAP) satellites, and are now evaluating the SMAP assimilation. The SMAP-enhanced LIS product is planned for public release by October 2016.
NASA Astrophysics Data System (ADS)
Mirfenderesgi, G.; Matheny, A. M.; Bohrer, G.
2017-12-01
Whole-plant hydraulic performance depends on the integrated function of complexes of traits, such as embolism resistance and xylem anatomy, stomatal closure mechanisms, hydraulic architecture, and root properties. The diversity of such traits produces a wide range of response strategies to both short-term variation of soil moisture and VPD, and to long-term changes to climate and hydrological cycles which affect water availability. This study aims to assess the role of different hydraulic trait combinations in trees' vulnerability to limitations in soil water availability. We use a quantitative hydrodynamic modeling framework which allows studying the influence of each suits of plant hydraulic traits independently, and assess how the different trait groups interact with each other to form viable hydraulic strategies in response to reduced soil moisture availability. We utilize the advanced plant hydrodynamic model, FETCH2, which resolves plant functional hydrodynamics, using parameters that represent emergent physiological traits at the root, stem and leaf levels. FETCH2 simulates the integrated plant-level transpiration and water capacitance, provided hydraulic traits and environmental forcing. We define a multi-dimensional hydraulic "trait space" by considering a broad continuum of hydraulic traits at each of the leaf, stem, and root levels. We test the consequences of different strategies under a range of environmental conditions, representing typical wet, intermediate, and dry conditions, based on as observations in a research forest in Northern Michigan, USA. We evaluate the degree to which simulated trees suffer hydraulic failure due to cavitation, resulting in loss of xylem conductivity, or carbon starvation, through leaf water-potential-driven reduction of stomatal conductance. Our result demonstrated that risk-prone leaf strategy when combined with risk-adverse xylem traits may expose plant to the risk of hydraulic failure due to declining water potential during period of low soil moisture and high VPD. However, if this strategy is coupled with deep roots, the plant is less likely to experience water stress even during periods of low soil water availability and high evaporative demand.
Downscaling SMAP Soil Moisture Using Geoinformation Data and Geostatistics
NASA Astrophysics Data System (ADS)
Xu, Y.; Wang, L.
2017-12-01
Soil moisture is important for agricultural and hydrological studies. However, ground truth soil moisture data for wide area is difficult to achieve. Microwave remote sensing such as Soil Moisture Active Passive (SMAP) can offer a solution for wide coverage. However, existing global soil moisture products only provide observations at coarse spatial resolutions, which often limit their applications in regional agricultural and hydrological studies. This paper therefore aims to generate fine scale soil moisture information and extend soil moisture spatial availability. A statistical downscaling scheme is presented that incorporates multiple fine scale geoinformation data into the downscaling of coarse scale SMAP data in the absence of ground measurement data. Geoinformation data related to soil moisture patterns including digital elevation model (DEM), land surface temperature (LST), land use and normalized difference vegetation index (NDVI) at a fine scale are used as auxiliary environmental variables for downscaling SMAP data. Generalized additive model (GAM) and regression tree are first conducted to derive statistical relationships between SMAP data and auxiliary geoinformation data at an original coarse scale, and residuals are then downscaled to a finer scale via area-to-point kriging (ATPK) by accounting for the spatial correlation information of the input residuals. The results from standard validation scores as well as the triple collocation (TC) method against soil moisture in-situ measurements show that the downscaling method can significantly improve the spatial details of SMAP soil moisture while maintain the accuracy.
Global response of the growing season to soil moisture and topography
NASA Astrophysics Data System (ADS)
Guevara, M.; Arroyo, C.; Warner, D. L.; Equihua, J.; Lule, A. V.; Schwartz, A.; Taufer, M.; Vargas, R.
2017-12-01
Soil moisture has a direct influence in plant productivity. Plant productivity and its greenness can be inferred by remote sensing with higher spatial detail than soil moisture. The objective was to improve the coarse scale of currently available satellite soil moisture estimates and identify areas of strong coupling between the interannual variability soil moisture and the maximum greenness vegetation fraction (MGVF) at the global scale. We modeled, cross-validated and downscaled remotely sensed soil moisture using machine learning and digital terrain analysis across 23 years (1991-2013) of available data. Improving the accuracy (0.69-0.87 % of cross-validated explained variance) and the spatial detail (from 27 to 15km) of satellite soil moisture, we filled temporal gaps of information across vegetated areas where satellite soil moisture does not work properly. We found that 7.57% of global vegetated area shows strong correlation with our downscaled product (R2>0.5, Fig. 1). We found a dominant positive response of vegetation greenness to topography-based soil moisture across water limited environments, however, the tropics and temperate environments of higher latitudes showed a sparse negative response. We conclude that topography can be used to effectively improve the spatial detail of globally available remotely sensed soil moisture, which is convenient to generate unbiased comparisons with global vegetation dynamics, and better inform land and crop modeling efforts.
Lai, K P K; Dolan, K D; Ng, P K W
2009-06-01
Thermal and moisture effects on grape anthocyanin degradation were investigated using solid media to simulate processing at temperatures above 100 degrees C. Grape pomace (anthocyanin source) mixed with wheat pastry flour (1: 3, w/w dry basis) was used in both isothermal and nonisothermal experiments by heating the same mixture at 43% (db) initial moisture in steel cells in an oil bath at 80, 105, and 145 degrees C. To determine the effect of moisture on anthocyanin degradation, the grape pomace-wheat flour mixture was heated isothermally at 80 degrees C at constant moisture contents of 10%, 20%, and 43% (db). Anthocyanin degradation followed a pseudo first-order reaction with moisture. Anthocyanins degraded more rapidly with increasing temperature and moisture. The effects of temperature and moisture on the rate constant were modeled according to the Arrhenius and an exponential relationship, respectively. The nonisothermal reaction rate constant and activation energy (mean +/- standard error) were k(80 degrees C, 43% (db) moisture) = 2.81 x 10(-4)+/- 1.1 x 10(-6) s(-1) and DeltaE = 75273 +/- 197 J/g mol, respectively. The moisture parameter for the exponential model was 4.28 (dry basis moisture content)(-1). One possible application of this study is as a tool to predict the loss of anthocyanins in nutraceutical products containing grape pomace. For example, if the process temperature history and moisture history in an extruded snack fortified with grape pomace is known, the percentage anthocyanin loss can be predicted.
NASA Astrophysics Data System (ADS)
Goodchild, Martin; Janes, Stuart; Jenkins, Malcolm; Nicholl, Chris; Kühn, Karl
2015-04-01
The aim of this work is to assess the use of temperature corrected substrate moisture data to improve the relationship between environmental drivers and the measurement of substrate moisture content in high porosity soil-free growing environments such as coir. Substrate moisture sensor data collected from strawberry plants grown in coir bags installed in a table-top system under a polytunnel illustrates the impact of temperature on capacitance-based moisture measurements. Substrate moisture measurements made in our coir arrangement possess the negative temperature coefficient of the permittivity of water where diurnal changes in moisture content oppose those of substrate temperature. The diurnal substrate temperature variation was seen to range from 7° C to 25° C resulting in a clearly observable temperature effect in substrate moisture content measurements during the 23 day test period. In the laboratory we measured the ML3 soil moisture sensor (ThetaProbe) response to temperature in Air, dry glass beads and water saturated glass beads and used a three-phase alpha (α) mixing model, also known as the Complex Refractive Index Model (CRIM), to derive the permittivity temperature coefficients for glass and water. We derived the α value and estimated the temperature coefficient for water - for sensors operating at 100MHz. Both results are good agreement with published data. By applying the CRIM equation with the temperature coefficients of glass and water the moisture temperature coefficient of saturated glass beads has been reduced by more than an order of magnitude to a moisture temperature coefficient of
NASA Astrophysics Data System (ADS)
Cowley, Garret S.; Niemann, Jeffrey D.; Green, Timothy R.; Seyfried, Mark S.; Jones, Andrew S.; Grazaitis, Peter J.
2017-02-01
Soil moisture can be estimated at coarse resolutions (>1 km) using satellite remote sensing, but that resolution is poorly suited for many applications. The Equilibrium Moisture from Topography, Vegetation, and Soil (EMT+VS) model downscales coarse-resolution soil moisture using fine-resolution topographic, vegetation, and soil data to produce fine-resolution (10-30 m) estimates of soil moisture. The EMT+VS model performs well at catchments with low topographic relief (≤124 m), but it has not been applied to regions with larger ranges of elevation. Large relief can produce substantial variations in precipitation and potential evapotranspiration (PET), which might affect the fine-resolution patterns of soil moisture. In this research, simple methods to downscale temporal average precipitation and PET are developed and included in the EMT+VS model, and the effects of spatial variations in these variables on the surface soil moisture estimates are investigated. The methods are tested against ground truth data at the 239 km2 Reynolds Creek watershed in southern Idaho, which has 1145 m of relief. The precipitation and PET downscaling methods are able to capture the main features in the spatial patterns of both variables. The space-time Nash-Sutcliffe coefficients of efficiency of the fine-resolution soil moisture estimates improve from 0.33 to 0.36 and 0.41 when the precipitation and PET downscaling methods are included, respectively. PET downscaling provides a larger improvement in the soil moisture estimates than precipitation downscaling likely because the PET pattern is more persistent through time, and thus more predictable, than the precipitation pattern.
NASA Astrophysics Data System (ADS)
Hamed Alemohammad, Seyed; Kolassa, Jana; Prigent, Catherine; Aires, Filipe; Gentine, Pierre
2017-04-01
Knowledge of root zone soil moisture is essential in studying plant's response to different stress conditions since plant photosynthetic activity and transpiration rate are constrained by the water available through their roots. Current global root zone soil moisture estimates are based on either outputs from physical models constrained by observations, or assimilation of remotely-sensed microwave-based surface soil moisture estimates with physical model outputs. However, quality of these estimates are limited by the accuracy of the model representations of physical processes (such as radiative transfer, infiltration, percolation, and evapotranspiration) as well as errors in the estimates of the surface parameters. Additionally, statistical approaches provide an alternative efficient platform to develop root zone soil moisture retrieval algorithms from remotely-sensed observations. In this study, we present a new neural network based retrieval algorithm to estimate surface and root zone soil moisture from passive microwave observations of SMAP satellite (L-band) and AMSR2 instrument (X-band). SMAP early morning observations are ideal for surface soil moisture retrieval. AMSR2 mid-night observations are used here as an indicator of plant hydraulic properties that are related to root zone soil moisture. The combined observations from SMAP and AMSR2 together with other ancillary observations including the Solar-Induced Fluorescence (SIF) estimates from GOME-2 instrument provide necessary information to estimate surface and root zone soil moisture. The algorithm is applied to observations from the first 18 months of SMAP mission and retrievals are validated against in-situ observations and other global datasets.
Transpiration-driven aridification of the American West in 21st-Century model projections
NASA Astrophysics Data System (ADS)
Mankin, J. S.; Smerdon, J. E.; Cook, B.; Williams, P.; Seager, R.
2016-12-01
Climate models project significant 21st-Century declines in soil moisture and runoff over the American West from anthropogenic climate change, but the associated physical mechanisms are poorly characterized. In particular, there are significant uncertainties regarding the modulation of evaporative losses by vegetation and how the physical determinants (i.e., changes in moisture supply and demand) of future surface moisture balance will vary in time, space, and depth in the soil. Using 35-members of the NCAR CESM large ensemble (LENS) and 1800 years of its pre-industrial control simulation, we examine the response of Western surface moisture balance (soil moisture and runoff) to anthropogenic forcing. Declines in runoff and soil moisture are forced primarily by robust increases in evapotranspiration (from increased plant transpiration and canopy evaporation from leaf area index increases), rather than more uncertain changes in total precipitation. This increased water loss occurs even with significant and widespread increases in plant water-use efficiency. Additionally, snowpack reductions in the Rockies and the Pacific Northwest contribute to reductions in summer-season deep soil moisture, while increased transpiration dries out near surface soil moisture even in regions where total precipitation increases. When coupled with a warming- and CO2-induced shift in phenology and increase in net primary production, these vegetation changes reduce peak summer soil moisture and runoff considerably. Our results thus point to a large role for simulated vegetation responses in determining future Western aridity, highlighting the importance of reducing the substantial extant uncertainties in vegetation processes simulated within climate models.
Modeling seasonal surface temperature variations in secondary tropical dry forests
NASA Astrophysics Data System (ADS)
Cao, Sen; Sanchez-Azofeifa, Arturo
2017-10-01
Secondary tropical dry forests (TDFs) provide important ecosystem services such as carbon sequestration, biodiversity conservation, and nutrient cycle regulation. However, their biogeophysical processes at the canopy-atmosphere interface remain unknown, limiting our understanding of how this endangered ecosystem influences, and responds to the ongoing global warming. To facilitate future development of conservation policies, this study characterized the seasonal land surface temperature (LST) behavior of three successional stages (early, intermediate, and late) of a TDF, at the Santa Rosa National Park (SRNP), Costa Rica. A total of 38 Landsat-8 Thermal Infrared Sensor (TIRS) data and the Surface Reflectance (SR) product were utilized to model LST time series from July 2013 to July 2016 using a radiative transfer equation (RTE) algorithm. We further related the LST time series to seven vegetation indices which reflect different properties of TDFs, and soil moisture data obtained from a Wireless Sensor Network (WSN). Results showed that the LST in the dry season was 15-20 K higher than in the wet season at SRNP. We found that the early successional stages were about 6-8 K warmer than the intermediate successional stages and were 9-10 K warmer than the late successional stages in the middle of the dry season; meanwhile, a minimum LST difference (0-1 K) was observed at the end of the wet season. Leaf phenology and canopy architecture explained most LST variations in both dry and wet seasons. However, our analysis revealed that it is precipitation that ultimately determines the LST variations through both biogeochemical (leaf phenology) and biogeophysical processes (evapotranspiration) of the plants. Results of this study could help physiological modeling studies in secondary TDFs.
Measurement of heat and moisture exchanger efficiency.
Chandler, M
2013-09-01
Deciding between a passive heat and moisture exchanger or active humidification depends upon the level of humidification that either will deliver. Published international standards dictate that active humidifiers should deliver a minimum humidity of 33 mg.l(-1); however, no such requirement exists, for heat and moisture exchangers. Anaesthetists instead have to rely on information provided by manufacturers, which may not allow comparison of different devices and their clinical effectiveness. I suggest that measurement of humidification efficiency, being the percentage moisture returned and determined by measuring the temperature of the respired gases, should be mandated, and report a modification of the standard method that will allow this to be easily measured. In this study, different types of heat and moisture exchangers for adults, children and patients with a tracheostomy were tested. Adult and paediatric models lost between 6.5 mg.l(-1) and 8.5 mg.l(-1) moisture (corresponding to an efficiency of around 80%); however, the models designed for patients with a tracheostomy lost between 16 mg.l(-1) and 18 mg.l(-1) (60% efficiency). I propose that all heat and moisture exchangers should be tested in this manner and percentage efficiency reported to allow an informed choice between different types and models. © 2013 The Association of Anaesthetists of Great Britain and Ireland.
Scaling an in situ network for high resolution modeling during SMAPVEX15
NASA Astrophysics Data System (ADS)
Coopersmith, E. J.; Cosh, M. H.; Jacobs, J. M.; Jackson, T. J.; Crow, W. T.; Holifield Collins, C.; Goodrich, D. C.; Colliander, A.
2015-12-01
Among the greatest challenges within the field of soil moisture estimation is that of scaling sparse point measurements within a network to produce higher resolution map products. Large-scale field experiments present an ideal opportunity to develop methodologies for this scaling, by coupling in situ networks, temporary networks, and aerial mapping of soil moisture. During the Soil Moisture Active Passive Validation Experiments in 2015 (SMAPVEX15) in and around the USDA-ARS Walnut Gulch Experimental Watershed and LTAR site in southeastern Arizona, USA, a high density network of soil moisture stations was deployed across a sparse, permanent in situ network in coordination with intensive soil moisture sampling and an aircraft campaign. This watershed is also densely instrumented with precipitation gages (one gauge/0.57 km2) to monitor the North American Monsoon System, which dominates the hydrologic cycle during the summer months in this region. Using the precipitation and soil moisture time series values provided, a physically-based model is calibrated that will provide estimates at the 3km, 9km, and 36km scales. The results from this model will be compared with the point-scale gravimetric samples, aircraft-based sensor, and the satellite-based products retrieved from NASA's Soil Moisture Active Passive mission.
Diagnosing MJO Destabilization and Propagation with the Moisture and MSE Budgets
NASA Astrophysics Data System (ADS)
Maloney, Eric; Wolding, Brandon
2015-04-01
Novel diagnostics obtained as an extension of empirical orthogonal function analysis are used as a composting basis to gain insight into MJO dynamics through examination of reanalysis moisture and moist static energy budgets. The net effect of vertical moisture advection and cloud processes was found to be a modest positive feedback to column moisture anomalies during both enhanced and suppressed phases of the MJO. This positive feedback is regionally strengthened by anomalous surface fluxes of latent heat. The modulation of horizontal synoptic scale eddy mixing acts as a negative feedback to column moisture anomalies, while anomalous winds acting against the mean state moisture gradient aid in eastward propagation. These processes act in a systematic fashion across the Indian Ocean and oceanic regions of the Maritime Continent. The ability to approximately close the MSE budget serves an important role in constraining the moisture budget, whose residual is several times larger than the total and horizontal advective moisture tendencies. Comparison with TRMM precipitation anomalies suggests that the moisture budget residual results from an underestimation by ERAi of variations in both total precipitation and vertical moisture advection associated with the MJO. The results of this study support the concept of the MJO as a moisture-mode. This analysis is extended to examine the impact of boundary layer convergence driven by MJO SST anomalies on the vertically-integrated moisture budget. Results from a coupled version of the SP-CAM suggest that SST-driven moisture convergence anomalies are of a sufficient amplitude to be important for MJO propagation and destabilization, and may help explain why coupled models produce better simulations of the MJO than uncoupled models.
NASA Astrophysics Data System (ADS)
Rivera Villarreyes, C.; Baroni, G.; Oswald, S. E.
2012-12-01
Soil water content at the plot or hill-slope scale is an important link between local vadose zone hydrology and catchment hydrology. One largest initiative to cover the measuring gap of soil moisture between point scale and remote sensing observations is the COSMOS network (Zreda et al., 2012). Here, cosmic-ray neutron sensing, which may be more precisely named ground albedo neutron sensing (GANS), is applied. The measuring principle is based on the crucial role of hydrogen as neutron moderator compared to others landscape materials. Soil water content contained in a footprint of ca. 600 m diameter and a depth ranging down to a few decimeters is inversely correlated to the neutron flux at the air-ground interface. This approach is now implemented, e.g. in USA (Zreda et al., 2012) and Germany (Rivera Villarreyes et al., 2011), based on its simple installation and integral measurement of soil moisture at the small catchment scale. The present study performed Ground Albedo Neutron Sensing on farmland at two locations in Germany under different vegetative situations (cropped and bare field) and different seasonal conditions (summer, autumn and winter). Ground albedo neutrons were measured at (i) a farmland close to Potsdam and Berlin cropped with corn in 2010, sunflower in 2011 and winter rye in 2012, and (ii) a mountainous farmland catchment (Schaefertal, Harz Mountains) since middle 2011. In order to test this methodology, classical soil moisture devices and meteorological data were used for comparison. Moreover, several calibration approaches, role of vegetation cover and transferability of calibration parameters to different times and locations were also evaluated. Observations suggest that GANS can overcome the lack of data for hydrological processes at the intermediate scale. Soil moisture from GANS compared quantitatively with mean values derived from a network of classical devices under vegetated and non- vegetated conditions. The GANS approach responded well to precipitation events through summer and autumn, but soil water content estimations were affected by water stored in snow and partly biomass. Thus, when calibration parameters were transferred to different crops (e.g. from sunflower to rye), the changes in biomass water will have to be considered. Finally, these results imply that GANS measurements can be a reliable ground-truthing possibility as well as additional constraint for hydrological models. References (1) Rivera Villarreyes, C.A., Baroni, G., and Oswald, S.E. (2011): Integral quantification of seasonal soil moisture changes in farmland by cosmic-ray neutrons, Hydrol. Earth Syst. Sci., 15, 3843-3859. (2) Rivera Villarreyes, C.A., Baroni, G., and Oswald, S.E. (2012): Evaluation of the Ground Albedo Neutron Sensing (GANS) method for soil moisture estimations in different crop fields (in preparation for Hydrological Processes). (3) Zreda, M., Shuttleworth, W.J., Zeng, X., Zweck, C., Desilets, D., Franz, T., Rosolem, R., and Ferre, T.P.A. (2012): COSMOS: The COsmic-ray Soil Moisture Observing System. Hydrol. Earth Syst. Sci. Discuss., 9, 4505-4551.
NASA Astrophysics Data System (ADS)
Najibi, N.; Lu, M.; Devineni, N.
2017-12-01
Long duration floods cause substantial damages and prolonged interruptions to water resource facilities and critical infrastructure. We present a novel generalized statistical and physical based model for flood duration with a deeper understanding of dynamically coupled nexus of the land surface wetness, effective atmospheric circulation and moisture transport/release. We applied the model on large reservoirs in the Missouri River Basin. The results indicate that the flood duration is not only a function of available moisture in the air, but also the antecedent condition of the blocking system of atmospheric pressure, resulting in enhanced moisture convergence, as well as the effectiveness of moisture condensation process leading to release. Quantifying these dynamics with a two-layer climate informed Bayesian multilevel model, we explain more than 80% variations in flood duration. The model considers the complex interaction between moisture transport, synoptic-to-large-scale atmospheric circulation pattern, and the antecedent wetness condition in the basin. Our findings suggest that synergy between a large low-pressure blocking system and a higher rate of divergent wind often triggers a long duration flood, and the prerequisite for moisture supply to trigger such event is moderate, which is more associated with magnitude than duration. In turn, this condition causes an extremely long duration flood if the surface wetness rate advancing to the flood event was already increased.
Sensitivity of transpiration to subsurface properties: Exploration with a 1-D model
Vrettas, Michail D.; Fung, Inez Y.
2017-05-04
The amount of moisture transpired by vegetation is critically tied to the moisture supply accessible to the root zone. In a Mediterranean climate, integrated evapotranspiration (ET) is typically greater in the dry summer when there is an uninterrupted period of high insolation. We present a 1-D model to explore the subsurface factors that may sustain ET through the dry season. The model includes a stochastic parameterization of hydraulic conductivity, root water uptake efficiency, and hydraulic redistribution by plant roots. Model experiments vary the precipitation, the magnitude and seasonality of ET demand, as well as rooting profiles and rooting depths ofmore » the vegetation. The results show that the amount of subsurface moisture remaining at the end of the wet winter is determined by the competition among abundant precipitation input, fast infiltration, and winter ET demand. The weathered bedrock retains math formula of the winter rain and provides a substantial moisture reservoir that may sustain ET of deep-rooted (>8 m) trees through the dry season. A small negative feedback exists in the root zone, where the depletion of moisture by ET decreases hydraulic conductivity and enhances the retention of moisture. Hence, hydraulic redistribution by plant roots is impactful in a dry season, or with a less conductive subsurface. Suggestions for implementing the model in the CESM are discussed.« less
Advances in Land Data Assimilation at the NASA Goddard Space Flight Center
NASA Technical Reports Server (NTRS)
Reichle, Rolf
2009-01-01
Research in land surface data assimilation has grown rapidly over the last decade. In this presentation we provide a brief overview of key research contributions by the NASA Goddard Space Flight Center (GSFC). The GSFC contributions to land assimilation primarily include the continued development and application of the Land Information System (US) and the ensemble Kalman filter (EnKF). In particular, we have developed a method to generate perturbation fields that are correlated in space, time, and across variables and that permit the flexible modeling of errors in land surface models and observations, along with an adaptive filtering approach that estimates observation and model error input parameters. A percentile-based scaling method that addresses soil moisture biases in model and observational estimates opened the path to the successful application of land data assimilation to satellite retrievals of surface soil moisture. Assimilation of AMSR-E surface soil moisture retrievals into the NASA Catchment model provided superior surface and root zone assimilation products (when validated against in situ measurements and compared to the model estimates or satellite observations alone). The multi-model capabilities of US were used to investigate the role of subsurface physics in the assimilation of surface soil moisture observations. Results indicate that the potential of surface soil moisture assimilation to improve root zone information is higher when the surface to root zone coupling is stronger. Building on this experience, GSFC leads the development of the Level 4 Surface and Root-Zone Soil Moisture (L4_SM) product for the planned NASA Soil-Moisture-Active-Passive (SMAP) mission. A key milestone was the design and execution of an Observing System Simulation Experiment that quantified the contribution of soil moisture retrievals to land data assimilation products as a function of retrieval and land model skill and yielded an estimate of the error budget for the SMAP L4_SM product. Terrestrial water storage observations from GRACE satellite system were also successfully assimilated into the NASA Catchment model and provided improved estimates of groundwater variability when compared to the model estimates alone. Moreover, satellite-based land surface temperature (LST) observations from the ISCCP archive were assimilated using a bias estimation module that was specifically designed for LST assimilation. As with soil moisture, LST assimilation provides modest yet statistically significant improvements when compared to the model or satellite observations alone. To achieve the improvement, however, the LST assimilation algorithm must be adapted to the specific formulation of LST in the land model. An improved method for the assimilation of snow cover observations was also developed. Finally, the coupling of LIS to the mesoscale Weather Research and Forecasting (WRF) model enabled investigations into how the sensitivity of land-atmosphere interactions to the specific choice of planetary boundary layer scheme and land surface model varies across surface moisture regimes, and how it can be quantified and evaluated against observations. The on-going development and integration of land assimilation modules into the Land Information System will enable the use of GSFC software with a variety of land models and make it accessible to the research community.
Bourlieu, C; Guillard, V; Vallès-Pamiès, B; Guilbert, S; Gontard, N
2009-05-01
Control of moisture transfer inside composite food products or between food and its environment remains today a major challenge in food preservation. A wide rage of film-forming compounds is now available and facilitates tailoring moisture barriers with optimized functional properties. Despite these huge potentials, a realistic assessment of the film or coating efficacy is still critical. Due to nonlinear water sorption isotherms, water-dependent diffusivities, and variations of physical state, modelling transport phenomena through edible barriers is complex. Water vapor permeability can hardly be considered as an inherent property of films and only gives a relative indication of the barrier efficacy. The formal or mechanistic models reported in literature that describe the influence of testing conditions on the barrier properties of edible films are reviewed and discussed. Most of these models have been validated on a narrow range of conditions. Conversely, few original predictive models based on Fick's Second Law have been developed to assess shelf-life extension of food products including barriers. These models, assuming complex and realistic hypothesis, have been validated in various model foods. The development of nondestructive methods of moisture content measurement should speed up model validation and allow a better comprehension of moisture transfer through edible films.
A moist aquaplanet variant of the Held–Suarez test for atmospheric model dynamical cores
DOE Office of Scientific and Technical Information (OSTI.GOV)
Thatcher, Diana R.; Jablonowski, Christiane
A moist idealized test case (MITC) for atmospheric model dynamical cores is presented. The MITC is based on the Held–Suarez (HS) test that was developed for dry simulations on “a flat Earth” and replaces the full physical parameterization package with a Newtonian temperature relaxation and Rayleigh damping of the low-level winds. This new variant of the HS test includes moisture and thereby sheds light on the nonlinear dynamics–physics moisture feedbacks without the complexity of full-physics parameterization packages. In particular, it adds simplified moist processes to the HS forcing to model large-scale condensation, boundary-layer mixing, and the exchange of latent and sensible heat betweenmore » the atmospheric surface and an ocean-covered planet. Using a variety of dynamical cores of the National Center for Atmospheric Research (NCAR)'s Community Atmosphere Model (CAM), this paper demonstrates that the inclusion of the moist idealized physics package leads to climatic states that closely resemble aquaplanet simulations with complex physical parameterizations. This establishes that the MITC approach generates reasonable atmospheric circulations and can be used for a broad range of scientific investigations. This paper provides examples of two application areas. First, the test case reveals the characteristics of the physics–dynamics coupling technique and reproduces coupling issues seen in full-physics simulations. In particular, it is shown that sudden adjustments of the prognostic fields due to moist physics tendencies can trigger undesirable large-scale gravity waves, which can be remedied by a more gradual application of the physical forcing. Second, the moist idealized test case can be used to intercompare dynamical cores. These examples demonstrate the versatility of the MITC approach and suggestions are made for further application areas. Furthermore, the new moist variant of the HS test can be considered a test case of intermediate complexity.« less
A moist aquaplanet variant of the Held–Suarez test for atmospheric model dynamical cores
Thatcher, Diana R.; Jablonowski, Christiane
2016-04-04
A moist idealized test case (MITC) for atmospheric model dynamical cores is presented. The MITC is based on the Held–Suarez (HS) test that was developed for dry simulations on “a flat Earth” and replaces the full physical parameterization package with a Newtonian temperature relaxation and Rayleigh damping of the low-level winds. This new variant of the HS test includes moisture and thereby sheds light on the nonlinear dynamics–physics moisture feedbacks without the complexity of full-physics parameterization packages. In particular, it adds simplified moist processes to the HS forcing to model large-scale condensation, boundary-layer mixing, and the exchange of latent and sensible heat betweenmore » the atmospheric surface and an ocean-covered planet. Using a variety of dynamical cores of the National Center for Atmospheric Research (NCAR)'s Community Atmosphere Model (CAM), this paper demonstrates that the inclusion of the moist idealized physics package leads to climatic states that closely resemble aquaplanet simulations with complex physical parameterizations. This establishes that the MITC approach generates reasonable atmospheric circulations and can be used for a broad range of scientific investigations. This paper provides examples of two application areas. First, the test case reveals the characteristics of the physics–dynamics coupling technique and reproduces coupling issues seen in full-physics simulations. In particular, it is shown that sudden adjustments of the prognostic fields due to moist physics tendencies can trigger undesirable large-scale gravity waves, which can be remedied by a more gradual application of the physical forcing. Second, the moist idealized test case can be used to intercompare dynamical cores. These examples demonstrate the versatility of the MITC approach and suggestions are made for further application areas. Furthermore, the new moist variant of the HS test can be considered a test case of intermediate complexity.« less
Combined evaluation of optical and microwave satellite dataset for soil moisture deficit estimation
NASA Astrophysics Data System (ADS)
Srivastava, Prashant K.; Han, Dawei; Islam, Tanvir; Singh, Sudhir Kumar; Gupta, Manika; Gupta, Dileep Kumar; Kumar, Pradeep
2016-04-01
Soil moisture is a key variable responsible for water and energy exchanges from land surface to the atmosphere (Srivastava et al., 2014). On the other hand, Soil Moisture Deficit (or SMD) can help regulating the proper use of water at specified time to avoid any agricultural losses (Srivastava et al., 2013b) and could help in preventing natural disasters, e.g. flood and drought (Srivastava et al., 2013a). In this study, evaluation of Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) and soil moisture from Soil Moisture and Ocean Salinity (SMOS) satellites are attempted for prediction of Soil Moisture Deficit (SMD). Sophisticated algorithm like Adaptive Neuro Fuzzy Inference System (ANFIS) is used for prediction of SMD using the MODIS and SMOS dataset. The benchmark SMD estimated from Probability Distributed Model (PDM) over the Brue catchment, Southwest of England, U.K. is used for all the validation. The performances are assessed in terms of Nash Sutcliffe Efficiency, Root Mean Square Error and the percentage of bias between ANFIS simulated SMD and the benchmark. The performance statistics revealed a good agreement between benchmark and the ANFIS estimated SMD using the MODIS dataset. The assessment of the products with respect to this peculiar evidence is an important step for successful development of hydro-meteorological model and forecasting system. The analysis of the satellite products (viz. SMOS soil moisture and MODIS LST) towards SMD prediction is a crucial step for successful hydrological modelling, agriculture and water resource management, and can provide important assistance in policy and decision making. Keywords: Land Surface Temperature, MODIS, SMOS, Soil Moisture Deficit, Fuzzy Logic System References: Srivastava, P.K., Han, D., Ramirez, M.A., Islam, T., 2013a. Appraisal of SMOS soil moisture at a catchment scale in a temperate maritime climate. Journal of Hydrology 498, 292-304. Srivastava, P.K., Han, D., Rico-Ramirez, M.A., Al-Shrafany, D., Islam, T., 2013b. Data fusion techniques for improving soil moisture deficit using SMOS satellite and WRF-NOAH land surface model. Water Resources Management 27, 5069-5087. Srivastava, P.K., Han, D., Rico-Ramirez, M.A., O'Neill, P., Islam, T., Gupta, M., 2014. Assessment of SMOS soil moisture retrieval parameters using tau-omega algorithms for soil moisture deficit estimation. Journal of Hydrology 519, 574-587.
NASA Technical Reports Server (NTRS)
Field, Richard T.
1990-01-01
SOILSIM, a digital model of energy and moisture fluxes in the soil and above the soil surface, is presented. It simulates the time evolution of soil temperature and moisture, temperature of the soil surface and plant canopy the above surface, and the fluxes of sensible and latent heat into the atmosphere in response to surface weather conditions. The model is driven by simple weather observations including wind speed, air temperature, air humidity, and incident radiation. The model intended to be useful in conjunction with remotely sensed information of the land surface state, such as surface brightness temperature and soil moisture, for computing wide area evapotranspiration.
NASA Astrophysics Data System (ADS)
Florian, Mallet; Vincent, Marc; Johnny, Douvinet; Philippe, Rossello; Bouteiller Caroline, Le; Jean-Philippe, Malet; Julien, Gance
2015-04-01
Runoff generation in the headwater catchments in various land use conditions still remain a core issue in catchment hydrology (Uhlenbrook S. et al., 2003). Vegetation has a strong impact on flows distribution (interception, infiltration, evapotranspiration, runoff) but the relative influence of these mechanisms according to geomorphological determinants is still not totally understood. The "ORE Draix" located in the Alpes-de-Haute-Provence (France) allows to study these parameters using experimental watersheds equipped with a long term monitoring instrumentation (rainfall, streamflow, water, soil and air temperature, soil erosion, soil moisture...). These marl torrential watersheds have a peculiar hydrological behavior during flood events with large outflow differences between the wooded and the bare areas. We try to identify the runoff production factors by studying water storage/drainage processes within the first 30 cm depth of soil (Wilson et al., 2003, Western et al., 2004). Soil moisture can explain runoff during floods, that's why we try to upscale this variable at the watershed level. Unlike studies on soil moisture monitoring in agricultural context (flat areas), conventional remote sensing methods are difficult to apply to the badlands (elevation between 1500 masl and 1800 masl, approximately 1km² areas, steep slopes, various land uses) (Bagdhadi, 2005). This difficulty can be overcome by measuring soil moisture at different spatial (point, plot, slope, catchment) and time scales (event, season, year) using innovative approaches. In this context, we propose a monitoring of soil moisture based on geostatistical treatments crossed with measurements at different scales. These measures are provided from ground and airborne sensors deployment. Point measurements are ensured at a very high time frequency using capacitance probes. At an intermediate level, a slope is equipped with a DTS sensor (distributed temperature sensing) to obtain a 2D estimate of soilwater flow of from the surface to - 30 cm. Another distributed approach will be carried out from a measurement of cosmic neutrons mitigation (Cosmic ray sensor) to estimate a soil moisture averaged value over 40 ha (Zreda et al., 2012). Finally, the smallest scale (slope and catchment) will be approached using remote sensing with a drone and/or satellite imagery (IR, passive and active microwave). This concatenation of scales with different combinations of time steps should enable us to better understand the hydrological dynamics in torrential environments. It aims at mapping the stormflow generation on a catchment at the flood scale and defining the main determinants of surface runoff. These results may contribute to the improvement of runoff simulation and flood prediction. References : Uhlenbrook S., J.J. McDonnell and C. Leibundgut, 2003. Preface: Runoff generation implications for river basin modelling. Hydrological Processes, Special Issue, 17: 197-198. Andrew W. Western, Sen-Lin Zhou, Rodger B. Grayson, Thomas A. MacMahon, Günter Blöshl, David J. Wilson, 2004. Spatial correlation of soil moisture in small catchments and its relationship to dominant spatial hydrological processes. Journal of Hydrology 286. Zreda, M., Shuttleworth WJ., Zeng X., Zweck C., Desilets D., Franz TE. et al., 2012. COSMOS: the COsmic-ray Soil Moisture Observing System. Hydrology and Earth System Sciences, 16(11): 4079-4099.
A study of 2014 record drought in India with CFSv2 model: role of water vapor transport
NASA Astrophysics Data System (ADS)
Ramakrishna, S. S. V. S.; Brahmananda Rao, V.; Srinivasa Rao, B. R.; Hari Prasad, D.; Nanaji Rao, N.; Panda, Roshmitha
2017-07-01
The Indian summer monsoon season of 2014 was erratic and ended up with a seasonal rainfall deficit of 12 % and a record drought in June. In this study we analyze the moisture transport characteristics for the monsoon season of 2014 using both NCEP FNL reanalysis (FNL) and CFSv2 (CFS) model data. In FNL, in June 2014 there was a large area of divergence of moisture flux. In other months also there was lesser flux. This probably is the cause of 2014 drought. The CFS model overestimated the drought and it reproduces poorly the observed rainfall over central India (65E-95E; 5N-35N). The correlation coefficient (CC) between the IMD observed rainfall and CFS model rainfall is only 0.1 while the CC between rainfall and moisture flux convergence in CFS model is only 0.20 and with FNL data -0.78. This clearly shows that the CFS model has serious difficulty in reproducing the moisture flux convergence and rainfall. We found that the rainfall variations are strongly related to the moisture convergence or divergence. The hypothesis of Krishnamurti et al. (J Atmos Sci 67:3423-3441, 2010) namely the intrusion of west African desert air and the associated low convective available potential energy inhibiting convection and rainfall shows some promise to explain dry spells in Indian summer monsoon. However, the rainfall or lack of it is mainly explained by convergence or divergence of moisture flux.
NASA Astrophysics Data System (ADS)
Gupta, Manika; Bolten, John; Lakshmi, Venkat
2015-04-01
This work addresses the improvement of available water capacity by developing a technique for estimating soil hydraulic parameters through the utilization of satellite-retrieved near surface soil moisture. The prototype involves the usage of Monte Carlo analysis to assimilate historical remote sensing soil moisture data available from the Advanced Microwave Scanning Radiometer (AMSR-E) within the hydrological model. The main hypothesis used in this study is that near-surface soil moisture data contain useful information that can describe the effective hydrological conditions of the basin such that when appropriately In the method followed in this study the hydraulic parameters are derived directly from information on the soil moisture state at the AMSR-E footprint scale and the available water capacity is derived for the root zone by coupling of AMSR-E soil moisture with the physically-based hydrological model. The available capacity water, which refers to difference between the field capacity and wilting point of the soil and represent the soil moisture content at 0.33 bar and 15 bar respectively is estimated from the soil hydraulic parameters using the van Genuchten equation. The initial ranges of soil hydraulic parameters are taken in correspondence with the values available from the literature based on Soil Survey Geographic (SSURGO) database within the particular AMSR-E footprint. Using the Monte Carlo simulation, the ranges are narrowed in the region where simulation shows a good match between predicted and near-surface soil moisture from AMSR-E. In this study, the uncertainties in accurately determining the parameters of the nonlinear soil water retention function for large-scale hydrological modeling is the focus of the development of the Bayesian framework. Thus, the model forecasting has been combined with the observational information to optimize the model state and the soil hydraulic parameters simultaneously. The optimization process is divided into two steps during one time interval: the state variable is optimized through the state filter and the optimal parameter values are then transferred for retrieving soil moisture. However, soil moisture from sensors such as AMSR-E can only be retrieved for the top few centimeters of soil. So, for the present study, a homogeneous soil system has been considered. By assimilating this information into the model, the accuracy of model structure in relating surface moisture dynamics to deeper soil profiles can be ascertained. 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 alongwith the available water capacity, the root mean square error (RMSE) and Mean Bias error (MBE) are used to measure the performance of the soil moisture simulations. The optimized parameters as compared to the pedo-transfer based parameters were found to reduce the RMSE from 0.14 to 0.04 and 0.15 to 0.07 in surface layer and root zone respectively.
B.L. Yashwanth; B. Shotorban; S. Mahalingam; C.W. Lautenberger; David Weise
2016-01-01
The effects of thermal radiation and moisture content on the pyrolysis and gas phase ignition of a solid fuel element containing high moisture content were investigated using the coupled Gpyro3D/FDS models. The solid fuel has dimensions of a typical Arctostaphylos glandulosa leaf which is modeled as thin cellulose subjected to radiative heating on...
Native Plant Uptake Model for Radioactive Waste Disposal Areas at the Nevada Test Site
DOE Office of Scientific and Technical Information (OSTI.GOV)
BROWN,THERESA J.; WIRTH,SHARON
1999-09-01
This report defines and defends the basic framework, methodology, and associated input parameters for modeling plant uptake of radionuclides for use in Performance Assessment (PA) activities of Radioactive Waste Management Sites (RWMS) at the Nevada Test Site (NTS). PAs are used to help determine whether waste disposal configurations meet applicable regulatory standards for the protection of human health, the environment, or both. Plants adapted to the arid climate of the NTS are able to rapidly capture infiltrating moisture. In addition to capturing soil moisture, plant roots absorb nutrients, minerals, and heavy metals, transporting them within the plant to the above-groundmore » biomass. In this fashion, plant uptake affects the movement of radionuclides. The plant uptake model presented reflects rooting characteristics important to plant uptake, biomass turnover rates, and the ability of plants to uptake radionuclides from the soil. Parameters are provided for modeling plant uptake and estimating surface contaminant flux due to plant uptake under both current and potential future climate conditions with increased effective soil moisture. The term ''effective moisture'' is used throughout this report to indicate the soil moisture that is available to plants and is intended to be inclusive of all the variables that control soil moisture at a site (e.g., precipitation, temperature, soil texture, and soil chemistry). Effective moisture is a concept used to simplify a number of complex, interrelated soil processes for which there are too little data to model actual plant available moisture. The PA simulates both the flux of radionuclides across the land surface and the potential dose to humans from that flux. Surface flux is modeled here as the amount of soil contamination that is transferred from the soil by roots and incorporated into aboveground biomass. Movement of contaminants to the surface is the only transport mechanism evaluated with the model presented here. Parameters necessary for estimating surface contaminant flux due to native plants expected to inhabit the NTS RWMSS are developed in this report. The model is specific to the plant communities found at the NTS and is designed for both short-term (<1,000 years) and long-term (>1,000 years) modeling efforts. While the model has been crafted for general applicability to any NTS PA, the key radionuclides considered are limited to the transuranic (TRU) wastes disposed of at the NTS.« less
Using lagged dependence to identify (de)coupled surface and subsurface soil moisture values
NASA Astrophysics Data System (ADS)
Carranza, Coleen D. U.; van der Ploeg, Martine J.; Torfs, Paul J. J. F.
2018-04-01
Recent advances in radar remote sensing popularized the mapping of surface soil moisture at different spatial scales. Surface soil moisture measurements are used in combination with hydrological models to determine subsurface soil moisture values. However, variability of soil moisture across the soil column is important for estimating depth-integrated values, as decoupling between surface and subsurface can occur. In this study, we employ new methods to investigate the occurrence of (de)coupling between surface and subsurface soil moisture. Using time series datasets, lagged dependence was incorporated in assessing (de)coupling with the idea that surface soil moisture conditions will be reflected at the subsurface after a certain delay. The main approach involves the application of a distributed-lag nonlinear model (DLNM) to simultaneously represent both the functional relation and the lag structure in the time series. The results of an exploratory analysis using residuals from a fitted loess function serve as a posteriori information to determine (de)coupled values. Both methods allow for a range of (de)coupled soil moisture values to be quantified. Results provide new insights into the decoupled range as its occurrence among the sites investigated is not limited to dry conditions.
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.
Water Sorption Isotherm of Pea Starch Edible Films and Prediction Models.
Saberi, Bahareh; Vuong, Quan V; Chockchaisawasdee, Suwimol; Golding, John B; Scarlett, Christopher J; Stathopoulos, Costas E
2015-12-24
The moisture sorption isotherm of pea starch films prepared with various glycerol contents as plasticizer was investigated at different storage relative humidities (11%-96% RH) and at 5 ± 1, 15 ± 1, 25 ± 1 and 40 ± 1 °C by using gravimetric method. The results showed that the equilibrium moisture content of all films increased substantially above a w = 0.6. Films plasticized with glycerol, under all temperatures and RH conditions (11%-96%), adsorbed more moisture resulting in higher equilibrium moisture contents. Reduction of the temperature enhanced the equilibrium moisture content and monolayer water of the films. The obtained experimental data were fitted to different models including two-parameter equations (Oswin, Henderson, Brunauer-Emmitt-Teller (BET), Flory-Huggins, and Iglesias-Chirife), three-parameter equations Guggenhiem-Anderson-deBoer (GAB), Ferro-Fontan, and Lewicki) and a four-parameter equation (Peleg). The three-parameter Lewicki model was found to be the best-fitted model for representing the experimental data within the studied temperatures and whole range of relative humidities (11%-98%). Addition of glycerol increased the net isosteric heat of moisture sorption of pea starch film. The results provide important information with estimating of stability and functional characteristics of the films in various environments.
NASA Astrophysics Data System (ADS)
Cotterman, K. A.; Follum, M. L.; Pradhan, N. R.; Niemann, J. D.
2017-12-01
Flooding impacts numerous aspects of society, from localized flash floods to continental-scale flood events. Many numerical flood models focus solely on riverine flooding, with some capable of capturing both localized and continental-scale flood events. However, these models neglect flooding away from channels that are related to excessive ponding, typically found in areas with flat terrain and poorly draining soils. In order to obtain a holistic view of flooding, we combine flood results from the Streamflow Prediction Tool (SPT), a riverine flood model, with soil moisture downscaling techniques to determine if a better representation of flooding is obtained. This allows for a more holistic understanding of potential flood prone areas, increasing the opportunity for more accurate warnings and evacuations during flooding conditions. Thirty-five years of near-global historical streamflow is reconstructed with continental-scale flow routing of runoff from global land surface models. Elevation data was also obtained worldwide, to establish a relationship between topographic attributes and soil moisture patterns. Derived soil moisture data is validated against observed soil moisture, increasing confidence in the ability to accurately capture soil moisture patterns. Potential flooding situations can be examined worldwide, with this study focusing on the United States, Central America, and the Philippines.
Water Sorption Isotherm of Pea Starch Edible Films and Prediction Models
Saberi, Bahareh; Vuong, Quan V.; Chockchaisawasdee, Suwimol; Golding, John B.; Scarlett, Christopher J.; Stathopoulos, Costas E.
2015-01-01
The moisture sorption isotherm of pea starch films prepared with various glycerol contents as plasticizer was investigated at different storage relative humidities (11%–96% RH) and at 5 ± 1, 15 ± 1, 25 ± 1 and 40 ± 1 °C by using gravimetric method. The results showed that the equilibrium moisture content of all films increased substantially above aw = 0.6. Films plasticized with glycerol, under all temperatures and RH conditions (11%–96%), adsorbed more moisture resulting in higher equilibrium moisture contents. Reduction of the temperature enhanced the equilibrium moisture content and monolayer water of the films. The obtained experimental data were fitted to different models including two-parameter equations (Oswin, Henderson, Brunauer–Emmitt–Teller (BET), Flory–Huggins, and Iglesias–Chirife), three-parameter equations Guggenhiem–Anderson–deBoer (GAB), Ferro–Fontan, and Lewicki) and a four-parameter equation (Peleg). The three-parameter Lewicki model was found to be the best-fitted model for representing the experimental data within the studied temperatures and whole range of relative humidities (11%–98%). Addition of glycerol increased the net isosteric heat of moisture sorption of pea starch film. The results provide important information with estimating of stability and functional characteristics of the films in various environments. PMID:28231096
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.
NASA Astrophysics Data System (ADS)
Zhang, Hongjuan; Kurtz, Wolfgang; Kollet, Stefan; Vereecken, Harry; Franssen, Harrie-Jan Hendricks
2018-01-01
The linkage between root zone soil moisture and groundwater is either neglected or simplified in most land surface models. The fully-coupled subsurface-land surface model TerrSysMP including variably saturated groundwater dynamics is used in this work. We test and compare five data assimilation methodologies for assimilating groundwater level data via the ensemble Kalman filter (EnKF) to improve root zone soil moisture estimation with TerrSysMP. Groundwater level data are assimilated in the form of pressure head or soil moisture (set equal to porosity in the saturated zone) to update state vectors. In the five assimilation methodologies, the state vector contains either (i) pressure head, or (ii) log-transformed pressure head, or (iii) soil moisture, or (iv) pressure head for the saturated zone only, or (v) a combination of pressure head and soil moisture, pressure head for the saturated zone and soil moisture for the unsaturated zone. These methodologies are evaluated in synthetic experiments which are performed for different climate conditions, soil types and plant functional types to simulate various root zone soil moisture distributions and groundwater levels. The results demonstrate that EnKF cannot properly handle strongly skewed pressure distributions which are caused by extreme negative pressure heads in the unsaturated zone during dry periods. This problem can only be alleviated by methodology (iii), (iv) and (v). The last approach gives the best results and avoids unphysical updates related to strongly skewed pressure heads in the unsaturated zone. If groundwater level data are assimilated by methodology (iii), EnKF fails to update the state vector containing the soil moisture values if for (almost) all the realizations the observation does not bring significant new information. Synthetic experiments for the joint assimilation of groundwater levels and surface soil moisture support methodology (v) and show great potential for improving the representation of root zone soil moisture.
Revealing Invisible Water: Moisture Recycling as an Ecosystem Service.
Keys, Patrick W; Wang-Erlandsson, Lan; Gordon, Line J
2016-01-01
An ecosystem service is a benefit derived by humanity that can be traced back to an ecological process. Although ecosystem services related to surface water have been thoroughly described, the relationship between atmospheric water and ecosystem services has been mostly neglected, and perhaps misunderstood. Recent advances in land-atmosphere modeling have revealed the importance of terrestrial ecosystems for moisture recycling. In this paper, we analyze the extent to which vegetation sustains the supply of atmospheric moisture and precipitation for downwind beneficiaries, globally. We simulate land-surface evaporation with a global hydrology model and track changes to moisture recycling using an atmospheric moisture budget model, and we define vegetation-regulated moisture recycling as the difference in moisture recycling between current vegetation and a hypothetical desert world. Our results show that nearly a fifth of annual average precipitation falling on land is from vegetation-regulated moisture recycling, but the global variability is large, with many places receiving nearly half their precipitation from this ecosystem service. The largest potential impacts for changes to this ecosystem service are land-use changes across temperate regions in North America and Russia. Likewise, in semi-arid regions reliant on rainfed agricultural production, land-use change that even modestly reduces evaporation and subsequent precipitation, could significantly affect human well-being. We also present a regional case study in the Mato Grosso region of Brazil, where we identify the specific moisture recycling ecosystem services associated with the vegetation in Mato Grosso. We find that Mato Grosso vegetation regulates some internal precipitation, with a diffuse region of benefit downwind, primarily to the south and east, including the La Plata River basin and the megacities of Sao Paulo and Rio de Janeiro. We synthesize our global and regional results into a generalized framework for describing moisture recycling as an ecosystem service. We conclude that future work ought to disentangle whether and how this vegetation-regulated moisture recycling interacts with other ecosystem services, so that trade-offs can be assessed in a comprehensive and sustainable manner.
NASA Astrophysics Data System (ADS)
Mehmood, S.; Ashfaq, M.; Evans, K. J.; Black, R. X.; Hsu, H. H.
2017-12-01
Extreme precipitation during summer season has shown an increasing trend across South Asia in recent decades, causing an exponential increase in weather related losses. Here we combine a cluster analyses technique (Agglomerative Hierarchical Clustering) with a Lagrangian based moisture analyses technique to investigate potential commonalities in the characteristics of the large scale meteorological patterns (LSMP) and moisture anomalies associated with the observed extreme precipitation events, and their representation in the Department of Energy model ACME. Using precipitation observations from the Indian Meteorological Department (IMD) and Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation (APHRODITE), and atmospheric variables from Era-Interim Reanalysis, we first identify LSMP both in upper and lower troposphere that are responsible for wide spread precipitation extreme events during 1980-2015 period. For each of the selected extreme event, we perform moisture source analyses to identify major evaporative sources that sustain anomalous moisture supply during the course of the event, with a particular focus on local terrestrial moisture recycling. Further, we perform similar analyses on two sets of five-member ensemble of ACME model (1-degree and ¼ degree) to investigate the ability of ACME model in simulating precipitation extremes associated with each of the LSMP patterns and associated anomalous moisture sourcing from each of the terrestrial and oceanic evaporative region. Comparison of low and high-resolution model configurations provides insight about the influence of horizontal grid spacing in the simulation of extreme precipitation and the governing mechanisms.
NASA Astrophysics Data System (ADS)
Wang, Guiling
2005-12-01
This study examines the impact of greenhouse gas warming on soil moisture based on predictions of 15 global climate models by comparing the after-stabilization climate in the SRESA1b experiment with the pre-industrial control climate. The models are consistent in predicting summer dryness and winter wetness in only part of the northern middle and high latitudes. Slightly over half of the models predict year-round wetness in central Eurasia and/or year-round dryness in Siberia and mid-latitude Northeast Asia. One explanation is offered that relates such lack of seasonality to the carryover effect of soil moisture storage from season to season. In the tropics and subtropics, a decrease of soil moisture is the dominant response. The models are especially consistent in predicting drier soil over the southwest North America, Central America, the Mediterranean, Australia, and the South Africa in all seasons, and over much of the Amazon and West Africa in the June July August (JJA) season and the Asian monsoon region in the December January February (DJF) season. Since the only major areas of future wetness predicted with a high level of model consistency are part of the northern middle and high latitudes during the non-growing season, it is suggested that greenhouse gas warming will cause a worldwide agricultural drought. Over regions where there is considerable consistency among the analyzed models in predicting the sign of soil moisture changes, there is a wide range of magnitudes of the soil moisture response, indicating a high degree of model dependency in terrestrial hydrological sensitivity. A major part of the inter-model differences in the sensitivity of soil moisture response are attributable to differences in land surface parameterization.
NASA Technical Reports Server (NTRS)
Case, Jonathan L.; Blakenship, Clay B.; Zavodsky, Bradley T.
2014-01-01
As part of the NASA Soil Moisture Active Passive (SMAP) Early Adopter (EA) program, the NASA Shortterm Prediction Research and Transition (SPoRT) Center has implemented a data assimilation (DA) routine into the NASA Land Information System (LIS) for soil moisture retrievals from the European Space Agency's Soil Moisture Ocean Salinity (SMOS) satellite. The SMAP EA program promotes application-driven research to provide a fundamental understanding of how SMAP data products will be used to improve decision-making at operational agencies. SPoRT has partnered with select NOAA/NWS Weather Forecast Offices (WFOs) that use output from a real-time regional configuration of LIS, without soil moisture DA, to initialize local numerical weather prediction (NWP) models and enhance situational awareness. Improvements to local NWP with the current LIS have been demonstrated; however, a better representation of the land surface through assimilation of SMOS (and eventually SMAP) retrievals is expected to lead to further model improvement, particularly during warm-season months. SPoRT will collaborate with select WFOs to assess the impact of soil moisture DA on operational forecast situations. Assimilation of the legacy SMOS instrument data provides an opportunity to develop expertise in preparation for using SMAP data products shortly after the scheduled launch on 5 November 2014. SMOS contains a passive L-band radiometer that is used to retrieve surface soil moisture at 35-km resolution with an accuracy of 0.04 cu cm cm (exp -3). SMAP will feature a comparable passive L-band instrument in conjunction with a 3-km resolution active radar component of slightly degraded accuracy. A combined radar-radiometer product will offer unprecedented global coverage of soil moisture at high spatial resolution (9 km) for hydrometeorological applications, balancing the resolution and accuracy of the active and passive instruments, respectively. The LIS software framework manages land surface model (LSM) simulations and includes an Ensemble Kalman Filter for conducting land surface DA. SPoRT has added a module to read, quality-control and bias-correct swaths of Level II SMOS soil moisture retrievals prior to assimilation within LIS. The impact of SMOS DA is being tested using the Noah LSM. Experiments are being conducted to examine the impacts of SMOS soil moisture DA on the resulting LISNoah fields and subsequent NWP simulations using the Weather Research and Forecasting (WRF) model initialized with LIS-Noah output. LIS-Noah soil moisture will be validated against in situ observations from Texas A&M's North American Soil Moisture Database to reveal the impact and possible improvement in soil moisture trends through DA. WRF model NWP case studies will test the impacts of DA on the simulated near-surface and boundary-layer environments, and precipitation during both quiescent and disturbed weather scenarios. Emphasis will be placed on cases with large analysis increments, especially due to contributions from regional irrigation patterns that are not represented by precipitation input in the baseline LIS-Noah run. This poster presentation will describe the soil moisture DA methodology and highlight LIS-Noah and WRF simulation results with and without assimilation.
Investigations of the unsaturated zone at two radioactive waste disposal sites in Lithuania.
Skuratovič, Žana; Mažeika, Jonas; Petrošius, Rimantas; Martma, Tõnu
2016-01-01
The unsaturated zone is an important part of the water cycle, governed by many hydrological and hydrogeological factors and processes and provide water and nutrients to the terrestrial ecosystem. Besides, the soils of the unsaturated zone are regarded as the first natural barrier to a large extent and are able to limit the spread of contaminants depending on their properties. The unsaturated zone provides a linkage between atmospheric moisture, groundwater, and seepage of groundwater to streams, lakes, or other surface water bodies. The major difference between water flow in saturated and unsaturated soils is that the hydraulic conductivity, which is conventionally assumed to be a constant in saturated soils, is a function of the degree of saturation or matrix suction in the unsaturated soils. In Lithuania, low and intermediate level radioactive wastes generated from medicine, industry and research were accumulated at the Maisiagala radioactive waste repository. Short-lived low and intermediate levels radioactive waste, generated during the operation of the Ignalina Nuclear Power Plant (INPP) and arising after the INPP decommissioning will be disposed of in the near surface repository close to the INPP (Stabatiske site). Extensive data sets of the hydraulic properties and water content attributed to unsaturated zone soil profiles of the two radioactive waste disposal sites have been collected and summarized. Globally widespread radionuclide tritium ((3)H) and stable isotope ratio ((18)O/(16)O and (2)H/(1)H) distribution features were determined in precipitation, unsaturated zone soil moisture profiles and groundwater.
Spatio-Temporal Distribution of Bark and Ambrosia Beetles in a Brazilian Tropical Dry Forest.
Macedo-Reis, Luiz Eduardo; Novais, Samuel Matos Antunes de; Monteiro, Graziela França; Flechtmann, Carlos Alberto Hector; Faria, Maurício Lopes de; Neves, Frederico de Siqueira
2016-01-01
Bark and the ambrosia beetles dig into host plants and live most of their lives in concealed tunnels. We assessed beetle community dynamics in tropical dry forest sites in early, intermediate, and late successional stages, evaluating the influence of resource availability and seasonal variations in guild structure. We collected a total of 763 beetles from 23 species, including 14 bark beetle species, and 9 ambrosia beetle species. Local richness of bark and ambrosia beetles was estimated at 31 species. Bark and ambrosia composition was similar over the successional stages gradient, and beta diversity among sites was primarily determined by species turnover, mainly in the bark beetle community. Bark beetle richness and abundance were higher at intermediate stages; availability of wood was the main spatial mechanism. Climate factors were effectively non-seasonal. Ambrosia beetles were not influenced by successional stages, however the increase in wood resulted in increased abundance. We found higher richness at the end of the dry and wet seasons, and abundance increased with air moisture and decreased with higher temperatures and greater rainfall. In summary, bark beetle species accumulation was higher at sites with better wood production, while the needs of fungi (host and air moisture), resulted in a favorable conditions for species accumulation of ambrosia. The overall biological pattern among guilds differed from tropical rain forests, showing patterns similar to dry forest areas. © The Author 2016. Published by Oxford University Press on behalf of the Entomological Society of America.
Wetting and drying of soil in response to precipitation: Data analysis, modeling, and forecasting
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.
Assimilating satellite soil moisture into rainfall-runoff modelling: towards a systematic study
NASA Astrophysics Data System (ADS)
Massari, Christian; Tarpanelli, Angelica; Brocca, Luca; Moramarco, Tommaso
2015-04-01
Soil moisture is the main factor for the repartition of the mass and energy fluxes between the land surface and the atmosphere thus playing a fundamental role in the hydrological cycle. Indeed, soil moisture represents the initial condition of rainfall-runoff modelling that determines the flood response of a catchment. Different initial soil moisture conditions can discriminate between catastrophic and minor effects of a given rainfall event. Therefore, improving the estimation of initial soil moisture conditions will reduce uncertainties in early warning flood forecasting models addressing the mitigation of flood hazard. In recent years, satellite soil moisture products have become available with fine spatial-temporal resolution and a good accuracy. Therefore, a number of studies have been published in which the impact of the assimilation of satellite soil moisture data into rainfall-runoff modelling is investigated. Unfortunately, data assimilation involves a series of assumptions and choices that significantly affect the final result. Given a satellite soil moisture observation, a rainfall-runoff model and a data assimilation technique, an improvement or a deterioration of discharge predictions can be obtained depending on the choices made in the data assimilation procedure. Consequently, large discrepancies have been obtained in the studies published so far likely due to the differences in the implementation of the data assimilation technique. On this basis, a comprehensive and robust procedure for the assimilation of satellite soil moisture data into rainfall-runoff modelling is developed here and applied to six subcatchment of the Upper Tiber River Basin for which high-quality hydrometeorological hourly observations are available in the period 1989-2013. The satellite soil moisture product used in this study is obtained from the Advanced SCATterometer (ASCAT) onboard Metop-A satellite and it is available since 2007. The MISDc ("Modello Idrologico SemiDistribuito in continuo") continuous hydrological model is used for flood simulation. The Ensemble Kalman Filter (EnKF) is employed as data assimilation technique for its flexibility and good performance in a number of previous applications. Different components are involved in the developed data assimilation procedure. For the correction of the bias between satellite and modelled soil moisture data three different techniques are considered: mean-variance matching, Cumulative Density Function (CDF) matching and least square linear regression. For properly generating the ensembles of model states, required in the application of EnKF technique, an exhaustive search of the model error parameterization and structure is carried out, differentiated for each study catchments. A number of scores and statistics are employed for the evaluation the reliability of the ensemble. Similarly, different configurations for the observation error are investigated. Results show that for four out six catchments the assimilation of the ASCAT soil moisture product improves discharge simulation in the validation period 2010-2013, mainly during flood events. The two catchments in which the assimilation does not improve the results are located in the mountainous part of the region where both MISDc and satellite data perform worse. The analysis on the data assimilation choices highlights that the selection of the observation error seems to have the largest influence on discharge simulation. Finally, the bias correction approaches have a lower effect and the selection of linear techniques is preferable. The assessment of all the components involved in the data assimilation procedure provides a clear understanding of results and it is advised to follow a similar procedure in this kind of studies.
Moisture processes accompanying convective activity
NASA Technical Reports Server (NTRS)
Sienkiewicz, M. E.; Scoggins, J. R.
1982-01-01
A moisture budget analysis was performed on data collected during the AVE 7 (May 2 to 3, 1978) and AVE-SESAME1 (April 10 to 11, 1979) experiments. Local rates-of-change of moisture were compared with average moisture divergence in the same time period. Results were presented as contoured plots in the horizontal and as vertical cross sections. These results were used to develop models of the distribution of moisture processes in the vicinity of convective areas in two layers representing lower and middle tropospheric conditions. Good correspondence was found between the residual term of the moisture budget and actual precipitation.
Whelan, Andrew; Mitchell, Robert; Staudhammer, Christina; Starr, Gregory
2013-01-01
Fire regulates the structure and function of savanna ecosystems, yet we lack understanding of how cyclic fire affects savanna carbon dynamics. Furthermore, it is largely unknown how predicted changes in climate may impact the interaction between fire and carbon cycling in these ecosystems. This study utilizes a novel combination of prescribed fire, eddy covariance (EC) and statistical techniques to investigate carbon dynamics in frequently burned longleaf pine savannas along a gradient of soil moisture availability (mesic, intermediate and xeric). This research approach allowed us to investigate the complex interactions between carbon exchange and cyclic fire along the ecological amplitude of longleaf pine. Over three years of EC measurement of net ecosystem exchange (NEE) show that the mesic site was a net carbon sink (NEE = -2.48 tonnes C ha(-1)), while intermediate and xeric sites were net carbon sources (NEE = 1.57 and 1.46 tonnes C ha(-1), respectively), but when carbon losses due to fuel consumption were taken into account, all three sites were carbon sources (10.78, 7.95 and 9.69 tonnes C ha(-1) at the mesic, intermediate and xeric sites, respectively). Nonetheless, rates of NEE returned to pre-fire levels 1-2 months following fire. Consumption of leaf area by prescribed fire was associated with reduction in NEE post-fire, and the system quickly recovered its carbon uptake capacity 30-60 days post fire. While losses due to fire affected carbon balances on short time scales (instantaneous to a few months), drought conditions over the final two years of the study were a more important driver of net carbon loss on yearly to multi-year time scales. However, longer-term observations over greater environmental variability and additional fire cycles would help to more precisely examine interactions between fire and climate and make future predictions about carbon dynamics in these systems.
Whelan, Andrew; Mitchell, Robert; Staudhammer, Christina; Starr, Gregory
2013-01-01
Fire regulates the structure and function of savanna ecosystems, yet we lack understanding of how cyclic fire affects savanna carbon dynamics. Furthermore, it is largely unknown how predicted changes in climate may impact the interaction between fire and carbon cycling in these ecosystems. This study utilizes a novel combination of prescribed fire, eddy covariance (EC) and statistical techniques to investigate carbon dynamics in frequently burned longleaf pine savannas along a gradient of soil moisture availability (mesic, intermediate and xeric). This research approach allowed us to investigate the complex interactions between carbon exchange and cyclic fire along the ecological amplitude of longleaf pine. Over three years of EC measurement of net ecosystem exchange (NEE) show that the mesic site was a net carbon sink (NEE = −2.48 tonnes C ha−1), while intermediate and xeric sites were net carbon sources (NEE = 1.57 and 1.46 tonnes C ha−1, respectively), but when carbon losses due to fuel consumption were taken into account, all three sites were carbon sources (10.78, 7.95 and 9.69 tonnes C ha−1 at the mesic, intermediate and xeric sites, respectively). Nonetheless, rates of NEE returned to pre-fire levels 1–2 months following fire. Consumption of leaf area by prescribed fire was associated with reduction in NEE post-fire, and the system quickly recovered its carbon uptake capacity 30–60 days post fire. While losses due to fire affected carbon balances on short time scales (instantaneous to a few months), drought conditions over the final two years of the study were a more important driver of net carbon loss on yearly to multi-year time scales. However, longer-term observations over greater environmental variability and additional fire cycles would help to more precisely examine interactions between fire and climate and make future predictions about carbon dynamics in these systems. PMID:23335986
NASA Astrophysics Data System (ADS)
Wang, S. G.; Li, X.; Han, X. J.; Jin, R.
2010-06-01
Radar remote sensing has demonstrated its applicability to the retrieval of basin-scale soil moisture. The mechanism of radar backscattering from soils is complicated and strongly influenced by surface roughness. Furthermore, retrieval of soil moisture using AIEM-like models is a classic example of the underdetermined problem due to a lack of credible known soil roughness distributions at a regional scale. Characterization of this roughness is therefore crucial for an accurate derivation of soil moisture based on backscattering models. This study aims to directly obtain surface roughness information along with soil moisture from multi-angular ASAR images. The method first used a semi-empirical relationship that connects the roughness slope (Zs) and the difference in backscattering coefficient (Δσ) from ASAR data in different incidence angles, in combination with an optimal calibration form consisting of two roughness parameters (the standard deviation of surface height and the correlation length), to estimate the roughness parameters. The deduced surface roughness was then used in the AIEM model for the retrieval of soil moisture. An evaluation of the proposed method was performed in a grassland site in the middle stream of the Heihe River Basin, where the Watershed Allied Telemetry Experimental Research (WATER) was taken place. It has demonstrated that the method is feasible to achieve reliable estimation of soil water content. The key challenge to surface soil moisture retrieval is the presence of vegetation cover, which significantly impacts the estimates of surface roughness and soil moisture.
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
An empirical model for the complex dielectric permittivity of soils as a function of water content
NASA Technical Reports Server (NTRS)
Wang, J. R.; Chmugge, T. J.
1978-01-01
The recent measurements on the dielectric properties of soils shows that the variation of dielectric constant with moisture content depends on soil types. The observed dielectric constant increases only slowly with moisture content up to a transition point. Beyond the transition it increases rapidly with moisture content. The moisture value of transition region was found to be higher for high clay content soils than for sandy soils. Many mixing formulas were compared with, and were found incompatible with, the measured dielectric variations of soil-water mixtures. A simple empirical model was proposed to describe the dielectric behavior of ths soil-water mixtures. The relationship between transition moisture and wilting point provides a means of estimating soil dielectric properties on the basis of texture information.
The advanced qualtiy control techniques planned for the Internation Soil Moisture Network
NASA Astrophysics Data System (ADS)
Xaver, A.; Gruber, A.; Hegiova, A.; Sanchis-Dufau, A. D.; Dorigo, W. A.
2012-04-01
In situ soil moisture observations are essential to evaluate and calibrate modeled and remotely sensed soil moisture products. Although a number of meteorological networks and field campaigns measuring soil moisture exist on a global and long-term scale, their observations are not easily accessible and lack standardization of both technique and protocol. Thus, handling and especially comparing these datasets with satellite products or land surface models is a demanding issue. To overcome these limitations the International Soil Moisture Network (ISMN; http://www.ipf.tuwien.ac.at/insitu/) has been initiated to act as a centralized data hosting facility. One advantage of the ISMN is that users are able to access the harmonized datasets easily through a web portal. Another advantage is the fully automated processing chain including the data harmonization in terms of units and sampling interval, but even more important is the advanced quality control system each measurement has to run through. The quality of in situ soil moisture measurements is crucial for the validation of satellite- and model-based soil moisture retrievals; therefore a sophisticated quality control system was developed. After a check for plausibility and geophysical limits a quality flag is added to each measurement. An enhanced flagging mechanism was recently defined using a spectrum based approach to detect spurious spikes, jumps and plateaus. The International Soil Moisture Network has already evolved to one of the most important distribution platforms for in situ soil moisture observations and is still growing. Currently, data from 27 networks in total covering more than 800 stations in Europe, North America, Australia, Asia and Africa is hosted by the ISMN. Available datasets also include historical datasets as well as near real-time measurements. The improved quality control system will provide important information for satellite-based as well as land surface model-based validation studies.
Soil Moisture Estimate Under Forest Using a Semi-Empirical Model at P-Band
NASA Technical Reports Server (NTRS)
Truong-Loi, My-Linh; Saatchi, Sassan; Jaruwatanadilok, Sermsak
2013-01-01
Here we present the result of a semi-empirical inversion model for soil moisture retrieval using the three backscattering coefficients: sigma(sub HH), sigma(sub VV) and sigma(sub HV). In this paper we focus on the soil moisture estimate and use the biomass as an ancillary parameter estimated automatically from the algorithm and used as a validation parameter, We will first remind the model analytical formulation. Then we will sow some results obtained with real SAR data and compare them to ground estimates.
NASA Astrophysics Data System (ADS)
Dalla Valle, Nicolas; Wutzler, Thomas; Meyer, Stefanie; Potthast, Karin; Michalzik, Beate
2017-04-01
Dual-permeability type models are widely used to simulate water fluxes and solute transport in structured soils. These models contain two spatially overlapping flow domains with different parameterizations or even entirely different conceptual descriptions of flow processes. They are usually able to capture preferential flow phenomena, but a large set of parameters is needed, which are very laborious to obtain or cannot be measured at all. Therefore, model inversions are often used to derive the necessary parameters. Although these require sufficient input data themselves, they can use measurements of state variables instead, which are often easier to obtain and can be monitored by automated measurement systems. In this work we show a method to estimate soil hydraulic parameters from high frequency soil moisture time series data gathered at two different measurement depths by inversion of a simple one dimensional dual-permeability model. The model uses an advection equation based on the kinematic wave theory to describe the flow in the fracture domain and a Richards equation for the flow in the matrix domain. The soil moisture time series data were measured in mesocosms during sprinkling experiments. The inversion consists of three consecutive steps: First, the parameters of the water retention function were assessed using vertical soil moisture profiles in hydraulic equilibrium. This was done using two different exponential retention functions and the Campbell function. Second, the soil sorptivity and diffusivity functions were estimated from Boltzmann-transformed soil moisture data, which allowed the calculation of the hydraulic conductivity function. Third, the parameters governing flow in the fracture domain were determined using the whole soil moisture time series. The resulting retention functions were within the range of values predicted by pedotransfer functions apart from very dry conditions, where all retention functions predicted lower matrix potentials. The diffusivity function predicted values of a similar range as shown in other studies. Overall, the model was able to emulate soil moisture time series for low measurement depths, but deviated increasingly at larger depths. This indicates that some of the model parameters are not constant throughout the profile. However, overall seepage fluxes were still predicted correctly. In the near future we will apply the inversion method to lower frequency soil moisture data from different sites to evaluate the model's ability to predict preferential flow seepage fluxes at the field scale.
Infusion of SMAP Data into Offline and Coupled Models: Evaluation, Calibration, and Assimilation
NASA Astrophysics Data System (ADS)
Lawston, P.; Santanello, J. A., Jr.; Dennis, E. J.; Kumar, S.
2017-12-01
The impact of the land surface on the water and energy cycle is modulated by its coupling to the planetary boundary layer (PBL), and begins at the local scale. A core component of the local land-atmosphere coupling (LoCo) effort requires understanding the `links in the chain' between soil moisture and precipitation, most notably through surface heat fluxes and PBL evolution. To date, broader (i.e. global) application of LoCo diagnostics has been limited by observational data requirements of the coupled system (and in particular, soil moisture) that are typically only met during localized, short-term field campaigns. SMAP offers, for the first time, the ability to map high quality, near-surface soil moisture globally every few days at a spatial resolution comparable to current modeling efforts. As a result, there are numerous potential avenues for SMAP model-data fusion that can be explored in the context of improving understanding of L-A interaction and NWP. In this study, we assess multiple points of intersection of SMAP products with offline and coupled models and evaluate impacts using process-level diagnostics. Results will inform upon the importance of high-resolution soil moisture mapping for improved coupled prediction and model development, as well as reconciling differences in modeled, retrieved, and measured soil moisture. Specifically, NASA model (LIS, NU-WRF) and observation (SMAP, NLDAS-2) products are combined with in-situ standard and IOP measurements (soil moisture, flux, and radiosonde) over the ARM-SGP. An array of land surface model spinups (via LIS-Noah) are performed with varying atmospheric forcing, greenness fraction, and soil layering permutations. Calibration of LIS-Noah soil hydraulic parameters is then performed using an array of in-situ soil moisture and flux and SMAP products. In addition, SMAP assimilation is performed in LIS-Noah both at the scale of the observation (36 and 9km) and the model grid (1km). The focus is on the consistency in calibrated parameters, impact of soil drydown dynamics and soil layers, and terrestrial (soil moisture-flux) coupling. The impacts of these various spinup runs and initialization of NU-WRF coupled forecasts then follows with a focus on weather (ambient, PBL, and precipitation) using LoCo metrics.
Hursh, Andrew; Ballantyne, Ashley; Cooper, Leila; Maneta, Marco; Kimball, John; Watts, Jennifer
2017-05-01
Soil respiration (Rs) is a major pathway by which fixed carbon in the biosphere is returned to the atmosphere, yet there are limits to our ability to predict respiration rates using environmental drivers at the global scale. While temperature, moisture, carbon supply, and other site characteristics are known to regulate soil respiration rates at plot scales within certain biomes, quantitative frameworks for evaluating the relative importance of these factors across different biomes and at the global scale require tests of the relationships between field estimates and global climatic data. This study evaluates the factors driving Rs at the global scale by linking global datasets of soil moisture, soil temperature, primary productivity, and soil carbon estimates with observations of annual Rs from the Global Soil Respiration Database (SRDB). We find that calibrating models with parabolic soil moisture functions can improve predictive power over similar models with asymptotic functions of mean annual precipitation. Soil temperature is comparable with previously reported air temperature observations used in predicting Rs and is the dominant driver of Rs in global models; however, within certain biomes soil moisture and soil carbon emerge as dominant predictors of Rs. We identify regions where typical temperature-driven responses are further mediated by soil moisture, precipitation, and carbon supply and regions in which environmental controls on high Rs values are difficult to ascertain due to limited field data. Because soil moisture integrates temperature and precipitation dynamics, it can more directly constrain the heterotrophic component of Rs, but global-scale models tend to smooth its spatial heterogeneity by aggregating factors that increase moisture variability within and across biomes. We compare statistical and mechanistic models that provide independent estimates of global Rs ranging from 83 to 108 Pg yr -1 , but also highlight regions of uncertainty where more observations are required or environmental controls are hard to constrain. © 2016 John Wiley & Sons Ltd.
NASA Astrophysics Data System (ADS)
Chahal, M. K.; Brown, D. J.; Brooks, E. S.; Campbell, C.; Cobos, D. R.; Vierling, L. A.
2012-12-01
Estimating soil moisture content continuously over space and time using geo-statistical techniques supports the refinement of process-based watershed hydrology models and the application of soil process models (e.g. biogeochemical models predicting greenhouse gas fluxes) to complex landscapes. In this study, we model soil profile volumetric moisture content for five agricultural fields with loess soils in the Palouse region of Eastern Washington and Northern Idaho. Using a combination of stratification and space-filling techniques, we selected 42 representative and distributed measurement locations in the Cook Agronomy Farm (Pullman, WA) and 12 locations each in four additional grower fields that span the precipitation gradient across the Palouse. At each measurement location, soil moisture was measured on an hourly basis at five different depths (30, 60, 90, 120, and 150 cm) using Decagon 5-TE/5-TM soil moisture sensors (Decagon Devices, Pullman, WA, USA). This data was collected over three years for the Cook Agronomy Farm and one year for each of the grower fields. In addition to ordinary kriging, we explored the correlation of volumetric water content with external, spatially exhaustive indices derived from terrain models, optical remote sensing imagery, and proximal soil sensing data (electromagnetic induction and VisNIR penetrometer)
USDA-ARS?s Scientific Manuscript database
NASA’s SMAP satellite, launched in November of 2014, produces estimates of average volumetric soil moisture at 3, 9, and 36-kilometer scales. The calibration and validation process of these estimates requires the generation of an identically-scaled soil moisture product from existing in-situ networ...
Modelling recent and future climatic suitability for fasciolosis in Europe.
Caminade, Cyril; van Dijk, Jan; Baylis, Matthew; Williams, Diana
2015-03-19
Fasciola hepatica is a parasitic worm responsible for fasciolosis in grazed ruminants in Europe. The free-living stages of this parasite are sensitive to temperature and soil moisture, as are the intermediate snail hosts the parasite depends on for its life-cycle. We used a climate-driven disease model in order to assess the impact of recent and potential future climate changes on the incidence of fasciolosis and to estimate the related uncertainties at the scale of the European landmass. The current climate appears to be highly suitable for fasciolosis throughout the European Union with the exception of some parts of the Mediterranean region. Simulated climatic suitability for fasciolosis significantly increased during the 2000s in central and northwestern Europe, which is consistent with an observed increased in ruminant infections. The simulation showed that recent trends are likely to continue in the future with the estimated pattern of climate change for northern Europe, possibly extending the season suitable for development of the parasite in the environment by up to four months. For southern Europe, the simulated burden of disease may be lower, but the projected climate change will increase the risk during the winter months, since the simulated changes in temperature and moisture support the development of the free-living and intra-molluscan stages between November and March. In the event of predicted climate change, F. hepatica will present a serious risk to the health, welfare and productivity of all ruminant livestock. Improved, bespoke control programmes, both at farm and region levels, will then become imperative if problems, such as resistance of the parasite associated with increased drug use, are to be mitigated.
Is the Pearl River basin, China, drying or wetting? Seasonal variations, causes and implications
NASA Astrophysics Data System (ADS)
Zhang, Qiang; Li, Jianfeng; Gu, Xihui; Shi, Peijun
2018-07-01
Soil moisture plays crucial roles in the hydrological cycle and is also a critical link between land surface and atmosphere. The Pearl River basin (PRb) is climatically subtropical and tropical and is highly sensitive to climate changes. In this study, seasonal soil moisture changes across the PRb were analyzed using the Variable Infiltration Capacity (VIC) model forced by the gridded 0.5° × 0.5° climatic observations. Seasonal changes of soil moisture in both space and time were investigated using the Mann-Kendall trend test method. Potential influencing factors behind seasonal soil moisture changes such as precipitation and temperature were identified using the Maximum Covariance Analysis (MCA) technique. The results indicated that: (1) VIC model performs well in describing changing properties of soil moisture across the PRb; (2) Distinctly different seasonal features of soil moisture can be observed. Soil moisture in spring decreased from east to west parts of the PRb. In summer however, soil moisture was higher in east and west parts but was lower in central parts of the PRb; (3) A significant drying trend was identified over the PRb in autumn, while no significant drying trends can be detected in other seasons; (4) The increase/decrease in precipitation can generally explain the wetting/drying tendency of soil moisture. However, warming temperature contributed significantly to the drying trends and these drying trends were particularly evident during autumn and winter; (5) Significant decreasing precipitation and increasing temperature combined to trigger substantially decreasing soil moisture in autumn. In winter, warming temperature is the major reason behind decreased soil moisture although precipitation is in slightly decreasing tendency. Season variations of soil moisture and related implications for hydro-meteorological processes in the subtropical and tropical river basins over the globe should arouse considerable human concerns.
Baghdadi, Nicolas; Aubert, Maelle; Cerdan, Olivier; Franchistéguy, Laurent; Viel, Christian; Martin, Eric; Zribi, Mehrez; Desprats, Jean François
2007-01-01
Soil moisture is a key parameter in different environmental applications, such as hydrology and natural risk assessment. In this paper, surface soil moisture mapping was carried out over a basin in France using satellite synthetic aperture radar (SAR) images acquired in 2006 and 2007 by C-band (5.3 GHz) sensors. The comparison between soil moisture estimated from SAR data and in situ measurements shows good agreement, with a mapping accuracy better than 3%. This result shows that the monitoring of soil moisture from SAR images is possible in operational phase. Moreover, moistures simulated by the operational Météo-France ISBA soil-vegetation-atmosphere transfer model in the SIM-Safran-ISBA-Modcou chain were compared to radar moisture estimates to validate its pertinence. The difference between ISBA simulations and radar estimates fluctuates between 0.4 and 10% (RMSE). The comparison between ISBA and gravimetric measurements of the 12 March 2007 shows a RMSE of about 6%. Generally, these results are very encouraging. Results show also that the soil moisture estimated from SAR images is not correlated with the textural units defined in the European Soil Geographical Database (SGDBE) at 1:1000000 scale. However, dependence was observed between texture maps and ISBA moisture. This dependence is induced by the use of the texture map as an input parameter in the ISBA model. Even if this parameter is very important for soil moisture estimations, radar results shown that the textural map scale at 1:1000000 is not appropriate to differentiate moistures zones. PMID:28903238
Soil moisture needs in earth sciences
NASA Technical Reports Server (NTRS)
Engman, Edwin T.
1992-01-01
The author reviews the development of passive and active microwave techniques for measuring soil moisture with respect to how the data may be used. New science programs such as the EOS, the GEWEX Continental-Scale International Project (GCIP) and STORM, a mesoscale meteorology and hydrology project, will have to account for soil moisture either as a storage in water balance computations or as a state variable in-process modeling. The author discusses future soil moisture needs such as frequency of measurement, accuracy, depth, and spatial resolution, as well as the concomitant model development that must proceed concurrently if the development in microwave technology is to have a major impact in these areas.
Further experimentation on bubble generation during transformer overload. Final report
DOE Office of Scientific and Technical Information (OSTI.GOV)
Oommen, T.V.
1992-03-01
This report covers additional work done during 1990 and 1991 on gas bubble generation under overload conditions. To improve visual bubble detection, a single disc coil was used. To further improve detection, a corona device was also used which signaled the onset of corona activity in the early stages of bubble formation. A total of fourteen model tests were conducted, half of which used the Inertaire system, and the remaining, a conservator (COPS). Moisture content of paper in the coil varied from 1.0% to 8.0%; gas (nitrogen) content varied from 1.0% to 8.8%. The results confirmed earlier observations that themore » mathematical bubble prediction model was not valid for high gas content model with relatively low moisture levels in the coil. An empirical relationship was formulated to accurately predict bubble evolution temperatures from known moisture and gas content values. For low moisture content models (below 2%), the simple Piper relationship was sufficient to predict bubble evolution temperatures, regardless of gas content. Moisture in the coil appears to be the key factor in bubble generation. Gas blanketed (Inertaire) systems do not appear to be prone to premature bubble generation from overloads as previously thought. The new bubble prediction model reveals that for a coil with 2% moisture, the bubble evolution temperature would be about 140{degrees}C. Since old transformers in service may have as much as 2% moisture in paper, the 140{degrees}C bubble evolution temperature may be taken as the lower limit of bubble evolution temperature under overload conditions for operating transformers. Drier insulation would raise the bubble evolution temperature.« less
Observing and modeling links between soil moisture, microbes and CH4 fluxes from forest soils
NASA Astrophysics Data System (ADS)
Christiansen, Jesper; Levy-Booth, David; Barker, Jason; Prescott, Cindy; Grayston, Sue
2017-04-01
Soil moisture is a key driver of methane (CH4) fluxes in forest soils, both of the net uptake of atmospheric CH4 and emission from the soil. Climate and land use change will alter spatial patterns of soil moisture as well as temporal variability impacting the net CH4 exchange. The impact on the resultant net CH4 exchange however is linked to the underlying spatial and temporal distribution of the soil microbial communities involved in CH4 cycling as well as the response of the soil microbial community to environmental changes. Significant progress has been made to target specific CH4 consuming and producing soil organisms, which is invaluable in order to understand the microbial regulation of the CH4 cycle in forest soils. However, it is not clear as to which extent soil moisture shapes the structure, function and abundance of CH4 specific microorganisms and how this is linked to observed net CH4 exchange under contrasting soil moisture regimes. Here we report on the results from a research project aiming to understand how the CH4 net exchange is shaped by the interactive effects soil moisture and the spatial distribution CH4 consuming (methanotrophs) and producing (methanogens). We studied the growing season variations of in situ CH4 fluxes, microbial gene abundances of methanotrophs and methanogens, soil hydrology, and nutrient availability in three typical forest types across a soil moisture gradient in a temperate rainforest on the Canadian Pacific coast. Furthermore, we conducted laboratory experiments to determine whether the net CH4 exchange from hydrologically contrasting forest soils responded differently to changes in soil moisture. Lastly, we modelled the microbial mediation of net CH4 exchange along the soil moisture gradient using structural equation modeling. Our study shows that it is possible to link spatial patterns of in situ net exchange of CH4 to microbial abundance of CH4 consuming and producing organisms. We also show that the microbial community responds different to environmental change dependent on the soil moisture regime. These results are important to include in future modeling efforts to predict changes in soil-atmosphere exchange of CH4 under global change.
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.
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.
Molecular Modeling for Calculation of Mechanical Properties of Epoxies with Moisture Ingress
NASA Technical Reports Server (NTRS)
Clancy, Thomas C.; Frankland, Sarah J.; Hinkley, J. A.; Gates, T. S.
2009-01-01
Atomistic models of epoxy structures were built in order to assess the effect of crosslink degree, moisture content and temperature on the calculated properties of a typical representative generic epoxy. Each atomistic model had approximately 7000 atoms and was contained within a periodic boundary condition cell with edge lengths of about 4 nm. Four atomistic models were built with a range of crosslink degree and moisture content. Each of these structures was simulated at three temperatures: 300 K, 350 K, and 400 K. Elastic constants were calculated for these structures by monitoring the stress tensor as a function of applied strain deformations to the periodic boundary conditions. The mechanical properties showed reasonably consistent behavior with respect to these parameters. The moduli decreased with decreasing crosslink degree with increasing temperature. The moduli generally decreased with increasing moisture content, although this effect was not as consistent as that seen for temperature and crosslink degree.
Qiu, Jinya Jack; Pryor, Alan
2009-01-01
Ozone gas (O3) is a reactive oxidizing agent with biocidal properties. Because of the current phasing out of methyl bromide, investigations on the use of ozone gas as a soil-fumigant were conducted. Ozone gas was produced at a concentration of 1% in air by a conventional electrical discharge O3 generator. Two O3 dosages and three gas flow rates were tested on a sandy loam soil collected from a tomato field that had a resident population of root knot nematodes, Meloidogyne javanica. At dosages equivalent to 50 and 250 kg of O3/ha, M. javanica were reduced by 24% and 68%, and free-living nematodes by 19% and 52%, respectively. The reduction for both M. javanica and free-living nematodes was dosage dependent and flow rate independent. The rates of O3 mass transfer (OMT) through three soils of different texture were greater at low and high moisture levels than at intermediate ones. At any one soil moisture level, the OMT rate varied with soil texture and soil organic matter content. Results suggest that soil texture, moisture, and organic matter content should be considered in determining O3 dosage needed for effective nematode control. PMID:22736821
NASA Astrophysics Data System (ADS)
Dumedah, Gift; Walker, Jeffrey P.
2017-03-01
The sources of uncertainty in land surface models are numerous and varied, from inaccuracies in forcing data to uncertainties in model structure and parameterizations. Majority of these uncertainties are strongly tied to the overall makeup of the model, but the input forcing data set is independent with its accuracy usually defined by the monitoring or the observation system. The impact of input forcing data on model estimation accuracy has been collectively acknowledged to be significant, yet its quantification and the level of uncertainty that is acceptable in the context of the land surface model to obtain a competitive estimation remain mostly unknown. A better understanding is needed about how models respond to input forcing data and what changes in these forcing variables can be accommodated without deteriorating optimal estimation of the model. As a result, this study determines the level of forcing data uncertainty that is acceptable in the Joint UK Land Environment Simulator (JULES) to competitively estimate soil moisture in the Yanco area in south eastern Australia. The study employs hydro genomic mapping to examine the temporal evolution of model decision variables from an archive of values obtained from soil moisture data assimilation. The data assimilation (DA) was undertaken using the advanced Evolutionary Data Assimilation. Our findings show that the input forcing data have significant impact on model output, 35% in root mean square error (RMSE) for 5cm depth of soil moisture and 15% in RMSE for 15cm depth of soil moisture. This specific quantification is crucial to illustrate the significance of input forcing data spread. The acceptable uncertainty determined based on dominant pathway has been validated and shown to be reliable for all forcing variables, so as to provide optimal soil moisture. These findings are crucial for DA in order to account for uncertainties that are meaningful from the model standpoint. Moreover, our results point to a proper treatment of input forcing data in general land surface and hydrological model estimation.
NASA Astrophysics Data System (ADS)
Wever, Nander; Comola, Francesco; Bavay, Mathias; Lehning, Michael
2017-08-01
The assessment of flood risks in alpine, snow-covered catchments requires an understanding of the linkage between the snow cover, soil and discharge in the stream network. Here, we apply the comprehensive, distributed model Alpine3D to investigate the role of soil moisture in the predisposition of the Dischma catchment in Switzerland to high flows from rainfall and snowmelt. The recently updated soil module of the physics-based multilayer snow cover model SNOWPACK, which solves the surface energy and mass balance in Alpine3D, is verified against soil moisture measurements at seven sites and various depths inside and in close proximity to the Dischma catchment. Measurements and simulations in such terrain are difficult and consequently, soil moisture was simulated with varying degrees of success. Differences between simulated and measured soil moisture mainly arise from an overestimation of soil freezing and an absence of a groundwater description in the Alpine3D model. Both were found to have an influence in the soil moisture measurements. Using the Alpine3D simulation as the surface scheme for a spatially explicit hydrologic response model using a travel time distribution approach for interflow and baseflow, streamflow simulations were performed for the discharge from the catchment. The streamflow simulations provided a closer agreement with observed streamflow when driving the hydrologic response model with soil water fluxes at 30 cm depth in the Alpine3D model. Performance decreased when using the 2 cm soil water flux, thereby mostly ignoring soil processes. This illustrates that the role of soil moisture is important to take into account when understanding the relationship between both snowpack runoff and rainfall and catchment discharge in high alpine terrain. However, using the soil water flux at 60 cm depth to drive the hydrologic response model also decreased its performance, indicating that an optimal soil depth to include in surface simulations exists and that the runoff dynamics are controlled by only a shallow soil layer. Runoff coefficients (i.e. ratio of rainfall over discharge) based on measurements for high rainfall and snowmelt events were found to be dependent on the simulated initial soil moisture state at the onset of an event, further illustrating the important role of soil moisture for the hydrological processes in the catchment. The runoff coefficients using simulated discharge were found to reproduce this dependency, which shows that the Alpine3D model framework can be successfully applied to assess the predisposition of the catchment to flood risks from both snowmelt and rainfall events.
An inversion method for retrieving soil moisture information from satellite altimetry observations
NASA Astrophysics Data System (ADS)
Uebbing, Bernd; Forootan, Ehsan; Kusche, Jürgen; Braakmann-Folgmann, Anne
2016-04-01
Soil moisture represents an important component of the terrestrial water cycle that controls., evapotranspiration and vegetation growth. Consequently, knowledge on soil moisture variability is essential to understand the interactions between land and atmosphere. Yet, terrestrial measurements are sparse and their information content is limited due to the large spatial variability of soil moisture. Therefore, over the last two decades, several active and passive radar and satellite missions such as ERS/SCAT, AMSR, SMOS or SMAP have been providing backscatter information that can be used to estimate surface conditions including soil moisture which is proportional to the dielectric constant of the upper (few cm) soil layers . Another source of soil moisture information are satellite radar altimeters, originally designed to measure sea surface height over the oceans. Measurements of Jason-1/2 (Ku- and C-Band) or Envisat (Ku- and S-Band) nadir radar backscatter provide high-resolution along-track information (~ 300m along-track resolution) on backscatter every ~10 days (Jason-1/2) or ~35 days (Envisat). Recent studies found good correlation between backscatter and soil moisture in upper layers, especially in arid and semi-arid regions, indicating the potential of satellite altimetry both to reconstruct and to monitor soil moisture variability. However, measuring soil moisture using altimetry has some drawbacks that include: (1) the noisy behavior of the altimetry-derived backscatter (due to e.g., existence of surface water in the radar foot-print), (2) the strong assumptions for converting altimetry backscatters to the soil moisture storage changes, and (3) the need for interpolating between the tracks. In this study, we suggest a new inversion framework that allows to retrieve soil moisture information from along-track Jason-2 and Envisat satellite altimetry data, and we test this scheme over the Australian arid and semi-arid regions. Our method consists of: (i) deriving time-invariant spatial patterns (base-functions) by applying principal component analysis (PCA) to simulated soil moisture from a large-scale land surface model. (ii) Estimating time-variable soil moisture evolution by fitting these base functions of (i) to the along-track retracked backscatter coefficients in a least squares sense. (iii) Combining the estimated time-variable amplitudes and the pre-computed base-functions, which results in reconstructed (spatio-temporal) soil moisture information. We will show preliminary results that are compared to available high-resolution soil moisture model data over the region (the Australian Water Resource Assessment, AWRA model). We discuss the possibility of using altimetry-derived soil moisture estimations to improve the simulation skill of soil moisture in the Global Land Data Assimilation System (GLDAS) over Australia.
Lucato, Jeanette Janaina Jaber; Adams, Alexander Bernard; Souza, Rogério; Torquato, Jamili Anbar; Carvalho, Carlos Roberto Ribeiro; Marini, John J
2009-01-01
To evaluate and compare the efficiency of humidification in available heat and moisture exchanger models under conditions of varying tidal volume, respiratory rate, and flow rate. Inspired gases are routinely preconditioned by heat and moisture exchangers to provide a heat and water content similar to that provided normally by the nose and upper airways. The absolute humidity of air retrieved from and returned to the ventilated patient is an important measurable outcome of the heat and moisture exchangers' humidifying performance. Eight different heat and moisture exchangers were studied using a respiratory system analog. The system included a heated chamber (acrylic glass, maintained at 37 degrees C), a preserved swine lung, a hygrometer, circuitry and a ventilator. Humidity and temperature levels were measured using eight distinct interposed heat and moisture exchangers given different tidal volumes, respiratory frequencies and flow-rate conditions. Recovery of absolute humidity (%RAH) was calculated for each setting. Increasing tidal volumes led to a reduction in %RAH for all heat and moisture exchangers while no significant effect was demonstrated in the context of varying respiratory rate or inspiratory flow. Our data indicate that heat and moisture exchangers are more efficient when used with low tidal volume ventilation. The roles of flow and respiratory rate were of lesser importance, suggesting that their adjustment has a less significant effect on the performance of heat and moisture exchangers.
Evaluating ESA CCI soil moisture in East Africa.
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.
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.
Refinement of moisture calibration curves for nuclear gage : interim report no. 1.
DOT National Transportation Integrated Search
1972-01-01
This study was initiated to determine the correct moisture calibration curves for different nuclear gages. It was found that the Troxler Model 227 had a linear response between count ratio and moisture content. Also, the two calibration curves for th...
NASA Technical Reports Server (NTRS)
Lee, S. L.
1974-01-01
Controlled ground-based passive microwave radiometric measurements on soil moisture were conducted to determine the effects of terrain surface roughness and vegetation on microwave emission. Theoretical predictions were compared with the experimental results and with some recent airborne radiometric measurements. The relationship of soil moisture to the permittivity for the soil was obtained in the laboratory. A dual frequency radiometer, 1.41356 GHz and 10.69 GHz, took measurements at angles between 0 and 50 degrees from an altitude of about fifty feet. Distinct surface roughnesses were studied. With the roughness undisturbed, oats were later planted and vegetated and bare field measurements were compared. The 1.4 GHz radiometer was less affected than the 10.6 GHz radiometer, which under vegetated conditions was incapable of detecting soil moisture. The bare surface theoretical model was inadequate, although the vegetation model appeared to be valid. Moisture parameters to correlate apparent temperature with soil moisture were compared.
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.
The Impact of Soil Moisture Initialization On Seasonal Precipitation Forecasts
NASA Technical Reports Server (NTRS)
Koster, R. D.; Suarez, M. J.; Tyahla, L.; Houser, Paul (Technical Monitor)
2002-01-01
Some studies suggest that the proper initialization of soil moisture in a forecasting model may contribute significantly to the accurate prediction of seasonal precipitation, especially over mid-latitude continents. In order for the initialization to have any impact at all, however, two conditions must be satisfied: (1) the initial soil moisture anomaly must be "remembered" into the forecasted season, and (2) the atmosphere must respond in a predictable way to the soil moisture anomaly. In our previous studies, we identified the key land surface and atmospheric properties needed to satisfy each condition. Here, we tie these studies together with an analysis of an ensemble of seasonal forecasts. Initial soil moisture conditions for the forecasts are established by forcing the land surface model with realistic precipitation prior to the start of the forecast period. As expected, the impacts on forecasted precipitation (relative to an ensemble of runs that do not utilize soil moisture information) tend to be localized over the small fraction of the earth with all of the required land and atmosphere properties.
Estimation of improved resolution soil moisture in vegetated areas using passive AMSR-E data
NASA Astrophysics Data System (ADS)
Moradizadeh, Mina; Saradjian, Mohammad R.
2018-03-01
Microwave remote sensing provides a unique capability for soil parameter retrievals. Therefore, various soil parameters estimation models have been developed using brightness temperature (BT) measured by passive microwave sensors. Due to the low resolution of satellite microwave radiometer data, the main goal of this study is to develop a downscaling approach to improve the spatial resolution of soil moisture estimates with the use of higher resolution visible/infrared sensor data. Accordingly, after the soil parameters have been obtained using Simultaneous Land Parameters Retrieval Model algorithm, the downscaling method has been applied to the soil moisture estimations that have been validated against in situ soil moisture data. Advance Microwave Scanning Radiometer-EOS BT data in Soil Moisture Experiment 2003 region in the south and north of Oklahoma have been used to this end. Results illustrated that the soil moisture variability is effectively captured at 5 km spatial scales without a significant degradation of the accuracy.
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.
Fonteyne, Margot; Gildemyn, Delphine; Peeters, Elisabeth; Mortier, Séverine Thérèse F C; Vercruysse, Jurgen; Gernaey, Krist V; Vervaet, Chris; Remon, Jean Paul; Nopens, Ingmar; De Beer, Thomas
2014-08-01
Classically, the end point detection during fluid bed drying has been performed using indirect parameters, such as the product temperature or the humidity of the outlet drying air. This paper aims at comparing those classic methods to both in-line moisture and solid-state determination by means of Process Analytical Technology (PAT) tools (Raman and NIR spectroscopy) and a mass balance approach. The six-segmented fluid bed drying system being part of a fully continuous from-powder-to-tablet production line (ConsiGma™-25) was used for this study. A theophylline:lactose:PVP (30:67.5:2.5) blend was chosen as model formulation. For the development of the NIR-based moisture determination model, 15 calibration experiments in the fluid bed dryer were performed. Six test experiments were conducted afterwards, and the product was monitored in-line with NIR and Raman spectroscopy during drying. The results (drying endpoint and residual moisture) obtained via the NIR-based moisture determination model, the classical approach by means of indirect parameters and the mass balance model were then compared. Our conclusion is that the PAT-based method is most suited for use in a production set-up. Secondly, the different size fractions of the dried granules obtained during different experiments (fines, yield and oversized granules) were compared separately, revealing differences in both solid state of theophylline and moisture content between the different granule size fractions. Copyright © 2014 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Coopersmith, E. J.; Cosh, M. H.
2014-12-01
NASA's SMAP satellite, launched in November of 2014, produces estimates of average volumetric soil moisture at 3, 9, and 36-kilometer scales. The calibration and validation process of these estimates requires the generation of an identically-scaled soil moisture product from existing in-situ networks. This can be achieved via the integration of NLDAS precipitation data to perform calibration of models at each in-situ gauge. In turn, these models and the gauges' volumetric estimations are used to generate soil moisture estimates at a 500m scale throughout a given test watershed by leveraging, at each location, the gauge-calibrated models deemed most appropriate in terms of proximity, calibration efficacy, soil-textural similarity, and topography. Four ARS watersheds, located in Iowa, Oklahoma, Georgia, and Arizona are employed to demonstrate the utility of this approach. The South Fork watershed in Iowa represents the simplest case - the soil textures and topography are relative constants and the variability of soil moisture is simply tied to the spatial variability of precipitation. The Little Washita watershed in Oklahoma adds soil textural variability (but remains topographically simple), while the Little River watershed in Georgia incorporates topographic classification. Finally, the Walnut Gulch watershed in Arizona adds a dense precipitation network to be employed for even finer-scale modeling estimates. Results suggest RMSE values at or below the 4% volumetric standard adopted for the SMAP mission are attainable over the desired spatial scales via this integration of modeling efforts and existing in-situ networks.
NASA Astrophysics Data System (ADS)
Todisco, Francesca; Brocca, Luca; Termite, Loris Francesco; Wagner, Wolfgang
2015-04-01
The accuracy of water soil loss prediction depends on the ability of the model to account for effects of the physical phenomena causing the output and the accuracy by which the parameters have been determined. The process based models require considerable effort to obtain appropriate parameter values and their failure to produce better results than achieved using the USLE/RUSLE model, encourages the use of the USLE/RUSLE model in roles of which it was not designed. In particular it is widely used in watershed models even at the event temporal scale. At hillslope scale, spatial variability in soil and vegetation result in spatial variations in soil moisture and consequently in runoff within the area for which soil loss estimation is required, so the modeling approach required to produce those estimates needs to be sensitive to those spatial variations in runoff. Some models include explicit consideration of runoff in determining the erosive stresses but this increases the uncertainty of the prediction due to the difficulty in parameterising the models also because the direct measures of surface runoff are rare. The same remarks are effective also for the USLE/RUSLE models including direct consideration of runoff in the erosivity factor (i.e. USLE-M by Kinnell and Risse, 1998, and USLE-MM by Bagarello et al., 2008). Moreover actually most of the rainfall-runoff models are based on the knowledge of the pre-event soil moisture that is a fundamental variable in the rainfall-runoff transformation. In addiction soil moisture is a readily available datum being possible to have easily direct pre-event measures of soil moisture using in situ sensors or satellite observations at larger spatial scale; it is also possible to derive the antecedent water content with soil moisture simulation models. The attempt made in the study is to use the pre-event soil moisture to account for the spatial variation in runoff within the area for which the soil loss estimates are required. More specifically the analysis was focused on the evaluation of the effectiveness of coupling modeled or satellite-derived soil moisture with USLE-derived models in predicting event unit soil loss at the plot scale in a silty-clay soil in Central Italy. To this end was used the database of the Masse experimental station developed considering for a given erosive event (an event yielding a measurable soil loss) the simultaneous measures of the total runoff amount, Qe (mm), and soil loss per unit area, Ae (Mg-ha-1) at plot scale and of the rainfall data required to derive the erosivity factor Re according to Wischmeiser and Smith (1978), with a MIT=6 h (Bagarello et al., 2013; Todisco et al., 2012). To the purpose of this investigation only data collected on the λ = 22 m long plots were considered: 63 erosive events in the period 2008-2013, 18 occurred during the dry period (from June to September) and the other 45 in the complementary period (wet period). The models tested are the USLE/RUSLE and some USLE-derived formulations in which the event erosivity factor, Re, is corrected by the antecedent soil moisture, θ, and powered to an exponent α > 0 (α =1: linear model; α ≠ 1: power model). Both soil moisture data the satellite retrieved (θ = θsat) and the estimates (θ = θest) of Soil Water Balance model (Brocca et al., 2011) were tested. The results have been compared with those obtained by the USLE/RUSLE, USLE-M and USLE-MM models coupled with a parsimonious rainfall-runoff model, MILc, (Brocca et al. 2011) for the prediction of runoff volume (that in these models is the term used to correct the erosivity factor Re). The results showed that: including direct consideration of antecedent soil moisture and runoff in the event rainfall-runoff factor of the RUSLE/USLE enhanced the capacity of the model to account for variations in event soil loss when soil moisture and runoff volume are measured or predicted reasonably well; the accuracy of the original USLE/RUSLE model was always the lowest; the accuracy in estimating the event soil loss of a models with erosivity factor that includes the estimated runoff is always overcome by at least one model that uses the antecedent soil moisture θ in the erosivity index; the power models generally, at Masse, work better than the linear. The more accurate models are that with the estimated antecedent soil moisture, θest, when all the database is used and with the satellite retrieved soil moisture, θsat, when only the wet periods' events are considered. In fact it was also verified that much of the inaccuracy of the tested models is due to summer rainfall events, probably because of the particular characteristics that the soil assumes in the dry period (superficial crusts causing higher runoff): in this cases, high soil losses are observed in association to low values of soil moisture, while the simulated runoff assume low values too, since they are based on the antecedent wetness conditions. Thus, the analyses were repeated excluding the summer events. As expected, the performance of all the models increases, but still the use of θ provides the best results. The results of the analysis open interesting scenarios in the use of USLE-derived models for the unit event soil loss estimation at large scale. In particular the use of the soil moisture to correct the rainfall erosivity factor acquires a great practical importance, since it is a relatively simple measurable data and moreover because remote sensing soil moisture data are widely available and useful in large-scale erosion assessment. Bagarello, V., Di Piazza, G. V., Ferro, V., Giordano, G., 2008. Predicting unit soil loss in Sicily, south Italy. Hydrol. Process. 22, 586-595. Bagarello, V., Ferro, V., Giordano, G., Mannocchi, F., Todisco, F., Vergni, L., 2013. Predicting event soil loss form bare plots at two Italian sites. Catena 109, 96-102. Brocca, L., Melone, F., Moramarco, T., 2011. Distributed rainfall-runoff modeling for flood frequency estimation and flood forecasting. Hydrol. Process. 25, 2801-2813. Kinnell, P. I. A., Risse, L. M., 1998. USLE-M: empirical modeling rainfall erosion through runoff and sediment concentration. Soil Sci. Soc. Am. J. 62, 1667-1672. Todisco, F., Vergni, L., Mannocchi, F., Bomba, C., 2012. Calibration of the soil loss measurement at the Masse experimental station. Catena 91, 4-9. Wischmeier, W. H., Smith, D. D., 1978. Predicting rainfall-erosion losses - A guide to conservation planning. Agriculture Handbook 537, United Stated Department of Agriculture.
Sorption Isotherm Modelling Of Fermented Cassava Flour by Red Yeast Rice
NASA Astrophysics Data System (ADS)
Cahyanti, M. N.; Alfiah, M. N.; Hartini, S.
2018-04-01
The objective of the study is to determine the characteristic of moisture sorption isotherm from fermented cassava flour by red yeast rice using various modeling. This research used seven salt solutions and storage temperature of 298K, 303K, and 308K. The models used were Brunauer-Emmet-Teller (BET), Guggenheim-Anderson-de Boer (GAB) and Caurie model. The monolayer moisture content was around 4.51 – 5.99% db. Constant related to absorption heat in the multilayer area of [GAB model was around 0.86-0,91. Constant related to absorption heat in the monolayer area of GAB model was around 4.67-5.97. Constant related to absorption heat in the monolayer area of BET model was around 4.83-7.04. Caurie constant was around 1.25-1.59. The equilibrium and monolayer moisture content on fermented cassava flour by red yeast rice was decreasing as increasing temperature. GAB constant value indicated that the process of moisture absorption on the fermented cassava flour by red yeast rice categorized in type II.
Assimilation of Satellite Data in Regional Air Quality Models
NASA Technical Reports Server (NTRS)
Mcnider, Richard T.; Norris, William B.; Casey, Daniel; Pleim, Jonathan E.; Roselle, Shawn J.; Lapenta, William M.
1997-01-01
In terms of important uncertainty in regional-scale air-pollution models, probably no other aspect ranks any higher than the current ability to specify clouds and soil moisture on the regional scale. Because clouds in models are highly parameterized, the ability of models to predict the correct spatial and radiative characteristics is highly suspect and subject to large error. The poor representation of cloud fields from point measurements at National Weather Services stations and the almost total absence of surface moisture availability observations has made assimilation of these variables difficult to impossible. Yet, the correct inclusion of clouds and surface moisture are of first-order importance in regional-scale photochemistry.
DOE Office of Scientific and Technical Information (OSTI.GOV)
McFarlane, Karis J.
The overall goal of my Early Career research is to constrain belowground carbon turnover times for tropical forests across a broad range in moisture regimes. My group is using 14C analysis and modeling to address two major objectives: quantify age and belowground carbon turnover times across tropical forests spanning a moisture gradient from wetlands to dry forest; and identify specific areas for focused model improvement and data needs through site-specific model-data comparison and belowground carbon modeling for tropic forests.
NASA Technical Reports Server (NTRS)
Bolten, John; Crow, Wade
2012-01-01
The added value of satellite-based surface soil moisture retrievals for agricultural drought monitoring is assessed by calculating the lagged rank correlation between remotely-sensed vegetation indices (VI) and soil moisture estimates obtained both before and after the assimilation of surface soil moisture retrievals derived from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) into a soil water balance model. Higher soil moisture/VI lag correlations imply an enhanced ability to predict future vegetation conditions using estimates of current soil moisture. Results demonstrate that the assimilation of AMSR-E surface soil moisture retrievals substantially improve the performance of a global drought monitoring system - particularly in sparsely-instrumented areas of the world where high-quality rainfall observations are unavailable.
Use of Temperature and Humidity Sensors to Determine Moisture Content of Oolong Tea
Chen, Andrew; Chen, Hsuan-Yu; Chen, Chiachung
2014-01-01
The measurement of tea moisture content is important for processing and storing tea. The moisture content of tea affects the quality and durability of the product. Some electrical devices have been proposed to measure the moisture content of tea leaves but are not practical. Their performance is influenced by material density and packing. The official oven method is time-consuming. In this study, the moisture content of Oolong tea was measured by the equilibrium relative humidity technique. The equilibrium relative humidity, and temperature, of tea materials were measured by using temperature and relative humidity sensors. Sensors were calibrated, and calibration equations were established to improve accuracy. The moisture content was calculated by using an equilibrium moisture content model. The error of the moisture content determined with this method was within 0.5% w.b. at moisture <15% w.b. Uncertainty analysis revealed that the performance of the humidity sensor had a significant effect on the accuracy of moisture determination. PMID:25153142
Evaluation of hydrologic components of community land model 4 and bias identification
Du, Enhao; Vittorio, Alan Di; Collins, William D.
2015-04-01
Runoff and soil moisture are two key components of the global hydrologic cycle that should be validated at local to global scales in Earth System Models (ESMs) used for climate projection. Here, we have evaluated the runoff and surface soil moisture output by the Community Climate System Model (CCSM) along with 8 other models from the Coupled Model Intercomparison Project (CMIP5) repository using satellite soil moisture observations and stream gauge corrected runoff products. A series of Community Land Model (CLM) runs forced by reanalysis and coupled model outputs was also performed to identify atmospheric drivers of biases and uncertainties inmore » the CCSM. Results indicate that surface soil moisture simulations tend to be positively biased in high latitude areas by most selected CMIP5 models except CCSM, FGOALS, and BCC, which share similar land surface model code. With the exception of GISS, runoff simulations by all selected CMIP5 models were overestimated in mountain ranges and in most of the Arctic region. In general, positive biases in CCSM soil moisture and runoff due to precipitation input error were offset by negative biases induced by temperature input error. Excluding the impact from atmosphere modeling, the global mean of seasonal surface moisture oscillation was out of phase compared to observations in many years during 1985–2004. The CLM also underestimated runoff in the Amazon, central Africa, and south Asia, where soils all have high clay content. We hypothesize that lack of a macropore flow mechanism is partially responsible for this underestimation. However, runoff was overestimated in the areas covered by volcanic ash soils (i.e., Andisols), which might be associated with poor soil porosity representation in CLM. Finally, our results indicate that CCSM predictability of hydrology could be improved by addressing the compensating errors associated with precipitation and temperature and updating the CLM soil representation.« less
NASA Technical Reports Server (NTRS)
Boggs, Johnny; Birgan, Latricia J.; Tsegaye, Teferi; Coleman, Tommy; Soman, Vishwas
1997-01-01
Models are used for numerous application including hydrology. The Modular Modeling System (MMS) is one of the few that can simulate a hydrology process. MMS was tested and used to compare infiltration, soil moisture, daily temperature, and potential and actual evaporation for the Elinsboro sandy loam soil and the Mattapex silty loam soil in the Microwave Radiometer Experiment of Soil Moisture Sensing at Beltsville Agriculture Research Test Site in Maryland. An input file for each location was created to nut the model. Graphs were plotted, and it was observed that the model gave a good representation for evaporation for both plots. In comparing the two plots, it was noted that infiltration and soil moisture tend to peak around the same time, temperature peaks in July and August and the peak evaporation was observed on September 15 and July 4 for the Elinsboro Mattapex plot respectively. MMS can be used successfully to predict hydrological processes as long as the proper input parameters are available.
NASA Astrophysics Data System (ADS)
Rasul, H.; Wu, M.; Olofsson, B.
2017-12-01
Modelling moisture and heat changes in road layers is very important to understand road hydrology and for better construction and maintenance of roads in a sustainable manner. In cold regions due to the freezing/thawing process in the partially saturated material of roads, the modeling task will become more complicated than simple model of flow through porous media without freezing/thawing pores considerations. This study is presenting a 2-D model simulation for a section of highway with considering freezing/thawing and vapor changes. Partial deferential equations (PDEs) are used in formulation of the model. Parameters are optimized from modelling results based on the measured data from test station on E18 highway near Stockholm. Impacts of phase change considerations in the modelling are assessed by comparing the modeled soil moisture with TDR-measured data. The results show that the model can be used for prediction of water and ice content in different layers of the road and at different seasons. Parameter sensitivities are analyzed by implementing a calibration strategy. In addition, the phase change consideration is evaluated in the modeling process, by comparing the PDE model with another model without considerations of freezing/thawing in roads. The PDE model shows high potential in understanding the moisture dynamics in the road system.
He, Song
2017-01-01
This paper presents a model for heat and moisture transfer through firefighters' protective clothing (FPC) during radiation exposure. The model, which accounts for air gaps in the FPC as well as heat transfer through human skin, investigates the effect of different initial moisture contents on the thermal insulation performance of FPC. Temperature, water vapor density, and the volume fraction of liquid water profiles were monitored during the simulation, and the heat quantity absorbed by water evaporation was calculated. Then the maximum durations of heat before the wearer acquires first- and second-degree burns were calculated based on the bioheat transfer equation and the Henriques equation. The results show that both the moisture weight in each layer and the total moisture weight increase linearly within a given environmental humidity level. The initial moisture content in FPC samples significantly influenced the maximum water vapor density. The first- and second-degree burn injury time increase 16 sec and 18 sec when the RH increases from 0% to 90%. The total quantity of heat accounted for by water evaporation was about 10% when the relative humidity (RH) is 80%. Finally, a linear relationship was identified between initial moisture content and the human skin burn injury time before suffering first- and second-degree burn injuries. PMID:28466066
Huang, Dongmei; He, Song
2017-01-01
This paper presents a model for heat and moisture transfer through firefighters' protective clothing (FPC) during radiation exposure. The model, which accounts for air gaps in the FPC as well as heat transfer through human skin, investigates the effect of different initial moisture contents on the thermal insulation performance of FPC. Temperature, water vapor density, and the volume fraction of liquid water profiles were monitored during the simulation, and the heat quantity absorbed by water evaporation was calculated. Then the maximum durations of heat before the wearer acquires first- and second-degree burns were calculated based on the bioheat transfer equation and the Henriques equation. The results show that both the moisture weight in each layer and the total moisture weight increase linearly within a given environmental humidity level. The initial moisture content in FPC samples significantly influenced the maximum water vapor density. The first- and second-degree burn injury time increase 16 sec and 18 sec when the RH increases from 0% to 90%. The total quantity of heat accounted for by water evaporation was about 10% when the relative humidity (RH) is 80%. Finally, a linear relationship was identified between initial moisture content and the human skin burn injury time before suffering first- and second-degree burn injuries.
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.
Integration of Hydrogeophysical Datasets for Improved Water Resource Management in Irrigated Systems
NASA Astrophysics Data System (ADS)
Finkenbiner, C. E.; Franz, T. E.; Heeren, D.; Gibson, J. P.; Russell, M. V.
2016-12-01
With an average irrigation water use efficiency of approximately 45% in the United States, improvements in water management can be made within agricultural systems. Advancements in precision irrigation technologies allow application rates and times to vary within a field. Current limitations in applying these technologies are often attributed to the quantification of soil spatial variability. This work aims to increase our understanding of soil hydrologic fluxes at intermediate spatial scales. Field capacity and wilting point values for a field near Sutherland, NE were downloaded from the USDA SSURGO database. Stationary and roving cosmic-ray neutron probes (CRNP) (sensor measurement volume of 300 m radius sphere and 30 cm vertical soil depth) were combined in order to characterize the spatial and temporal patterns of soil moisture at the site. We used a data merging technique to produce a statistical daily soil moisture product at a range of key spatial scales in support of current irrigation technologies: the individual sprinkler ( 102 m2) for variable rate irrigation, the individual wedge ( 103 m2) for variable speed irrigation, and the quarter section (0.82 km2) for uniform rate irrigation. The results show our CRNP "observed" field capacity was higher compared to the SSURGO products. The measured hydraulic properties from sixty-two soil cores collected from the field correlate well with our "observed" CRNP values. We hypothesize that our results, when provided to irrigators, will decrease water losses due to runoff and deep percolation as sprinkler managers can better estimate irrigation application depths and times in relation to soil moisture depletion below field capacity and above maximum allowable depletion. The incorporation of the CRNP into current irrigation practices has the potential to greatly increase agricultural water use efficiency. Moreover, the defined soil hydraulic properties at various spatial scales offers additional valuable datasets for the land surface modeling community.
NASA Astrophysics Data System (ADS)
Korres, W.; Reichenau, T. G.; Schneider, K.
2013-08-01
Soil moisture is a key variable in hydrology, meteorology and agriculture. Soil moisture, and surface soil moisture in particular, is highly variable in space and time. Its spatial and temporal patterns in agricultural landscapes are affected by multiple natural (precipitation, soil, topography, etc.) and agro-economic (soil management, fertilization, etc.) factors, making it difficult to identify unequivocal cause and effect relationships between soil moisture and its driving variables. The goal of this study is to characterize and analyze the spatial and temporal patterns of surface soil moisture (top 20 cm) in an intensively used agricultural landscape (1100 km2 northern part of the Rur catchment, Western Germany) and to determine the dominant factors and underlying processes controlling these patterns. A second goal is to analyze the scaling behavior of surface soil moisture patterns in order to investigate how spatial scale affects spatial patterns. To achieve these goals, a dynamically coupled, process-based and spatially distributed ecohydrological model was used to analyze the key processes as well as their interactions and feedbacks. The model was validated for two growing seasons for the three main crops in the investigation area: Winter wheat, sugar beet, and maize. This yielded RMSE values for surface soil moisture between 1.8 and 7.8 vol.% and average RMSE values for all three crops of 0.27 kg m-2 for total aboveground biomass and 0.93 for green LAI. Large deviations of measured and modeled soil moisture can be explained by a change of the infiltration properties towards the end of the growing season, especially in maize fields. The validated model was used to generate daily surface soil moisture maps, serving as a basis for an autocorrelation analysis of spatial patterns and scale. Outside of the growing season, surface soil moisture patterns at all spatial scales depend mainly upon soil properties. Within the main growing season, larger scale patterns that are induced by soil properties are superimposed by the small scale land use pattern and the resulting small scale variability of evapotranspiration. However, this influence decreases at larger spatial scales. Most precipitation events cause temporarily higher surface soil moisture autocorrelation lengths at all spatial scales for a short time even beyond the autocorrelation lengths induced by soil properties. The relation of daily spatial variance to the spatial scale of the analysis fits a power law scaling function, with negative values of the scaling exponent, indicating a decrease in spatial variability with increasing spatial resolution. High evapotranspiration rates cause an increase in the small scale soil moisture variability, thus leading to large negative values of the scaling exponent. Utilizing a multiple regression analysis, we found that 53% of the variance of the scaling exponent can be explained by a combination of an independent LAI parameter and the antecedent precipitation.
Moisture Management for High R-Value Walls
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lepage, R.; Schumacher, C.; Lukachko, A.
2013-11-01
This report explains the moisture-related concerns for high R-value wall assemblies and discusses past Building America research work that informs this study. In this project, hygrothermal simulations were prepared for several common approaches to High R-value wall construction in six cities (Houston, Atlanta, Seattle, St. Louis, Chicago, and International Falls) representing a range of climate zones. The modeling program assessed the moisture durability of the wall assemblies based on three primary sources of moisture: construction moisture, air leakage condensation, and bulk water leakage; the report presents results of the study.
Determination of suitable drying curve model for bread moisture loss during baking
NASA Astrophysics Data System (ADS)
Soleimani Pour-Damanab, A. R.; Jafary, A.; Rafiee, S.
2013-03-01
This study presents mathematical modelling of bread moisture loss or drying during baking in a conventional bread baking process. In order to estimate and select the appropriate moisture loss curve equation, 11 different models, semi-theoretical and empirical, were applied to the experimental data and compared according to their correlation coefficients, chi-squared test and root mean square error which were predicted by nonlinear regression analysis. Consequently, of all the drying models, a Page model was selected as the best one, according to the correlation coefficients, chi-squared test, and root mean square error values and its simplicity. Mean absolute estimation error of the proposed model by linear regression analysis for natural and forced convection modes was 2.43, 4.74%, respectively.
Nutrition systems for pressure suits.
NASA Technical Reports Server (NTRS)
Huber, C. S.; Heidelbaugh, N. D.; Rapp, R. M.; Smith, M. C., Jr.
1973-01-01
Nutrition systems were successfully developed in the Apollo Program for astronauts wearing pressure suits during emergency decompression situations and during lunar surface explorations. These nutrition systems consisted of unique dispensers, water, flavored beverages, nutrient-fortified beverages, and intermediate moisture food bars. The emergency decompression system dispensed the nutrition from outside the pressure suit by interfacing with a suit helmet penetration port. The lunar exploration system utilized dispensers stowed within the interior layers of the pressure suit. These systems could be adapted for provision of nutrients in other situations requiring the use of pressure suits.
JPRS Report, Science & Technology, Japan, MITI’s Large-Scale R&D Projects Reviewed
1990-02-08
pollutions, red tide, Active enzymes etc. for cleaners and detergents -- .... .... Intermediates aw materials for r rcosmetics and and medicines moisturizers...PN 00 1H carq 1 0 HZc4 IO -l~ to u .ci~’ *H 0 w 1 Q 0 r - 0 0J w H 04P 04- c0 a) 00 bD O44 0 w w 0 -p 00 021.J4 COQ )a > u0-0 T1 CL Cfp p P H -H14 OL
NASA Astrophysics Data System (ADS)
M Ali, M. K.; Ruslan, M. H.; Muthuvalu, M. S.; Wong, J.; Sulaiman, J.; Yasir, S. Md.
2014-06-01
The solar drying experiment of seaweed using Green V-Roof Hybrid Solar Drier (GVRHSD) was conducted in Semporna, Sabah under the metrological condition in Malaysia. Drying of sample seaweed in GVRHSD reduced the moisture content from about 93.4% to 8.2% in 4 days at average solar radiation of about 600W/m2 and mass flow rate about 0.5 kg/s. Generally the plots of drying rate need more smoothing compared moisture content data. Special cares is needed at low drying rates and moisture contents. It is shown the cubic spline (CS) have been found to be effective for moisture-time curves. The idea of this method consists of an approximation of data by a CS regression having first and second derivatives. The analytical differentiation of the spline regression permits the determination of instantaneous rate. The method of minimization of the functional of average risk was used successfully to solve the problem. This method permits to obtain the instantaneous rate to be obtained directly from the experimental data. The drying kinetics was fitted with six published exponential thin layer drying models. The models were fitted using the coefficient of determination (R2), and root mean square error (RMSE). The modeling of models using raw data tested with the possible of exponential drying method. The result showed that the model from Two Term was found to be the best models describe the drying behavior. Besides that, the drying rate smoothed using CS shows to be effective method for moisture-time curves good estimators as well as for the missing moisture content data of seaweed Kappaphycus Striatum Variety Durian in Solar Dryer under the condition tested.
DOE Office of Scientific and Technical Information (OSTI.GOV)
M Ali, M. K., E-mail: majidkhankhan@ymail.com, E-mail: eutoco@gmail.com; Ruslan, M. H., E-mail: majidkhankhan@ymail.com, E-mail: eutoco@gmail.com; Muthuvalu, M. S., E-mail: sudaram-@yahoo.com, E-mail: jumat@ums.edu.my
2014-06-19
The solar drying experiment of seaweed using Green V-Roof Hybrid Solar Drier (GVRHSD) was conducted in Semporna, Sabah under the metrological condition in Malaysia. Drying of sample seaweed in GVRHSD reduced the moisture content from about 93.4% to 8.2% in 4 days at average solar radiation of about 600W/m{sup 2} and mass flow rate about 0.5 kg/s. Generally the plots of drying rate need more smoothing compared moisture content data. Special cares is needed at low drying rates and moisture contents. It is shown the cubic spline (CS) have been found to be effective for moisture-time curves. The idea ofmore » this method consists of an approximation of data by a CS regression having first and second derivatives. The analytical differentiation of the spline regression permits the determination of instantaneous rate. The method of minimization of the functional of average risk was used successfully to solve the problem. This method permits to obtain the instantaneous rate to be obtained directly from the experimental data. The drying kinetics was fitted with six published exponential thin layer drying models. The models were fitted using the coefficient of determination (R{sup 2}), and root mean square error (RMSE). The modeling of models using raw data tested with the possible of exponential drying method. The result showed that the model from Two Term was found to be the best models describe the drying behavior. Besides that, the drying rate smoothed using CS shows to be effective method for moisture-time curves good estimators as well as for the missing moisture content data of seaweed Kappaphycus Striatum Variety Durian in Solar Dryer under the condition tested.« less
NASA Astrophysics Data System (ADS)
Sanchez-Mejia, Zulia Mayari; Papuga, Shirley A.
2017-11-01
In semiarid regions, where water resources are limited and precipitation dynamics are changing, understanding land surface-atmosphere interactions that regulate the coupled soil moisture-precipitation system is key for resource management and planning. We present a modeling approach to study soil moisture and albedo controls on planetary boundary layer height (PBLh). We used Santa Rita Creosote Ameriflux and Tucson Airport atmospheric sounding data to generate empirical relationships between soil moisture, albedo, and PBLh. Empirical relationships showed that ˜50% of the variation in PBLh can be explained by soil moisture and albedo with additional knowledge gained by dividing the soil profile into two layers. Therefore, we coupled these empirical relationships with soil moisture estimated using a two-layer bucket approach to model PBLh under six precipitation scenarios. Overall we observed that decreases in precipitation tend to limit the recovery of the PBL at the end of the wet season. However, increases in winter precipitation despite decreases in summer precipitation may provide opportunities for positive feedbacks that may further generate more winter precipitation. Our results highlight that the response of soil moisture, albedo, and the PBLh will depend not only on changes in annual precipitation, but also on the frequency and intensity of this change. We argue that because albedo and soil moisture data are readily available at multiple temporal and spatial scales, developing empirical relationships that can be used in land surface-atmosphere applications have great potential for exploring the consequences of climate change.
Arvela, H.; Holmgren, O.; Hänninen, P.
2016-01-01
The effect of soil moisture on seasonal variation in soil air and indoor radon is studied. A brief review of the theory of the effect of soil moisture on soil air radon has been presented. The theoretical estimates, together with soil moisture measurements over a period of 10 y, indicate that variation in soil moisture evidently is an important factor affecting the seasonal variation in soil air radon concentration. Partitioning of radon gas between the water and air fractions of soil pores is the main factor increasing soil air radon concentration. On two example test sites, the relative standard deviation of the calculated monthly average soil air radon concentration was 17 and 26 %. Increased soil moisture in autumn and spring, after the snowmelt, increases soil gas radon concentrations by 10–20 %. In February and March, the soil gas radon concentration is in its minimum. Soil temperature is also an important factor. High soil temperature in summer increased the calculated soil gas radon concentration by 14 %, compared with winter values. The monthly indoor radon measurements over period of 1 y in 326 Finnish houses are presented and compared with the modelling results. The model takes into account radon entry, climate and air exchange. The measured radon concentrations in autumn and spring were higher than expected and it can be explained by the seasonal variation in the soil moisture. The variation in soil moisture is a potential factor affecting markedly to the high year-to-year variation in the annual or seasonal average radon concentrations, observed in many radon studies. PMID:25899611
USDA-ARS?s Scientific Manuscript database
Soil moisture condition is an important indicator for agricultural drought monitoring. Through the Land Parameter Retrieval Model (LPRM), vegetation optical depth (VOD) as well as surface soil moisture (SM) can be retrieved simultaneously from brightness temperature observations from the Advanced Mi...
Challenges in Interpreting and Validating Satellite Soil Moisture Information
USDA-ARS?s Scientific Manuscript database
Global soil moisture products are now being generated routinely using microwave-based satellite observing systems. These include the NASA Soil Moisture Active Passive (SMAP) mission. In order to fully exploit these observations they must be integrated with both in situ measurements and model-based e...
Error characterization of microwave satellite soil moisture data sets using fourier analysis
USDA-ARS?s Scientific Manuscript database
Soil moisture is a key geophysical variable in hydrological and meteorological processes. Accurate and current observations of soil moisture over meso to global scales used as inputs to hydrological, weather and climate modelling will benefit the predictability and understanding of these processes. ...
Error characterization of microwave satellite soil moisture data sets using fourier analysis
USDA-ARS?s Scientific Manuscript database
Abstract: Soil moisture is a key geophysical variable in hydrological and meteorological processes. Accurate and current observations of soil moisture over mesoscale to global scales as inputs to hydrological, weather and climate modelling will benefit the predictability and understanding of these p...
Dirmeyer, Paul A.; Wu, Jiexia; Norton, Holly E.; Dorigo, Wouter A.; Quiring, Steven M.; Ford, Trenton W.; Santanello, Joseph A.; Bosilovich, Michael G.; Ek, Michael B.; Koster, Randal D.; Balsamo, Gianpaolo; Lawrence, David M.
2018-01-01
Four land surface models in uncoupled and coupled configurations are compared to observations of daily soil moisture from 19 networks in the conterminous United States to determine the viability of such comparisons and explore the characteristics of model and observational data. First, observations are analyzed for error characteristics and representation of spatial and temporal variability. Some networks have multiple stations within an area comparable to model grid boxes; for those we find that aggregation of stations before calculation of statistics has little effect on estimates of variance, but soil moisture memory is sensitive to aggregation. Statistics for some networks stand out as unlike those of their neighbors, likely due to differences in instrumentation, calibration and maintenance. Buried sensors appear to have less random error than near-field remote sensing techniques, and heat dissipation sensors show less temporal variability than other types. Model soil moistures are evaluated using three metrics: standard deviation in time, temporal correlation (memory) and spatial correlation (length scale). Models do relatively well in capturing large-scale variability of metrics across climate regimes, but poorly reproduce observed patterns at scales of hundreds of kilometers and smaller. Uncoupled land models do no better than coupled model configurations, nor do reanalyses outperform free-running models. Spatial decorrelation scales are found to be difficult to diagnose. Using data for model validation, calibration or data assimilation from multiple soil moisture networks with different types of sensors and measurement techniques requires great caution. Data from models and observations should be put on the same spatial and temporal scales before comparison. PMID:29645013
NASA Technical Reports Server (NTRS)
Dirmeyer, Paul A.; Wu, Jiexia; Norton, Holly E.; Dorigo, Wouter A.; Quiring, Steven M.; Ford, Trenton W.; Santanello, Joseph A., Jr.; Bosilovich, Michael G.; Ek, Michael B.; Koster, Randal Dean;
2016-01-01
Four land surface models in uncoupled and coupled configurations are compared to observations of daily soil moisture from 19 networks in the conterminous United States to determine the viability of such comparisons and explore the characteristics of model and observational data. First, observations are analyzed for error characteristics and representation of spatial and temporal variability. Some networks have multiple stations within an area comparable to model grid boxes; for those we find that aggregation of stations before calculation of statistics has little effect on estimates of variance, but soil moisture memory is sensitive to aggregation. Statistics for some networks stand out as unlike those of their neighbors, likely due to differences in instrumentation, calibration and maintenance. Buried sensors appear to have less random error than near-field remote sensing techniques, and heat dissipation sensors show less temporal variability than other types. Model soil moistures are evaluated using three metrics: standard deviation in time, temporal correlation (memory) and spatial correlation (length scale). Models do relatively well in capturing large-scale variability of metrics across climate regimes, but poorly reproduce observed patterns at scales of hundreds of kilometers and smaller. Uncoupled land models do no better than coupled model configurations, nor do reanalyses out perform free-running models. Spatial decorrelation scales are found to be difficult to diagnose. Using data for model validation, calibration or data assimilation from multiple soil moisture networks with different types of sensors and measurement techniques requires great caution. Data from models and observations should be put on the same spatial and temporal scales before comparison.
Dirmeyer, Paul A; Wu, Jiexia; Norton, Holly E; Dorigo, Wouter A; Quiring, Steven M; Ford, Trenton W; Santanello, Joseph A; Bosilovich, Michael G; Ek, Michael B; Koster, Randal D; Balsamo, Gianpaolo; Lawrence, David M
2016-04-01
Four land surface models in uncoupled and coupled configurations are compared to observations of daily soil moisture from 19 networks in the conterminous United States to determine the viability of such comparisons and explore the characteristics of model and observational data. First, observations are analyzed for error characteristics and representation of spatial and temporal variability. Some networks have multiple stations within an area comparable to model grid boxes; for those we find that aggregation of stations before calculation of statistics has little effect on estimates of variance, but soil moisture memory is sensitive to aggregation. Statistics for some networks stand out as unlike those of their neighbors, likely due to differences in instrumentation, calibration and maintenance. Buried sensors appear to have less random error than near-field remote sensing techniques, and heat dissipation sensors show less temporal variability than other types. Model soil moistures are evaluated using three metrics: standard deviation in time, temporal correlation (memory) and spatial correlation (length scale). Models do relatively well in capturing large-scale variability of metrics across climate regimes, but poorly reproduce observed patterns at scales of hundreds of kilometers and smaller. Uncoupled land models do no better than coupled model configurations, nor do reanalyses outperform free-running models. Spatial decorrelation scales are found to be difficult to diagnose. Using data for model validation, calibration or data assimilation from multiple soil moisture networks with different types of sensors and measurement techniques requires great caution. Data from models and observations should be put on the same spatial and temporal scales before comparison.
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.
Reconstruction of droughts in India using multiple land-surface models (1951-2015)
NASA Astrophysics Data System (ADS)
Mishra, Vimal; Shah, Reepal; Azhar, Syed; Shah, Harsh; Modi, Parth; Kumar, Rohini
2018-04-01
India has witnessed some of the most severe historical droughts in the current decade, and severity, frequency, and areal extent of droughts have been increasing. As a large part of the population of India is dependent on agriculture, soil moisture drought affecting agricultural activities (crop yields) has significant impacts on socio-economic conditions. Due to limited observations, soil moisture is generally simulated using land-surface hydrological models (LSMs); however, these LSM outputs have uncertainty due to many factors, including errors in forcing data and model parameterization. Here we reconstruct agricultural drought events over India during the period of 1951-2015 based on simulated soil moisture from three LSMs, the Variable Infiltration Capacity (VIC), the Noah, and the Community Land Model (CLM). Based on simulations from the three LSMs, we find that major drought events occurred in 1987, 2002, and 2015 during the monsoon season (June through September). During the Rabi season (November through February), major soil moisture droughts occurred in 1966, 1973, 2001, and 2003. Soil moisture droughts estimated from the three LSMs are comparable in terms of their spatial coverage; however, differences are found in drought severity. Moreover, we find a higher uncertainty in simulated drought characteristics over a large part of India during the major crop-growing season (Rabi season, November to February: NDJF) compared to those of the monsoon season (June to September: JJAS). Furthermore, uncertainty in drought estimates is higher for severe and localized droughts. Higher uncertainty in the soil moisture droughts is largely due to the difference in model parameterizations (especially soil depth), resulting in different persistence of soil moisture simulated by the three LSMs. Our study highlights the importance of accounting for the LSMs' uncertainty and consideration of the multi-model ensemble system for the real-time monitoring and prediction of drought over India.
Examining Changes to the Madden-Julian Oscillation in a Warmer Climate Using CMIP5 Models
NASA Astrophysics Data System (ADS)
Rushley, Stephanie
Five models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) that reasonably represent the Madden-Julian Oscillation (MJO) are used to examine the response of the MJO to greenhouse gas induced warming. Changes in the MJO's amplitude, zonal scale, and phase speed are examined using daily-mean precipitation during boreal winter (November to April) when the MJO is strongest. The MJO precipitation variance increases with tropics mean surface temperature. However, the westward moving waves of the same temporal and spatial scales increase at about the same rate, suggesting that the maintenance mechanism for the MJO does not change with warming. On the other hand, a robust increase in phase speed of the MJO is found with a rate of 5-12% per degree of surface warming. The robust increase in the MJO phase speed are examined using the linear moisture wave theory of Adames and Kim (2016). In this theory, the MJO phase speed is determined by the horizontal moisture gradient in the lower troposphere, the gross dry stability, the convective moisture adjustment timescale, and zonal wavenumber of the MJO. All CMIP5 models examined show an increase in the horizontal humidity gradient, the gross dry stability and the convective moisture adjustment timescale, while exhibiting a decrease in the zonal wavenumber of the MJO. The increase in the horizontal humidity gradient and zonal scale of the MJO act to increase the speed of the MJO by enhancing horizontal moisture advection associated with the MJO, while the gross dry stability and convective moisture adjustment timescale act to slow down the MJO by dampening the horizontal moisture advection process. In all the models, the combined effects of the four key parameters act to speed up the MJO, matching the calculated phase speed changes with warming in the models.