Sensitivity of Polygonum aviculare Seeds to Light as Affected by Soil Moisture Conditions
Batlla, Diego; Nicoletta, Marcelo; Benech-Arnold, Roberto
2007-01-01
Background and Aims It has been hypothesized that soil moisture conditions could affect the dormancy status of buried weed seeds, and, consequently, their sensitivity to light stimuli. In this study, an investigation is made of the effect of different soil moisture conditions during cold-induced dormancy loss on changes in the sensitivity of Polygonum aviculare seeds to light. Methods Seeds buried in pots were stored under different constant and fluctuating soil moisture environments at dormancy-releasing temperatures. Seeds were exhumed at regular intervals during storage and were exposed to different light treatments. Changes in the germination response of seeds to light treatments during storage under the different moisture environments were compared in order to determine the effect of soil moisture on the sensitivity to light of P. aviculare seeds. Key Results Seed acquisition of low-fluence responses during dormancy release was not affected by either soil moisture fluctuations or different constant soil moisture contents. On the contrary, different soil moisture environments affected seed acquisition of very low fluence responses and the capacity of seeds to germinate in the dark. Conclusions The results indicate that under field conditions, the sensitivity to light of buried weed seeds could be affected by the soil moisture environment experienced during the dormancy release season, and this could affect their emergence pattern. PMID:17430979
USDA-ARS?s Scientific Manuscript database
This paper aims to investigate how surface soil moisture data assimilation affects each hydrologic process and how spatially varying inputs affect the potential capability of surface soil moisture assimilation at the watershed scale. The Ensemble Kalman Filter (EnKF) is coupled with a watershed scal...
Bento, F de M M; Marques, R N; Costa, M L Z; Walder, J M M; Silva, A P; Parra, J R P
2010-08-01
This study aimed to evaluate adult emergence and duration of the pupal stage of the Mediterranean fruit fly, Ceratitis capitata (Wiedemann), and emergence of the fruit fly parasitoid, Diachasmimorpha longicaudata (Ashmead), under different moisture conditions in four soil types, using soil water matric potential. Pupal stage duration in C. capitata was influenced differently for males and females. In females, only soil type affected pupal stage duration, which was longer in a clay soil. In males, pupal stage duration was individually influenced by moisture and soil type, with a reduction in pupal stage duration in a heavy clay soil and in a sandy clay, with longer duration in the clay soil. As matric potential decreased, duration of the pupal stage of C. capitata males increased, regardless of soil type. C. capitata emergence was affected by moisture, regardless of soil type, and was higher in drier soils. The emergence of D. longicaudata adults was individually influenced by soil type and moisture factors, and the number of emerged D. longicaudata adults was three times higher in sandy loam and lower in a heavy clay soil. Always, the number of emerged adults was higher at higher moisture conditions. C. capitata and D. longicaudata pupal development was affected by moisture and soil type, which may facilitate pest sampling and allow release areas for the parasitoid to be defined under field conditions.
Ngo, H T T; Cavagnaro, T R
2018-01-24
We aimed to investigate the combined impacts of compost addition and pre-planting soil moisture conditions, on plant-available nutrients, and subsequent impacts on the biomass, nutrition and formation of AM by two important crop species. A glasshouse study was undertaken in which wheat and tomato plants were grown in compost amended or un-amended soil that was subjected to different moisture regimes prior to planting. The availability of P was strongly influenced by compost addition, but not pre-planting moisture conditions. In contrast, mineral N pools were affected by compost addition and pre-planting soil moisture conditions in complex ways. These changes in nutrient availability affected plant biomass, nutrient uptake and formation of AM. In general, plant performance was better where pre-planting soil moisture conditions were wet or dry, and worse where they involved a wet/dry cycle, and mycorrhizal colonisation was lower where compost was added to the soil. That pre-planting moisture conditions affect the biomass of subsequent crops is an important finding, the potential implications of which are considered here.
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.
Interpretation of in situ tests as affected by soil suction.
DOT National Transportation Integrated Search
2013-07-01
Soil moisture conditions are subject to change depending on the season in which they are tested. In : unsaturated soils the moisture at which a soil is tested can directly affect strength and stiffness of the : material. In situ testing is commonly u...
Cao, Zhiming; Rossi, Lorenzo; Stowers, Cheyenne; Zhang, Weilan; Lombardini, Leonardo; Ma, Xingmao
2018-01-01
The ongoing global climate change raises concerns over the decreasing moisture content in agricultural soils. Our research investigated the physiological impact of two types of cerium oxide nanoparticles (CeO 2 NPs) on soybean at different moisture content levels. One CeO 2 NP was positively charged on the surface and the other negatively charged due to the polyvinylpyrrolidone (PVP) coating. The results suggest that the effect of CeO 2 NPs on plant photosynthesis and water use efficiency (WUE) was dependent upon the soil moisture content. Both types of CeO 2 NPs exhibited consistently positive impacts on plant photosynthesis at the moisture content above 70% of field capacity (θ fc ). Similar positive impact of CeO 2 NPs was not observed at 55% θ fc , suggesting that the physiological impact of CeO 2 NPs was dependent upon the soil moisture content. The results also revealed that V Cmax (maximum carboxylation rate) was affected by CeO 2 NPs, indicating that CeO 2 NPs affected the Rubisco activity which governs carbon assimilation in photosynthesis. In conclusion, CeO 2 NPs demonstrated significant impacts on the photosynthesis and WUE of soybeans and such impacts were affected by the soil moisture content. Graphical abstract Soil moisture content affects plant cerium oxide nanoparticle interactions.
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.
Scott D. Roberts; Constance A. Harrington; Thomas A. Terry
2005-01-01
Decisions made during stand regeneration that affect subsequent levels of competing vegetation and residual biomass can have important short-term consequences for early stand growth, and may affect long-term site productivity. Competing vegetation clearly affects the availability of site resources such as soil moisture and nutrients. Harvest residues can also impact...
Soil-Site Factors Affecting Southern Upland Oak Managment and Growth
John K. Francis
1980-01-01
Soil supplies trees with physical support, moisture, oxygen, and nutrients. Amount of moisture most limits tree growth; and soil and topographic factors such as texture and aspect, which influence available soil moisture. are most useful in predicting growth. Equations that include soil and topographic variables can be used to predict site index. Foresters can also...
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
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yan, Zhifeng; Liu, Chongxuan; Todd-Brown, Katherine E.
The relationship between microbial respiration rate and soil moisture content is an important property for understanding and predicting soil organic carbon degradation, CO 2 production and emission, and their subsequent effects on climate change. This paper reports a pore-scale modeling study to investigate the response of heterotrophic respiration to moisture conditions in soils and to evaluate various factors that affect this response. X-ray computed tomography was used to derive soil pore structures, which were then used for pore-scale model investigation. The pore-scale results were then averaged to calculate the effective respiration rates as a function of water content in soils.more » The calculated effective respiration rate first increases and then decreases with increasing soil water content, showing a maximum respiration rate at water saturation degree of 0.75 that is consistent with field and laboratory observations. The relationship between the respiration rate and moisture content is affected by various factors, including pore-scale organic carbon bioavailability, the rate of oxygen delivery, soil pore structure and physical heterogeneity, soil clay content, and microbial drought resistivity. Simulations also illustrates that a larger fraction of CO 2 produced from microbial respiration can be accumulated inside soil cores under higher saturation conditions, implying that CO 2 flux measured on the top of soil cores may underestimate or overestimate true soil respiration rates under dynamic moisture conditions. Overall, this study provides mechanistic insights into the soil respiration response to the change in moisture conditions, and reveals a complex relationship between heterotrophic microbial respiration rate and moisture content in soils that is affected by various hydrological, geochemical, and biophysical factors.« less
USDA-ARS?s Scientific Manuscript database
Soil moisture affects the spatial variation of land–atmosphere interactions through its in'uence on the balance of latent and sensible heat 'ux. Wetter soils are more prone to 'ooding because a smaller fraction of rainfall can in'ltrate into the soil. The Soil Moisture and Oceanic Salinity (SMOS) sa...
A microwave systems approach to measuring root zone soil moisture
NASA Technical Reports Server (NTRS)
Newton, R. W.; Paris, J. F.; Clark, B. V.
1983-01-01
Computer microwave satellite simulation models were developed and the program was used to test the ability of a coarse resolution passive microwave sensor to measure soil moisture over large areas, and to evaluate the effect of heterogeneous ground covers with the resolution cell on the accuracy of the soil moisture estimate. The use of realistic scenes containing only 10% to 15% bare soil and significant vegetation made it possible to observe a 60% K decrease in brightness temperature from a 5% soil moisture to a 35% soil moisture at a 21 cm microwave wavelength, providing a 1.5 K to 2 K per percent soil moisture sensitivity to soil moisture. It was shown that resolution does not affect the basic ability to measure soil moisture with a microwave radiometer system. Experimental microwave and ground field data were acquired for developing and testing a root zone soil moisture prediction algorithm. The experimental measurements demonstrated that the depth of penetration at a 21 cm microwave wavelength is not greater than 5 cm.
High-resolution soil moisture mapping in Afghanistan
NASA Astrophysics Data System (ADS)
Hendrickx, Jan M. H.; Harrison, J. Bruce J.; Borchers, Brian; Kelley, Julie R.; Howington, Stacy; Ballard, Jerry
2011-06-01
Soil moisture conditions have an impact upon virtually all aspects of Army activities and are increasingly affecting its systems and operations. Soil moisture conditions affect operational mobility, detection of landmines and unexploded ordinance, natural material penetration/excavation, military engineering activities, blowing dust and sand, watershed responses, and flooding. This study further explores a method for high-resolution (2.7 m) soil moisture mapping using remote satellite optical imagery that is readily available from Landsat and QuickBird. The soil moisture estimations are needed for the evaluation of IED sensors using the Countermine Simulation Testbed in regions where access is difficult or impossible. The method has been tested in Helmand Province, Afghanistan, using a Landsat7 image and a QuickBird image of April 23 and 24, 2009, respectively. In previous work it was found that Landsat soil moisture can be predicted from the visual and near infra-red Landsat bands1-4. Since QuickBird bands 1-4 are almost identical to Landsat bands 1- 4, a Landsat soil moisture map can be downscaled using QuickBird bands 1-4. However, using this global approach for downscaling from Landsat to QuickBird scale yielded a small number of pixels with erroneous soil moisture values. Therefore, the objective of this study is to examine how the quality of the downscaled soil moisture maps can be improved by using a data stratification approach for the development of downscaling regression equations for each landscape class. It was found that stratification results in a reliable downscaled soil moisture map with a spatial resolution of 2.7 m.
NASA Astrophysics Data System (ADS)
Gines, G. A.; Bea, J. G.; Palaoag, T. D.
2018-03-01
Soil serves a medium for plants growth. One factor that affects soil moisture is drought. Drought has been a major cause of agricultural disaster. Agricultural drought is said to occur when soil moisture is insufficient to meet crop water requirements, resulting in yield losses. In this research, it aimed to characterize soil moisture level for Rice and Maize Crops using Arduino and applying fuzzy logic. System architecture for soil moisture sensor and water pump were the basis in developing the equipment. The data gathered was characterized by applying fuzzy logic. Based on the results, applying fuzzy logic in validating the characterization of soil moisture level for Rice and Maize crops is accurate as attested by the experts. This will help the farmers in monitoring the soil moisture level of the Rice and Maize crops.
Wang, Xinbing; Zhou, Baoyuan; Sun, Xuefang; Yue, Yang; Ma, Wei; Zhao, Ming
2015-01-01
The spatial distribution of the root system through the soil profile has an impact on moisture and nutrient uptake by plants, affecting growth and productivity. The spatial distribution of the roots, soil moisture, and fertility are affected by tillage practices. The combination of high soil density and the presence of a soil plow pan typically impede the growth of maize (Zea mays L.).We investigated the spatial distribution coordination of the root system, soil moisture, and N status in response to different soil tillage treatments (NT: no-tillage, RT: rotary-tillage, SS: subsoiling) and the subsequent impact on maize yield, and identify yield-increasing mechanisms and optimal soil tillage management practices. Field experiments were conducted on the Huang-Huai-Hai plain in China during 2011 and 2012. The SS and RT treatments significantly reduced soil bulk density in the top 0-20 cm layer of the soil profile, while SS significantly decreased soil bulk density in the 20-30 cm layer. Soil moisture in the 20-50 cm profile layer was significantly higher for the SS treatment compared to the RT and NT treatment. In the 0-20 cm topsoil layer, the NT treatment had higher soil moisture than the SS and RT treatments. Root length density of the SS treatment was significantly greater than density of the RT and NT treatments, as soil depth increased. Soil moisture was reduced in the soil profile where root concentration was high. SS had greater soil moisture depletion and a more concentration root system than RT and NT in deep soil. Our results suggest that the SS treatment improved the spatial distribution of root density, soil moisture and N states, thereby promoting the absorption of soil moisture and reducing N leaching via the root system in the 20-50 cm layer of the profile. Within the context of the SS treatment, a root architecture densely distributed deep into the soil profile, played a pivotal role in plants' ability to access nutrients and water. An optimal combination of deeper deployment of roots and resource (water and N) availability was realized where the soil was prone to leaching. The correlation between the depletion of resources and distribution of patchy roots endorsed the SS tillage practice. It resulted in significantly greater post-silking biomass and grain yield compared to the RT and NT treatments, for summer maize on the Huang-Huai-Hai plain.
Wang, Xinbing; Zhou, Baoyuan; Sun, Xuefang; Yue, Yang; Ma, Wei; Zhao, Ming
2015-01-01
The spatial distribution of the root system through the soil profile has an impact on moisture and nutrient uptake by plants, affecting growth and productivity. The spatial distribution of the roots, soil moisture, and fertility are affected by tillage practices. The combination of high soil density and the presence of a soil plow pan typically impede the growth of maize (Zea mays L.).We investigated the spatial distribution coordination of the root system, soil moisture, and N status in response to different soil tillage treatments (NT: no-tillage, RT: rotary-tillage, SS: subsoiling) and the subsequent impact on maize yield, and identify yield-increasing mechanisms and optimal soil tillage management practices. Field experiments were conducted on the Huang-Huai-Hai plain in China during 2011 and 2012. The SS and RT treatments significantly reduced soil bulk density in the top 0–20 cm layer of the soil profile, while SS significantly decreased soil bulk density in the 20–30 cm layer. Soil moisture in the 20–50 cm profile layer was significantly higher for the SS treatment compared to the RT and NT treatment. In the 0-20 cm topsoil layer, the NT treatment had higher soil moisture than the SS and RT treatments. Root length density of the SS treatment was significantly greater than density of the RT and NT treatments, as soil depth increased. Soil moisture was reduced in the soil profile where root concentration was high. SS had greater soil moisture depletion and a more concentration root system than RT and NT in deep soil. Our results suggest that the SS treatment improved the spatial distribution of root density, soil moisture and N states, thereby promoting the absorption of soil moisture and reducing N leaching via the root system in the 20–50 cm layer of the profile. Within the context of the SS treatment, a root architecture densely distributed deep into the soil profile, played a pivotal role in plants’ ability to access nutrients and water. An optimal combination of deeper deployment of roots and resource (water and N) availability was realized where the soil was prone to leaching. The correlation between the depletion of resources and distribution of patchy roots endorsed the SS tillage practice. It resulted in significantly greater post-silking biomass and grain yield compared to the RT and NT treatments, for summer maize on the Huang-Huai-Hai plain. PMID:26098548
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...
NASA Astrophysics Data System (ADS)
Cao, W.; Sheng, Y.
2017-12-01
The soil moisture movement is an important carrier of material cycle and energy flow among the various geo-spheres in the cold regions. It is very critical to protect the alpine ecology and hydrologic cycle in Qinghai-Tibet Plateau. Especially, it becomes one of the key problems to reveal the spatial-temporal variability of soil moisture movement and its main influence factors in earth system science. Thus, this research takes the north slope of Bayan Har Mountains in Qinghai-Tibet Plateau as a case study. The present study firstly investigates the change of permafrost moisture in different slope positions and depths. Based on this investigation, this article attempts to investigate the spatial variability of permafrost moisture and identifies the key influence factors in different terrain conditions. The method of classification and regression tree (CART) is adopted to identify the main controlling factors influencing the soil moisture movement. And the relationships between soil moisture and environmental factors are revealed by the use of the method of canonical correspondence analysis (CCA). The results show that: 1) the change of the soil moisture on the permafrost slope is divided into 4 stages, including the freezing stability phase, the rapid thawing phase, the thawing stability phase and the fast freezing phase; 2) this greatly enhances the horizontal flow in the freezing period due to the terrain slope and the freezing-thawing process. Vertical migration is the mainly form of the soil moisture movement. It leads to that the soil-moisture content in the up-slope is higher than that in the down-slope. On the contrary, the soil-moisture content in the up-slope is lower than that in the down-slope during the melting period; 3) the main environmental factors which affect the slope-permafrost soil-moisture are elevation, soil texture, soil temperature and vegetation coverage. But there are differences in the impact factors of the soil moisture in different freezing-thawing stages; 4) the main factors that affect the slope-permafrost soil-moisture at the shallow depth of 0-20cm are slope, elevation and vegetation coverage. And the main factors influencing the soil moisture at the middle and lower depth are complex.
Topographic effects on denitrification in drained agricultural fields
USDA-ARS?s Scientific Manuscript database
Denitrification is affected by soil moisture, while soil moisture can be affected by topography. Therefore, denitrification can be spatially correlated to topographic gradients. Three prior converted fields on the Delmarva Peninsula were sampled spatially for denitrification enzyme activity. The up...
NASA Astrophysics Data System (ADS)
Chang, Ni-Bin; Xuan, Zhemin; Wimberly, Brent
2011-09-01
Soil moisture and evapotranspiration (ET) is affected by both water and energy balances in the soilvegetation- atmosphere system, it involves many complex processes in the nexus of water and thermal cycles at the surface of the Earth. These impacts may affect the recharge of the upper Floridian aquifer. The advent of urban hydrology and remote sensing technologies opens new and innovative means to undertake eventbased assessment of ecohydrological effects in urban regions. For assessing these landfalls, the multispectral Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing images can be used for the estimation of such soil moisture change in connection with two other MODIS products - Enhanced Vegetation Index (EVI), Land Surface Temperature (LST). Supervised classification for soil moisture retrieval was performed for Tampa Bay area on the 2 kmx2km grid with MODIS images. Machine learning with genetic programming model for soil moisture estimation shows advances in image processing, feature extraction, and change detection of soil moisture. ET data that were derived by Geostationary Operational Environmental Satellite (GOES) data and hydrologic models can be retrieved from the USGS web site directly. Overall, the derived soil moisture in comparison with ET time series changes on a seasonal basis shows that spatial and temporal variations of soil moisture and ET that are confined within a defined region for each type of surfaces, showing clustered patterns and featuring space scatter plot in association with the land use and cover map. These concomitant soil moisture patterns and ET fluctuations vary among patches, plant species, and, especially, location on the urban gradient. Time series plots of LST in association with ET, soil moisture and EVI reveals unique ecohydrological trends. Such ecohydrological assessment can be applied for supporting the urban landscape management in hurricane-stricken regions.
Southern U.S. Soil Moisture Map
2015-05-19
Southern U.S. NASA's SMAP soil moisture retrievals from April 27, 2015, when severe storms were affecting Texas. Top: radiometer data alone. Bottom: combined radar and radiometer data with a resolution of 5.6 miles (9 kilometers). The combined product reveals more detailed surface soil moisture features. http://photojournal.jpl.nasa.gov/catalog/PIA19338
Response of deep soil moisture to land use and afforestation in the semi-arid Loess Plateau, China
NASA Astrophysics Data System (ADS)
Yang, Lei; Wei, Wei; Chen, Liding; Mo, Baoru
2012-12-01
SummarySoil moisture is an effective water source for plant growth in the semi-arid Loess Plateau of China. Characterizing the response of deep soil moisture to land use and afforestation is important for the sustainability of vegetation restoration in this region. In this paper, the dynamics of soil moisture were quantified to evaluate the effect of land use on soil moisture at a depth of 2 m. Specifically, the gravimetric soil moisture content was measured in the soil layer between 0 and 8 m for five land use types in the Longtan catchment of the western Loess Plateau. The land use types included traditional farmland, native grassland, and lands converted from traditional farmland (pasture grassland, shrubland and forestland). Results indicate that the deep soil moisture content decreased more than 35% after land use conversion, and a soil moisture deficit appeared in all types of land with introduced vegetation. The introduced vegetation decreased the soil moisture content to levels lower than the reference value representing no human impact in the entire 0-8 m soil profile. No significant differences appeared between different land use types and introduced vegetation covers, especially in deeper soil layers, regardless of which plant species were introduced. High planting density was found to be the main reason for the severe deficit of soil moisture. Landscape management activities such as tillage activities, micro-topography reconstruction, and fallowed farmland affected soil moisture in both shallow and deep soil layers. Tillage and micro-topography reconstruction can be used as effective countermeasures to reduce the soil moisture deficit due to their ability to increase soil moisture content. For sustainable vegetation restoration in a vulnerable semi-arid region, the plant density should be optimized with local soil moisture conditions and appropriate landscape management practices.
USDA-ARS?s Scientific Manuscript database
Precipitation limits primary production by affecting soil moisture, and soil type interacts with soil moisture to determine soil water availability to plants. We used ALMANAC, a process-based model, to simulate switchgrass (Panicum virgatum var. Alamo) biomass production in Central Texas under thre...
NASA Astrophysics Data System (ADS)
Wlostowski, A. N.; Gooseff, M. N.; Adams, B. J.
2018-01-01
Antarctic soil ecosystems are strongly controlled by abiotic habitat variables. Regional climate change in the McMurdo Dry Valleys is expected to cause warming over the next century, leading to an increase in frequency of freeze-thaw cycling in the soil habitat. Previous studies show that physiological stress associated with freeze-thaw cycling adversely affects invertebrate populations by decreasing abundance and positively selecting for larger body sizes. However, it remains unclear whether or not climate warming will indeed enhance the frequency of annual freeze-thaw cycling and associated physiological stresses. This research quantifies the frequency, rate, and spatial heterogeneity of active layer freezing to better understand how regional climate change may affect active layer soil thermodynamics, and, in turn, affect soil macroinvertebrate communities. Shallow active layer temperature, specific conductance, and soil moisture were observed along natural wetness gradients. Field observations show that the frequency and rate of freeze events are nonlinearly related to freezable soil moisture (θf). Over a 2 year period, soils at θf < 0.080 m3/m3 experienced between 15 and 35 freeze events and froze rapidly compared to soils with θf > 0.080 m3/m3, which experienced between 2 and 6 freeze events and froze more gradually. A numerical soil thermodynamic model is able to simulate observed freezing rates across a range of θf, reinforcing a well-known causal relationship between soil moisture and active layer freezing dynamics. Findings show that slight increases in soil moisture can potentially offset the effect of climate warming on exacerbating soil freeze-thaw cycling.
NASA Technical Reports Server (NTRS)
Tsegaye, T.; Coleman, T.; Senwo, Z.; Shaffer, D.; Zou, X.
1998-01-01
Little is known about the landuse management effect on soil moisture and soil pH distribution on a landscape covered with dense tropical forest vegetation. This study was conducted at three locations where the history of the landuse management is different. Soil moisture was measured using a 6-cm three-rod Time Domain Reflectometery (TDR) probe. Disturbed soil samples were taken from the top 5-cm at the up, mid, and foothill landscape position from the same spots where soil moisture was measured. The results showed that soil moisture varies with landscape position and depth at all three locations. Soil pH and moisture variability were found to be affected by the change in landuse management and landscape position. Soil moisture distribution usually expected to be relatively higher in the foothill (P3) area of these forests than the uphill (P1) position. However, our results indicated that in the Luquillo and Guanica site the surface soil moisture was significantly higher for P1 than P3 position. These suggest that the surface and subsurface drainage in these two sites may have been poor due to the nature of soil formation and type.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gu, Lianhong; Meyers, T. P.; Pallardy, Stephen G.
2006-01-01
The purpose of this paper is to examine the mechanism that controls the variation of surface energy partitioning between latent and sensible heat fluxes at a temperate deciduous forest site in central Missouri, USA. Taking advantage of multiple micrometeorological and ecophysiological measurements and a prolonged drought in the middle of the 2005 growing season at this site, we studied how soil moisture, atmospheric vapor pressure deficit (VPD), and net radiation affected surface energy partitioning. We stratified these factors to minimize potential confounding effects of correlation among them. We found that all three factors had direct effects on surface energy partitioning,more » but more important, all three factors also had crucial indirect effects. The direct effect of soil moisture was characterized by a rapid decrease in Bowen ratio with increasing soil moisture when the soil was dry and by insensitivity of Bowen ratio to variations in soil moisture when the soil was wet. However, the rate of decrease in Bowen ratio when the soil was dry and the level of soil moisture above which Bowen ratio became insensitive to changes in soil moisture depended on atmospheric conditions. The direct effect of increased net radiation was to increase Bowen ratio. The direct effect of VPD was very nonlinear: Increased VPD decreased Bowen ratio at low VPD but increased Bowen ratio at high VPD. The indirect effects were much more complicated. Reduced soil moisture weakened the influence of VPD but enhanced the influence of net adiation on surface energy partitioning. Soil moisture also controlled how net radiation influenced the relationship between surface energy partitioning and VPD and how VPD affected the relationship between surface energy partitioning and net radiation. Furthermore, both increased VPD and increased net radiation enhanced the sensitivity of Bowen ratio to changes in soil moisture and the effect of drought on surface energy partitioning. The direct and indirect effects of atmospheric conditions and soil moisture on surface energy partitioning identified in this paper provide a target for testing atmospheric general circulation models in their representation of land-atmosphere coupling.« less
NASA Astrophysics Data System (ADS)
Chen, Li; Wang, Wenke; Zhang, Zaiyong; Wang, Zhoufeng; Wang, Qiangmin; Zhao, Ming; Gong, Chengcheng
2018-04-01
Soil surface evaporation is a significant component of the hydrological cycle, occurring at the interface between the atmosphere and vadose zone, but it is affected by factors such as groundwater level, soil properties, solar radiation and others. In order to understand the soil evaporation characteristics in arid regions, a field experiment was conducted in the Ordos Basin, central China, and high accuracy sensors of soil moisture, moisture potential and temperature were installed in three field soil profiles with water-table depths (WTDs) of about 0.4, 1.4 and 2.2 m. Soil-surface-evaporation values were estimated by observed data combined with Darcy's law. Results showed that: (1) soil-surface-evaporation rate is linked to moisture content and it is also affected by air temperature. When there is sufficient moisture in the soil profile, soil evaporation increases with rising air temperature. For a WTD larger than the height of capillary rise, the soil evaporation is related to soil moisture content, and when air temperature is above 25 °C, the soil moisture content reduces quickly and the evaporation rate lowers; (2) phreatic water contributes to soil surface evaporation under conditions in which the WTD is within the capillary fringe. This indicates that phreatic water would not participate in soil evaporation for a WTD larger than the height of capillary rise. This finding developed further the understanding of phreatic evaporation, and this study provides valuable information on recognized soil evaporation processes in the arid environment.
NASA Astrophysics Data System (ADS)
Feng, Tianjiao; Wei, Wei; Chen, Liding; Yu, Yang
2017-04-01
In the dryland regions, soil moisture is the main factor to determine vegetation growth and ecosystem restoration. Land preparation and vegetation restoration are the principal means for improving soil water content(SWC). Thus, it is important to analyze the coupling role of these two means on soil moisture. In this study, soil moisture were monitored at a semi-arid loess hilly catchment of China, during the growing season of 2014 and 2015. Four different land preparation methods (level ditches, fish-scale pits, adverse grade tablelands and level benches)and vegetation types(Prunus armeniaca, Platycladus orientalis, Platycladus orientalis and Caragana microphylla) were included in the experimental design. Our results showed that: (1)Soil moisture content differed across land preparation types, which is higher for fish-scale pits and decreased in the order of level ditches and adverse grade tablelands.(2) Rainwater harvesting capacity of fish-scale pits is greater than adverse grade tablelands. However the water holding capacity is much higher at soils prepared with the adverse grade tablelands method than the ones prepared by fish-scale pits methods. (3) When land preparation method is similar, vegetation play a key role in soil moisture variation. For example, the mean soil moisture under a Platycladus orientalis field is 26.72% higher than a Pinus tabulaeformis field, with the same land preparation methods. (4)Soil moisture in deeper soil layers is more affected by changes in the vegetation cover while soil moisture in the shallower layers is more affected by the variation in the land preparation methods. Therefore, we suggest that vegetation types such as: Platycladus orientalisor as well as soil preparation methods such as level ditch and fish-scale pit are the most appropriate vegetation cover and land preparation methods for landscape restoration in semi-arid loess hilly area. This conclusion was made based on the vegetation type and land preparation with the best water-holding capacity.
Soil moisture patterns in a northern coniferous forest
Thomas F. McLintock
1959-01-01
The trend of soil moisture during the growing season, the alternate wetting from rainfall and drying during clear weather, determines the amount of moisture available for tree growth and also fixes, in part, the environment for root growth. In much of the northern coniferous region both moisture content and root environment are in turn affected by the hummock-and-...
Examining diel patterns of soil and xylem moisture using electrical resistivity imaging
NASA Astrophysics Data System (ADS)
Mares, Rachel; Barnard, Holly R.; Mao, Deqiang; Revil, André; Singha, Kamini
2016-05-01
The feedbacks among forest transpiration, soil moisture, and subsurface flowpaths are poorly understood. We investigate how soil moisture is affected by daily transpiration using time-lapse electrical resistivity imaging (ERI) on a highly instrumented ponderosa pine and the surrounding soil throughout the growing season. By comparing sap flow measurements to the ERI data, we find that periods of high sap flow within the diel cycle are aligned with decreases in ground electrical conductivity and soil moisture due to drying of the soil during moisture uptake. As sap flow decreases during the night, the ground conductivity increases as the soil moisture is replenished. The mean and variance of the ground conductivity decreases into the summer dry season, indicating drier soil and smaller diel fluctuations in soil moisture as the summer progresses. Sap flow did not significantly decrease through the summer suggesting use of a water source deeper than 60 cm to maintain transpiration during times of shallow soil moisture depletion. ERI captured spatiotemporal variability of soil moisture on daily and seasonal timescales. ERI data on the tree showed a diel cycle of conductivity, interpreted as changes in water content due to transpiration, but changes in sap flow throughout the season could not be interpreted from ERI inversions alone due to daily temperature changes.
Investigating local controls on soil moisture temporal stability using an inverse modeling approach
NASA Astrophysics Data System (ADS)
Bogena, Heye; Qu, Wei; Huisman, Sander; Vereecken, Harry
2013-04-01
A better understanding of the temporal stability of soil moisture and its relation to local and nonlocal controls is a major challenge in modern hydrology. Both local controls, such as soil and vegetation properties, and non-local controls, such as topography and climate variability, affect soil moisture dynamics. Wireless sensor networks are becoming more readily available, which opens up opportunities to investigate spatial and temporal variability of soil moisture with unprecedented resolution. In this study, we employed the wireless sensor network SoilNet developed by the Forschungszentrum Jülich to investigate soil moisture variability of a grassland headwater catchment in Western Germany within the framework of the TERENO initiative. In particular, we investigated the effect of soil hydraulic parameters on the temporal stability of soil moisture. For this, the HYDRUS-1D code coupled with a global optimizer (DREAM) was used to inversely estimate Mualem-van Genuchten parameters from soil moisture observations at three depths under natural (transient) boundary conditions for 83 locations in the headwater catchment. On the basis of the optimized parameter sets, we then evaluated to which extent the variability in soil hydraulic conductivity, pore size distribution, air entry suction and soil depth between these 83 locations controlled the temporal stability of soil moisture, which was independently determined from the observed soil moisture data. It was found that the saturated hydraulic conductivity (Ks) was the most significant attribute to explain temporal stability of soil moisture as expressed by the mean relative difference (MRD).
Cornelius, Mary L; Osbrink, Weste L A
2010-06-01
This study examined the influence of soil type and moisture availability on termite foraging behavior. Physical properties of the soil affected both tunneling behavior and shelter tube construction. Termites tunneled through sand faster than top soil and clay. In containers with top soil and clay, termites built shelter tubes on the sides of the containers. In containers with sand, termites built shelter tubes directly into the air and covered the sides of the container with a layer of sand. The interaction of soil type and moisture availability affected termite movement, feeding, and survival. In assays with moist soils, termites were more likely to aggregate in top soil over potting soil and peat moss. However, termites were more likely to move into containers with dry peat moss and potting soil than containers with dry sand and clay. Termites were also significantly more likely to move into containers with dry potting soil than dry top soil. In the assay with dry soils, termite mortality was high even though termites were able to travel freely between moist sand and dry soil, possibly due to desiccation caused by contact with dry soil. Evaporation from potting soil and peat moss resulted in significant mortality, whereas termites were able to retain enough moisture in top soil, sand, and clay to survive for 25 d. The interaction of soil type and moisture availability influences the distribution of foraging termites in microhabitats.
NASA Astrophysics Data System (ADS)
Pandey, V.; Srivastava, P. K.
2018-04-01
Change in soil moisture regime is highly relevant for agricultural drought, which can be best analyzed in terms of Soil Moisture Deficit Index (SMDI). A macroscale hydrological model Variable Infiltration Capacity (VIC) was used to simulate the hydro-climatological fluxes including evapotranspiration, runoff, and soil moisture storage to reconstruct the severity and duration of agricultural drought over semi-arid region of India. The simulations in VIC were performed at 0.25° spatial resolution by using a set of meteorological forcing data, soil parameters and Land Use Land Cover (LULC) and vegetation parameters. For calibration and validation, soil parameters obtained from National Bureau of Soil Survey and Land Use Planning (NBSSLUP) and ESA's Climate Change Initiative soil moisture (CCI-SM) data respectively. The analysis of results demonstrates that most of the study regions (> 80 %) especially for central northern part are affected by drought condition. The year 2001, 2002, 2007, 2008 and 2009 was highly affected by agricultural drought. Due to high average and maximum temperature, we observed higher soil evaporation that reduces the surface soil moisture significantly as well as the high topographic variations; coarse soil texture and moderate to high wind speed enhanced the drying upper soil moisture layer that incorporate higher negative SMDI over the study area. These findings can also facilitate the archetype in terms of daily time step data, lengths of the simulation period, various hydro-climatological outputs and use of reasonable hydrological model.
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.
USDA-ARS?s Scientific Manuscript database
This study examined the influence of soil type and moisture availability on termite foraging behavior. Physical properties of the soil affected both tunneling behavior and mud tube construction. Termites tunneled through sand faster than top soil and clay. In containers with top soil and clay, termi...
NASA Astrophysics Data System (ADS)
Dong, J.; Steele-Dunne, S. C.; Ochsner, T. E.; Van De Giesen, N.
2015-12-01
Soil moisture, hydraulic and thermal properties are critical for understanding the soil surface energy balance and hydrological processes. Here, we will discuss the potential of using soil temperature observations from Distributed Temperature Sensing (DTS) to investigate the spatial variability of soil moisture and soil properties. With DTS soil temperature can be measured with high resolution (spatial <1m, and temporal < 1min) in cables up to kilometers in length. Soil temperature evolution is primarily controlled by the soil thermal properties, and the energy balance at the soil surface. Hence, soil moisture, which affects both soil thermal properties and the energy that participates the evaporation process, is strongly correlated to the soil temperatures. In addition, the dynamics of the soil moisture is determined by the soil hydraulic properties.Here we will demonstrate that soil moisture, hydraulic and thermal properties can be estimated by assimilating observed soil temperature at shallow depths using the Particle Batch Smoother (PBS). The PBS can be considered as an extension of the particle filter, which allows us to infer soil moisture and soil properties using the dynamics of soil temperature within a batch window. Both synthetic and real field data will be used to demonstrate the robustness of this approach. We will show that the proposed method is shown to be able to handle different sources of uncertainties, which may provide a new view of using DTS observations to estimate sub-meter resolution soil moisture and properties for remote sensing product validation.
Climate Change, Growth, and Poverty in Ethiopia
2013-06-01
agricultural effects of global warming, reflecting their disadvantaged geographic location Higher evaporation and reduced soil moisture can damage crops...Ringler (2007) 5 Temperature, radiation, rainfall, soil moisture , and carbon dioxide (CO2) concentration are important variables that can proxy...iii) rainfall can affect other proxies of climate change in the literature such as soil moisture 6 This is based on FAOstat database 7 According to
Short and Long-Term Soil Moisture Effects of Liana Removal in a Seasonally Moist Tropical Forest
Reid, Joseph Pignatello; Schnitzer, Stefan A.; Powers, Jennifer S.
2015-01-01
Lianas (woody vines) are particularly abundant in tropical forests, and their abundance is increasing in the neotropics. Lianas can compete intensely with trees for above- and belowground resources, including water. As tropical forests experience longer and more intense dry seasons, competition for water is likely to intensify. However, we lack an understanding of how liana abundance affects soil moisture and hence competition with trees for water in tropical forests. To address this critical knowledge gap, we conducted a large-scale liana removal experiment in a seasonal tropical moist forest in central Panama. We monitored shallow and deep soil moisture over the course of three years to assess the effects of lianas in eight 0.64 ha removal plots and eight control plots. Liana removal caused short-term effects in surface soils. Surface soils (10 cm depth) in removal plots dried more slowly during dry periods and accumulated water more slowly after rainfall events. These effects disappeared within four months of the removal treatment. In deeper soils (40 cm depth), liana removal resulted in a multi-year trend towards 5–25% higher soil moisture during the dry seasons with the largest significant effects occurring in the dry season of the third year following treatment. Liana removal did not affect surface soil temperature. Multiple and mutually occurring mechanisms may be responsible for the effects of liana removal on soil moisture, including competition with trees, and altered microclimate, and soil structure. These results indicate that lianas influence hydrologic processes, which may affect tree community dynamics and forest carbon cycling. PMID:26545205
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
2015-12-07
Wallen, B., K.M. Smits and S.E. Howington. Thermal conductivity of binary sand mixtures evaluated through the full range of saturation. Hydrology Days...and T.H. Illangasekare. 2011. Thermal conductivity of soils as affected by temperature, Proceedings from Hydrology Days. Colorado State University...is mixed with very fine soil). Although it is well known that the apparent thermal conductivity (λ) of partially wet soil is a function of water (θ
Remote sensing of soil moisture using airborne hyperspectral data
Finn, M.; Lewis, M.; Bosch, D.; Giraldo, Mario; Yamamoto, K.; Sullivan, D.; Kincaid, R.; Luna, R.; Allam, G.; Kvien, Craig; Williams, M.
2011-01-01
Landscape assessment of soil moisture is critical to understanding the hydrological cycle at the regional scale and in broad-scale studies of biophysical processes affected by global climate changes in temperature and precipitation. Traditional efforts to measure soil moisture have been principally restricted to in situ measurements, so remote sensing techniques are often employed. Hyperspectral sensors with finer spatial resolution and narrow band widths may offer an alternative to traditional multispectral analysis of soil moisture, particularly in landscapes with high spatial heterogeneity. This preliminary research evaluates the ability of remotely sensed hyperspectral data to quantify soil moisture for the Little River Experimental Watershed (LREW), Georgia. An airborne hyperspectral instrument with a short-wavelength infrared (SWIR) sensor was flown in 2005 and 2007 and the results were correlated to in situ soil moisture values. A significant statistical correlation (R2 value above 0.7 for both sampling dates) for the hyperspectral instrument data and the soil moisture probe data at 5.08 cm (2 inches) was determined. While models for the 20.32 cm (8 inches) and 30.48 cm (12 inches) depths were tested, they were not able to estimate soil moisture to the same degree.
Remote sensing of soil moisture using airborne hyperspectral data
Finn, Michael P.; Lewis, Mark (David); Bosch, David D.; Giraldo, Mario; Yamamoto, Kristina H.; Sullivan, Dana G.; Kincaid, Russell; Luna, Ronaldo; Allam, Gopala Krishna; Kvien, Craig; Williams, Michael S.
2011-01-01
Landscape assessment of soil moisture is critical to understanding the hydrological cycle at the regional scale and in broad-scale studies of biophysical processes affected by global climate changes in temperature and precipitation. Traditional efforts to measure soil moisture have been principally restricted to in situ measurements, so remote sensing techniques are often employed. Hyperspectral sensors with finer spatial resolution and narrow band widths may offer an alternative to traditional multispectral analysis of soil moisture, particularly in landscapes with high spatial heterogeneity. This preliminary research evaluates the ability of remotely sensed hyperspectral data to quantify soil moisture for the Little River Experimental Watershed (LREW), Georgia. An airborne hyperspectral instrument with a short-wavelength infrared (SWIR) sensor was flown in 2005 and 2007 and the results were correlated to in situ soil moisture values. A significant statistical correlation (R 2 value above 0.7 for both sampling dates) for the hyperspectral instrument data and the soil moisture probe data at 5.08 cm (2 inches) was determined. While models for the 20.32 cm (8 inches) and 30.48 cm (12 inches) depths were tested, they were not able to estimate soil moisture to the same degree.
Xue, Xian; Peng, Fei; You, Quangang; Xu, Manhou; Dong, Siyang
2015-09-01
Recent studies found that the largest uncertainties in the response of the terrestrial carbon cycle to climate change might come from changes in soil moisture under the elevation of temperature. Warming-induced change in soil moisture and its level of influence on terrestrial ecosystems are mostly determined by climate, soil, and vegetation type and their sensitivity to temperature and moisture. Here, we present the results from a warming experiment of an alpine ecosystem conducted in the permafrost region of the Qinghai-Tibet Plateau using infrared heaters. Our results show that 3 years of warming treatments significantly elevated soil temperature at 0-100 cm depth, decreased soil moisture at 10 cm depth, and increased soil moisture at 40-100 cm depth. In contrast to the findings of previous research, experimental warming did not significantly affect NH 4 (+)-N, NO 3 (-)-N, and heterotrophic respiration, but stimulated the growth of plants and significantly increased root biomass at 30-50 cm depth. This led to increased soil organic carbon, total nitrogen, and liable carbon at 30-50 cm depth, and increased autotrophic respiration of plants. Analysis shows that experimental warming influenced deeper root production via redistributed soil moisture, which favors the accumulation of belowground carbon, but did not significantly affected the decomposition of soil organic carbon. Our findings suggest that future climate change studies need to take greater consideration of changes in the hydrological cycle and the local ecosystem characteristics. The results of our study will aid in understanding the response of terrestrial ecosystems to climate change and provide the regional case for global ecosystem models.
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.
Let's Break It Down; a Study of Organic Decompostion in Clay Soil
NASA Astrophysics Data System (ADS)
Weiss, E.
2017-12-01
Things that can affect decomposition are the decomposers in the soil, temperature, and water or moisture. My secondary research also showed that PH and chemical composition of the soil affect the rate of decomposition. Cold or freezing temperatures can help preserve organic material in soil because it freezes the soil and moisture, making it too dense for the organic decomposers to break down the organic matter. Soil also can be preserved by drying out and being stored at 4º Celsius (or 39º Fahrenheit) for 28 days. However, soil can degrade slowly in these conditions because it is not frozen and can be oxidized.
NASA Astrophysics Data System (ADS)
Kamiri, Hellen; Kreye, Christine; Becker, Mathias
2013-04-01
Wetland soils play an important role as storage compartments for water, carbon and nutrients. These soils implies various conditions, depending on the water regimes that affect several important microbial and physical-chemical processes which in turn influence the transformation of organic and inorganic components of nitrogen, carbon, soil acidity and other nutrients. Particularly, soil carbon and nitrogen play an important role in determining the productivity of a soil whereas management practices could determine the rate and magnitude of nutrient turnover. A study was carried out in a floodplain wetland planted with rice in North-west Tanzania- East Africa to determine the effects of different management practices and soil water regimes on paddy soil organic carbon and nitrogen. Four management treatments were compared: (i) control (non weeded plots); (ii) weeded plots; (iii) N fertilized plots, and (iv) non-cropped (non weeded plots). Two soil moisture regimes included soil under field capacity (rainfed conditions) and continuous water logging compared side-by-side. Soil were sampled at the start and end of the rice cropping seasons from the two fields differentiated by moisture regimes during the wet season 2012. The soils differed in the total organic carbon and nitrogen between the treatments. Soil management including weeding and fertilization is seen to affect soil carbon and nitrogen regardless of the soil moisture conditions. Particularly, the padddy soils were higher in the total organic carbon under continuous water logged field. These findings are preliminary and a more complete understanding of the relationships between management and soil moisture on the temporal changes of soil properties is required before making informed decisions on future wetland soil carbon and nitrogen dynamics. Keywords: Management, nitrogen, paddy soil, total carbon, Tanzania,
CO2 efflux from soils with seasonal water repellency
NASA Astrophysics Data System (ADS)
Urbanek, Emilia; Doerr, Stefan H.
2017-10-01
Soil carbon dioxide (CO2) emissions are strongly dependent on pore water distribution, which in turn can be modified by reduced wettability. Many soils around the world are affected by soil water repellency (SWR), which reduces infiltration and results in diverse moisture distribution. SWR is temporally variable and soils can change from wettable to water-repellent and vice versa throughout the year. Effects of SWR on soil carbon (C) dynamics, and specifically on CO2 efflux, have only been studied in a few laboratory experiments and hence remain poorly understood. Existing studies suggest soil respiration is reduced with increasing severity of SWR, but the responses of soil CO2 efflux to varying water distribution created by SWR are not yet known.Here we report on the first field-based study that tests whether SWR indeed reduces soil CO2 efflux, based on in situ measurements carried out over three consecutive years at a grassland and pine forest sites under the humid temperate climate of the UK.Soil CO2 efflux was indeed very low on occasions when soil exhibited consistently high SWR and low soil moisture following long dry spells. Low CO2 efflux was also observed when SWR was absent, in spring and late autumn when soil temperatures were low, but also in summer when SWR was reduced by frequent rainfall events. The highest CO2 efflux occurred not when soil was wettable, but when SWR, and thus soil moisture, was spatially patchy, a pattern observed for the majority of the measurement period. Patchiness of SWR is likely to have created zones with two different characteristics related to CO2 production and transport. Zones with wettable soil or low persistence of SWR with higher proportion of water-filled pores are expected to provide water with high nutrient concentration resulting in higher microbial activity and CO2 production. Soil zones with high SWR persistence, on the other hand, are dominated by air-filled pores with low microbial activity, but facilitating O2 supply and CO2 exchange between the soil and the atmosphere.The effects of soil moisture and SWR on soil CO2 efflux are strongly co-correlated, but the results of this study support the notion that SWR indirectly affects soil CO2 efflux by affecting soil moisture distribution. The appearance of SWR is influenced by moisture and temperature, but once present, SWR influences subsequent infiltration patterns and resulting soil water distribution, which in turn affects respiration. This study demonstrates that SWR can have contrasting effects on CO2 efflux. It can reduce it in dry soil zones by preventing their re-wetting, but, at the field soil scale and when spatially variable, it can also enhance overall CO2 efflux. Spatial variability in SWR and associated soil moisture distribution therefore need to be considered when evaluating the effects of SWR on soil C dynamics under current and predicted future climatic conditions.
Fate of 14C-labeled dissolved organic matter in paddy and upland soils in responding to moisture.
Chen, Xiangbi; Wang, Aihua; Li, Yang; Hu, Lening; Zheng, Hua; He, Xunyang; Ge, Tida; Wu, Jinshui; Kuzyakov, Yakov; Su, Yirong
2014-08-01
Soil organic matter (SOM) content in paddy soils is higher than that in upland soils in tropical and subtropical China. The dissolved organic matter (DOM) concentration, however, is lower in paddy soils. We hypothesize that soil moisture strongly controls the fate of DOM, and thereby leads to differences between the two agricultural soils under contrasting management regimens. A 100-day incubation experiment was conducted to trace the fate and biodegradability of DOM in paddy and upland soils under three moisture levels: 45%, 75%, and 105% of the water holding capacity (WHC). (14)C labeled DOM, extracted from the (14)C labeled rice plant material, was incubated in paddy and upland soils, and the mineralization to (14)CO2 and incorporation into microbial biomass were analyzed. Labile and refractory components of the initial (14)C labeled DOM and their respective half-lives were calculated by a double exponential model. During incubation, the mineralization of the initial (14)C labeled DOM in the paddy soils was more affected by moisture than in the upland soils. The amount of (14)C incorporated into the microbial biomass (2.4-11.0% of the initial DOM-(14)C activity) was less affected by moisture in the paddy soils than in the upland soils. At any of the moisture levels, 1) the mineralization of DOM to (14)CO2 within 100 days was 1.2-2.1-fold higher in the paddy soils (41.9-60.0% of the initial DOM-(14)C activity) than in the upland soils (28.7-35.7%), 2) (14)C activity remaining in solution was significantly lower in the paddy soils than in the upland soils, and 3) (14)C activity remaining in the same agricultural soil solution was not significantly different among the three moisture levels after 20 days. Therefore, moisture strongly controls DOM fate, but moisture was not the key factor in determining the lower DOM in the paddy soils than in the upland soils. The UV absorbance of DOM at 280 nm indicates less aromaticity of DOM from the paddy soils than from the upland soils. At any of the moisture levels, much more labile DOM was found in paddy soils (34.3-49.2% of the initial (14)C labeled DOM) compared with that in upland soils (19.4-23.9%). This demonstrates that the lower DOM content in the paddy soil compared with that in the upland soil is probably determined by the less complex components and structure of the DOM. Copyright © 2014 Elsevier B.V. All rights reserved.
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.
Effect of soil moisture on the temperature sensitivity of Northern soils
NASA Astrophysics Data System (ADS)
Minions, C.; Natali, S.; Ludwig, S.; Risk, D.; Macintyre, C. M.
2017-12-01
Arctic and boreal ecosystems are vast reservoirs of carbon and are particularly sensitive to climate warming. Changes in the temperature and precipitation regimes of these regions could significantly alter soil respiration rates, impacting atmospheric concentrations and affecting climate change feedbacks. Many incubation studies have shown that both temperature and soil moisture are important environmental drivers of soil respiration; this relationship, however, has rarely been demonstrated with in situ data. Here we present the results of a study at six field sites in Alaska from 2016 to 2017. Low-power automated soil gas systems were used to measure soil surface CO2 flux from three forced diffusion chambers and soil profile concentrations from three soil depth chambers at hourly intervals at each site. HOBO Onset dataloggers were used to monitor soil moisture and temperature profiles. Temperature sensitivity (Q10) was determined at each site using inversion analysis applied over different time periods. With highly resolved data sets, we were able to observe the changes in soil respiration in response to changes in temperature and soil moisture. Through regression analysis we confirmed that temperature is the primary driver in soil respiration, but soil moisture becomes dominant beyond a certain threshold, suppressing CO2 flux in soils with high moisture content. This field study supports the conclusions made from previous soil incubation studies and provides valuable insights into the impact of both temperature and soil moisture changes on soil respiration.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Grossiord, Charlotte; Sevanto, Sanna Annika; Limousin, Jean -Marc
Tree transpiration depends on biotic and abiotic factors that might change in the future, including precipitation and soil moisture status. Although short-term sap flux responses to soil moisture and evaporative demand have been the subject of attention before, the relative sensitivity of sap flux to these two factors under long-term changes in soil moisture conditions has rarely been determined experimentally. We tested how long-term artificial change in soil moisture affects the sensitivity of tree-level sap flux to daily atmospheric vapor pressure deficit ( VPD) and soil moisture variations, and the generality of these effects across forest types and environments usingmore » four manipulative sites in mature forests. Exposure to relatively long-term (two to six years) soil moisture reduction decreases tree sap flux sensitivity to daily VPD and relative extractable water ( REW) variations, leading to lower sap flux even under high soil moisture and optimal VPD. Inversely, trees subjected to long-term irrigation showed a significant increase in their sensitivity to daily VPD and REW, but only at the most water-limited site. The ratio between the relative change in soil moisture manipulation and the relative change in sap flux sensitivity to VPD and REW variations was similar across sites suggesting common adjustment mechanisms to long-term soil moisture status across environments for evergreen tree species. Altogether, our results show that long-term changes in soil water availability, and subsequent adjustments to these novel conditions, could play a critical and increasingly important role in controlling forest water use in the future.« less
Grossiord, Charlotte; Sevanto, Sanna Annika; Limousin, Jean -Marc; ...
2017-12-14
Tree transpiration depends on biotic and abiotic factors that might change in the future, including precipitation and soil moisture status. Although short-term sap flux responses to soil moisture and evaporative demand have been the subject of attention before, the relative sensitivity of sap flux to these two factors under long-term changes in soil moisture conditions has rarely been determined experimentally. We tested how long-term artificial change in soil moisture affects the sensitivity of tree-level sap flux to daily atmospheric vapor pressure deficit ( VPD) and soil moisture variations, and the generality of these effects across forest types and environments usingmore » four manipulative sites in mature forests. Exposure to relatively long-term (two to six years) soil moisture reduction decreases tree sap flux sensitivity to daily VPD and relative extractable water ( REW) variations, leading to lower sap flux even under high soil moisture and optimal VPD. Inversely, trees subjected to long-term irrigation showed a significant increase in their sensitivity to daily VPD and REW, but only at the most water-limited site. The ratio between the relative change in soil moisture manipulation and the relative change in sap flux sensitivity to VPD and REW variations was similar across sites suggesting common adjustment mechanisms to long-term soil moisture status across environments for evergreen tree species. Altogether, our results show that long-term changes in soil water availability, and subsequent adjustments to these novel conditions, could play a critical and increasingly important role in controlling forest water use in the future.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Grossiord, Charlotte; Sevanto, Sanna; Limousin, Jean-Marc
Tree transpiration depends on biotic and abiotic factors that might change in the future, including precipitation and soil moisture status. Although short-term sap flux responses to soil moisture and evaporative demand have been the subject of attention before, the relative sensitivity of sap flux to these two factors under long-term changes in soil moisture conditions has rarely been determined experimentally. We tested how long-term artificial change in soil moisture affects the sensitivity of tree-level sap flux to daily atmospheric vapor pressure deficit (VPD) and soil moisture variations, and the generality of these effects across forest types and environments using fourmore » manipulative sites in mature forests. Exposure to relatively long-term (two to six years) soil moisture reduction decreases tree sap flux sensitivity to daily VPD and relative extractable water (REW) variations, leading to lower sap flux even under high soil moisture and optimal VPD. Inversely, trees subjected to long-term irrigation showed a significant increase in their sensitivity to daily VPD and REW, but only at the most water-limited site. The ratio between the relative change in soil moisture manipulation and the relative change in sap flux sensitivity to VPD and REW variations was similar across sites suggesting common adjustment mechanisms to long-term soil moisture status across environments for evergreen tree species. Overall, our results show that long-term changes in soil water availability, and subsequent adjustments to these novel conditions, could play a critical and increasingly important role in controlling forest water use in the future.« less
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.
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.
EVALUATION OF RADON EMANATION FROM SOIL WITH VARYING MOISTURE CONTENT IN A SOIL CHAMBER
The paper describes measurements to quantitatively identify the extent to which moisture affects radon emanation and diffusive transport components of a sandy soil radon concentration gradient obtained in the EPA test chamber. The chamber (2X2X4 m long) was constructed to study t...
[Response processes of Aralia elata photosynthesis and transpiration to light and soil moisture].
Chen, Jian; Zhang, Guang-Can; Zhang, Shu-Yong; Wang, Meng-Jun
2008-06-01
By using CIRAS-2 portable photosynthesis system, the light response processes of Aralia elata photosynthesis and transpiration under different soil moisture conditions were studied, aimed to understand the adaptability of A. elata to different light and soil moisture conditions. The results showed that the response processes of A. elata net photosynthetic rate (Pn), transpiration rate (Tr), and water use efficiency (WUE) to photon flux density (PFD) were different. With the increasing PFD in the range of 800-1800 micromol x m2(-2) x s(-1), Pn changed less, Tr decreased gradually, while WUE increased obviously. The light saturation point (LSP) and light compensation point (LCP) were about 800 and 30 micromol m(-2) x s(-1), respectively, and less affected by soil water content; while the apparent photosynthetic quantum yield (Phi) and dark respiratory rate (Rd) were more affected by the moisture content. The Pn and WUE had evident threshold responses to the variations of soil water content. When the soil relative water content (RWC) was in the range of 44%-79%, A. elata could have higher levels of Pn and WUE.
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.
Aspect-related Vegetation Differences Amplify Soil Moisture Variability in Semiarid Landscapes
NASA Astrophysics Data System (ADS)
Yetemen, O.; Srivastava, A.; Kumari, N.; Saco, P. M.
2017-12-01
Soil moisture variability (SMV) in semiarid landscapes is affected by vegetation, soil texture, climate, aspect, and topography. The heterogeneity in vegetation cover that results from the effects of microclimate, terrain attributes (slope gradient, aspect, drainage area etc.), soil properties, and spatial variability in precipitation have been reported to act as the dominant factors modulating SMV in semiarid ecosystems. However, the role of hillslope aspect in SMV, though reported in many field studies, has not received the same degree of attention probably due to the lack of extensive large datasets. Numerical simulations can then be used to elucidate the contribution of aspect-driven vegetation patterns to this variability. In this work, we perform a sensitivity analysis to study on variables driving SMV using the CHILD landscape evolution model equipped with a spatially-distributed solar-radiation component that couples vegetation dynamics and surface hydrology. To explore how aspect-driven vegetation heterogeneity contributes to the SMV, CHILD was run using a range of parameters selected to reflect different scenarios (from uniform to heterogeneous vegetation cover). Throughout the simulations, the spatial distribution of soil moisture and vegetation cover are computed to estimate the corresponding coefficients of variation. Under the uniform spatial precipitation forcing and uniform soil properties, the factors affecting the spatial distribution of solar insolation are found to play a key role in the SMV through the emergence of aspect-driven vegetation patterns. Hence, factors such as catchment gradient, aspect, and latitude, define water stress and vegetation growth, and in turn affect the available soil moisture content. Interestingly, changes in soil properties (porosity, root depth, and pore-size distribution) over the domain are not as effective as the other factors. These findings show that the factors associated to aspect-related vegetation differences amplify the soil moisture variability of semi-arid landscapes.
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.
NASA Astrophysics Data System (ADS)
Sanchez-Mejia, Z. M.; Papuga, S. A.
2012-12-01
Water limited ecosystems in arid and semiarid regions are characterized by sparse vegetation and a relatively large fraction of bare soil. Importantly, the land surface in these dryland regions is highly sensitive to pulses of moisture that affect the vegetation canopy in density and color, as well as the soil color. Changes in surface conditions due to these pulses have been shown to affect the surface energy fluxes and atmospheric processes in these regions. For instance, previous studies have shown that shallow soil moisture ( < 20 cm below the surface) significantly changes surface albedo (a= SWup/ SWin). Recent studies have highlighted the importance of deep soil moisture ( > 20 cm below the surface) for vegetation dynamics in these regions. We hypothesize that deep soil moisture will change vegetation canopy density and color enough that changes in albedo will be observable at the surface, therefore linking deep soil moisture and albedo. We adopt a conceptual framework to address this hypothesis, where at any point in time the soil profile falls into one of four cases: (1) dry shallow soil and dry deep soil; (2) wet shallow soil and dry deep soil; (3) wet shallow soil and wet deep soil; and (4) dry shallow soil and wet deep soil. At a creosotebush dominated ecosystem of the Santa Rita Experimental Range, southern Arizona during summers of 2011 and 2012, we took albedo measurements during these cases at multiple bare and vegetated patches within the footprint of an eddy covariance tower. We found that when the soil is completely dry (Case 1) albedo is highest in both bare and vegetated patches. Likewise, when the soil is wet in both the shallow and deep regions (Case 3), albedo is lowest in both bare and vegetated patches. Interestingly, we also found that albedo is significantly lower for vegetated patches when the deep soil is wet and shallow soil is dry (Case 4). These results imply that deep soil moisture can be important in altering ecosystem level albedo. We note that ecosystems with higher percent vegetative cover are likely to be more sensitive to deep soil moisture driven changes in albedo. To quantify the influence of percent cover on ecosystem albedo, we populate a 100 x 100 cell grid randomly with bare and vegetated cells. For each case, we assign an albedo value to each cell based on probability distribution functions (PDFs) of soil moisture and albedo created from our field campaign data. Using this technique we can identify for each soil moisture case at which point the percent vegetative cover will significantly influence ecosystem albedo. Quantitative analyses of these ecosystem interactions help identify the unique role of deep soil moisture in land surface - atmosphere interactions.
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.
Soil moisture and biogeochemical factors influence the distribution of annual Bromus species
Belnap, Jayne; Stark, John Thomas; Rau, Benjamin; Allen, Edith B.; Phillips, Sue
2016-01-01
Abiotic factors have a strong influence on where annual Bromus species are found. At the large regional scale, temperature and precipitation extremes determine the boundaries of Bromusoccurrence. At the more local scale, soil characteristics and climate influence distribution, cover, and performance. In hot, dry, summer-rainfall-dominated deserts (Sonoran, Chihuahuan), little or noBromus is found, likely due to timing or amount of soil moisture relative to Bromus phenology. In hot, winter-rainfall-dominated deserts (parts of the Mojave Desert), Bromus rubens is widespread and correlated with high phosphorus availability. It also responds positively to additions of nitrogen alone or with phosphorus. On the Colorado Plateau, with higher soil moisture availability, factors limiting Bromus tectorum populations vary with life stage: phosphorus and water limit germination, potassium and the potassium/magnesium ratio affect winter performance, and water and potassium/magnesium affect spring performance. Controlling nutrients also change with elevation. In cooler deserts with winter precipitation (Great Basin, Columbia Plateau) and thus even greater soil moisture availability, B. tectorum populations are controlled by nitrogen, phosphorus, or potassium. Experimental nitrogen additions stimulate Bromus performance. The reason for different nutrients limiting in dissimilar climatic regions is not known, but it is likely that site conditions such as soil texture (as it affects water and nutrient availability), organic matter, and/or chemistry interact in a manner that regulates nutrient availability and limitations. Under future drier, hotter conditions,Bromus distribution is likely to change due to changes in the interaction between moisture and nutrient availability.
Barrier island community change: What controls it?
NASA Astrophysics Data System (ADS)
Dows, B.; Young, D.; Zinnert, J.
2014-12-01
Conversion from grassland to woody dominated communities has been observed globally. In recent decades, this pattern has been observed in coastal communities along the mid-Atlantic U.S. In coastal environments, a suite of biotic and abiotic factors interact as filters to determine plant community structure and distribution. Microclimatic conditions: soil and air temperature, soil moisture and salinity, and light attenuation under grass cover were measured across a grassland-woody encroachment gradient on a Virginia barrier island; to identify the primary factors that mediate this change. Woody establishment was associated with moderately dense (2200 shoots/m2) grass cover, but reduced at high (> 6200 shoots/ m2) and low (< 1250 shoots/ m2) densities. Moderately dense grass cover reduced light attenuation (82.50 % reduction) to sufficiently reduce soil temperature thereby limiting soil moisture evaporation. However, high grass density reduced light attenuation (98.7 % reduction) enough to inhibit establishment of woody species; whereas low grass density attenuated much less light (48.7 % reduction) which allowed for greater soil moisture evaporation. Soil salinity was dynamic as rainfall, tidal inundation, and sea spray produce spatiotemporal variation throughout the barrier island landscape. The importance of light and temperature were compounded as they also indirectly affect soil salinity via their affects on soil moisture. Determining how these biotic and abiotic factors relate to sea level rise and climate change will improve understanding coastal community response as global changes proceed. Understanding how community shifts affect ecosystem function and their potential to affect adjacent systems will also improve predictive ability of coastal ecosystem responses.
Zheng, S; Wang, C; Shen, Z; Quan, Y; Liu, X
2015-01-01
This study presents an efficient heavy metal (HM) control method in HM-contaminated wetlands with varied soil moisture levels through the introduction of extrinsic arbuscular mycorrhizal fungi (AMF) into natural wetland soil containing indigenous AMF species. A pot culture experiment was designed to determine the effect of two soil water contents (5-8% and 25-30%), five extrinsic AMF inoculants (Glomus mosseae, G. clarum, G. claroideum, G. etunicatum, and G. intraradices), and HM contamination on root colonization, plant growth, and element uptake of common reed (Phragmites australis (Cav.) Trin. ex Steudel) plantlets in wetland soils. This study showed the prevalence of mycorrhizae in the roots of all P. australis plantlets, regardless of extrinsic AMF inoculations, varied soil moisture or HM levels. It seems that different extrinsic AMF inoculations effectively lowered HM concentrations in the aboveground tissues of P. australis at two soil moisture levels. However, metal species, metal concentrations, and soil moisture should also be very important factors influencing the elemental uptake performance of plants in wetland ecosystems. Besides, the soil moisture level significantly influenced plant growth (including height, and shoot and root dry weight (DW)), and extrinsic AMF inoculations differently affected shoot DW.
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.
Remote Sensing Soil Moisture Analysis by Unmanned Aerial Vehicles Digital Imaging
NASA Astrophysics Data System (ADS)
Yeh, C. Y.; Lin, H. R.; Chen, Y. L.; Huang, S. Y.; Wen, J. C.
2017-12-01
In recent years, remote sensing analysis has been able to apply to the research of climate change, environment monitoring, geology, hydro-meteorological, and so on. However, the traditional methods for analyzing wide ranges of surface soil moisture of spatial distribution surveys may require plenty resources besides the high cost. In the past, remote sensing analysis performed soil moisture estimates through shortwave, thermal infrared ray, or infrared satellite, which requires lots of resources, labor, and money. Therefore, the digital image color was used to establish the multiple linear regression model. Finally, we can find out the relationship between surface soil color and soil moisture. In this study, we use the Unmanned Aerial Vehicle (UAV) to take an aerial photo of the fallow farmland. Simultaneously, we take the surface soil sample from 0-5 cm of the surface. The soil will be baking by 110° C and 24 hr. And the software ImageJ 1.48 is applied for the analysis of the digital images and the hue analysis into Red, Green, and Blue (R, G, B) hue values. The correlation analysis is the result from the data obtained from the image hue and the surface soil moisture at each sampling point. After image and soil moisture analysis, we use the R, G, B and soil moisture to establish the multiple regression to estimate the spatial distributions of surface soil moisture. In the result, we compare the real soil moisture and the estimated soil moisture. The coefficient of determination (R2) can achieve 0.5-0.7. The uncertainties in the field test, such as the sun illumination, the sun exposure angle, even the shadow, will affect the result; therefore, R2 can achieve 0.5-0.7 reflects good effect for the in-suit test by using the digital image to estimate the soil moisture. Based on the outcomes of the research, using digital images from UAV to estimate the surface soil moisture is acceptable. However, further investigations need to be collected more than ten days (four times a day) data to verify the relation between the image hue and the soil moisture for reliable moisture estimated model. And it is better to use the digital single lens reflex camera to prevent the deformation of the image and to have a better auto exposure. Keywords: soil, moisture, remote sensing
Evolving soils and hydrologic connectivity in semiarid hillslopes
NASA Astrophysics Data System (ADS)
Saco, Patricia M.
2015-04-01
Soil moisture availability is essential for the stability and resilience of semiarid ecosystems. In these ecosystems the amount of soil moisture available for vegetation growth and survival is intrinsically related to the way water is redistributed, that is from source to sink areas, and therefore prescribed by the hydrologic connectivity of the landscape. Recent studies have shown that hydrologic connectivity is highly dynamic and linked to the coevolution of geomorphic, soil and vegetation structures at a variety of spatial and temporal scales. This study investigates the effect of evolving soil depths on hydrologic connectivity using a modelling framework. The focus is on Australian semiarid hillslopes with patterned vegetation that result from coevolving landforms, soils, water redistribution, and vegetation patterns. We present and analyse results from simulations using a coupled landform evolution-dynamic vegetation model, which includes a soil depth evolution module and accounts for soil production and sediment erosion and deposition processes. We analyse the effect of soils depths on surface connectivity for a range of biotic (plant functional type strategies) and abiotic (slope and erodibility) conditions. The analysis shows that different plant functional types, through their varying facilitation strategies, have a profound effect on soils depths and therefore affect hydrologic connectivity and soil moisture patterns. This interplay becomes particularly important for systems that coevolve to have very shallow soils. In this case soil depth becomes the key factor prescribing surface connectivity and available soil moisture for plants, which affect the recovery of the system after disturbance. Conditions for the existence of threshold behaviour for which small perturbations can trigger a sudden increase in hydrologic connectivity, reduced soil moisture availability and decrease in productivity leading to degraded states are investigated. Critical implications for effective restoration efforts are discussed.
Microwave Remote Sensing of Soil Moisture
NASA Technical Reports Server (NTRS)
Schmugge, T. J.
1985-01-01
Because of the large contrast between the dielectric constant of liquid water and that of dry soil at microwave wavelength, there is a strong dependence of the thermal emission and radar backscatter from the soil on its moisture content. This dependence provides a means for the remote sensing of the moisture content in a surface layer approximately 5 cm thick. The feasibility of these techniques is demonstrated from field, aircraft and spacecraft platforms. The soil texture, surface roughness, and vegetative cover affect the sensitivity of the microwave response to moisture variations with vegetation being the most important. It serves as an attenuating layer which can totally obscure the surface. Research indicates that it is possible to obtain five or more levels of moisture discrimination and that a mature corn crop is the limiting vegetation situation.
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.
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.
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.
Deepika, Sharma; Kothamasi, David
2015-01-01
Multiple species of arbuscular mycorrhizal fungi (AMF) can colonize roots of an individual plant species but factors which determine the selection of a particular AMF species in a plant root are largely unknown. The present work analysed the effects of drought, flooding and optimal soil moisture (15-20 %) on AMF community composition and structure in Sorghum vulgare roots, using PCR-RFLP. Rhizophagus irregularis (isolate BEG 21), and rhizosphere soil (mixed inoculum) of Heteropogon contortus, a perennial C4 grass, collected from the semi-arid Delhi ridge, were used as AMF inocula. Soil moisture functioned as an abiotic filter and affected AMF community assembly inside plant roots by regulating AMF colonization and phylotype diversity. Roots of plants in flooded soils had lowest AMF diversity whilst root AMF diversity was highest under the soil moisture regime of 15-20 %. Although plant biomass was not affected, root P uptake was significantly influenced by soil moisture. Plants colonized with R. irregularis or mixed AMF inoculum showed higher root P uptake than non-mycorrhizal plants in drought and control treatments. No differences in root P levels were found in the flooded treatment between plants colonized with R. irregularis and non-mycorrhizal plants, whilst under the same treatment, root P uptake was lower in plants colonized with mixed AMF inoculum than in non-mycorrhizal plants.
Modeling the Impact of Soil Conditions on Global Water Balance
NASA Astrophysics Data System (ADS)
Wang, P. L.; Feddema, J. J.
2016-12-01
The amount of water the soil can hold for plant use, defined as soil water-holding capacity (WHC), has a large influence on the water cycle and climatic variables. Although soil properties vary widely worldwide, many climate modeling applications assume WHC to be spatially invariant. This study explores how a more realistic soil WHC estimate affects the global water balance relative to commonly assumed soil properties. We use a modified Thornthwaite water balance model combined with a newly developed soil WHC and soil thickness data at a 30 arc second resolution. The soil WHC data was obtained by integrating WHCs to a depth of 2 m and modified by the soil thickness data on a grid-by-grid basis, and then resampling to the 0.5 degree climatology data. We observed that down scaling soils data before modifying soil depths greatly increases global soil WHCs. This new dataset is compared to WHC information with a fixed 2-m soil depth, and a constant 150-mm soil WHC. Results indicate higher soil WHC results in increased soil moisture, decreased moisture surplus and deficits, and increased actual evapotranspiration (AE), and vice-versa. However, due to high variability in soil characteristics across climate gradients, this generalization does not hold true for regionally averaged outcomes. Compared to using a constant 150-mm WHC, more realistic soil WHC increases global averaged AE 1%, and decreases deficit 2% and surplus 3%. Most change is observed in areas with pronounced wet and dry seasons; using a constant 2-m soil depth doubles the differences. Regionally, Europe was most affected: AE increases 4%, and the deficit and surplus decrease 20% and 12%. Australia shows that regionally averaged results are not equivocal for moisture surplus and deficit; deficit decreases 0.4%, while surplus decreases 9%. This research highlights the importance of soil condition for climate modeling and how a better representation of soil moisture conditions affects global water balance modeling.
Quantifying soil moisture impacts on light use efficiency across biomes.
Stocker, Benjamin D; Zscheischler, Jakob; Keenan, Trevor F; Prentice, I Colin; Peñuelas, Josep; Seneviratne, Sonia I
2018-06-01
Terrestrial primary productivity and carbon cycle impacts of droughts are commonly quantified using vapour pressure deficit (VPD) data and remotely sensed greenness, without accounting for soil moisture. However, soil moisture limitation is known to strongly affect plant physiology. Here, we investigate light use efficiency, the ratio of gross primary productivity (GPP) to absorbed light. We derive its fractional reduction due to soil moisture (fLUE), separated from VPD and greenness changes, using artificial neural networks trained on eddy covariance data, multiple soil moisture datasets and remotely sensed greenness. This reveals substantial impacts of soil moisture alone that reduce GPP by up to 40% at sites located in sub-humid, semi-arid or arid regions. For sites in relatively moist climates, we find, paradoxically, a muted fLUE response to drying soil, but reduced fLUE under wet conditions. fLUE identifies substantial drought impacts that are not captured when relying solely on VPD and greenness changes and, when seasonally recurring, are missed by traditional, anomaly-based drought indices. Counter to common assumptions, fLUE reductions are largest in drought-deciduous vegetation, including grasslands. Our results highlight the necessity to account for soil moisture limitation in terrestrial primary productivity data products, especially for drought-related assessments. © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.
NASA Technical Reports Server (NTRS)
Girotto, Manuela
2018-01-01
Observations from recent soil moisture dedicated missions (e.g. SMOS or SMAP) have been used in innovative data assimilation studies to provide global high spatial (i.e., approximately10-40 km) and temporal resolution (i.e., daily) soil moisture profile estimates from microwave brightness temperature observations. These missions are only sensitive to near-surface soil moisture 0-5 cm). In contrast, the Gravity Recovery and Climate Experiment (GRACE) mission provides accurate measurements of the entire vertically integrated terrestrial water storage (TWS) column but, it is characterized by low spatial (i.e., 150,000 km2) and temporal (i.e., monthly) resolutions. Data assimilation studies have shown that GRACE-TWS primarily affects (in absolute terms) deeper moisture storages (i.e., groundwater). In this presentation I will review benefits and drawbacks associated to the assimilation of both types of observations. In particular, I will illustrate the benefits and drawbacks of their joint assimilation for the purpose of improving the entire profile of soil moisture (i.e., surface and deeper water storages).
Detection of moisture and moisture related phenomena from Skylab. [Texas
NASA Technical Reports Server (NTRS)
Eagleman, J. R.; Pogge, E. C.; Moore, R. K. (Principal Investigator); Hardy, N.; Lin, W.; League, L.
1973-01-01
The author has identified the following significant results. This is a preliminary report on the ability to detect soil moisture variation from the two different sensors on board Skylab. Initial investigations of S190A and Sl94 Skylab data and ground truth has indicated the following significant results. (1) There was a decrease in Sl94 antenna temperature from NW to SE across the Texas test site. (2) Soil moisture increases were measured from NW to SE across the test site. (3) There was a general increase in precipitation distribution and radar echoes from NW to SE across the site for the few days prior to measurements. This was consistent with the soil moisture measurements and gives more complete coverage of the site. (4) There are distinct variations in soil textures over the test site. This affects the moisture holding capacity of soils and must be considered. (5) Strong correlation coefficients were obtained between S194 antenna temperature and soil moisutre content. As the antenna temperature decreases soil moisture increases. (6) The Sl94 antenna temperature correlated best with soil mositure content in the upper two inches of the soil. A correlation coefficient of .988 was obtained. (7) Sl90A photographs in the red-infrared region were shown to be useful for identification of Abilene clay loam and for determining the distribution of this soil type.
NASA Astrophysics Data System (ADS)
Soulsby, C.; Dick, J.; Tetzlaff, D.; Bradford, J.
2016-12-01
The role of vegetation on the partitioning of precipitation, and the subsequent storage and release of water within the landscape is poorly understood. In particular, the relationship between vegetation and soil moisture is complex and reciprocal. The role of soil moisture as the primary source of water to plants may affect vegetation distribution. In turn, the structure of vegetation canopies may regulate water partitioning into interception, throughfall and steam flow. Such spatial differences in the inputs, together with complex patterns of water uptake from highly distributed root networks can create marked heterogeneity in soil moisture dynamics at small scales. Here, we present a study combining 3D and 2D ERT surveys with soil moisture measurements in a 3.2km upland catchment in the Scottish Highlands to understand influences of different vegetation types on spatio-temporal dynamics in soil moisture. The study focussed on one year of fortnightly ERT surveys to investigate plant-soil-water interactions within the root zone in podzolic soils. Locations were selected in both forest stands of 15m high Scots pine (Pinus sylvestris) and non-forest locations dominated by heather (Calluna vulgaris) shrubs (<0.5m high). These dominant species are typical of forest and non-forest vegetation communities in the Scottish Highlands. Results showed differences in the soil moisture dynamics under the different vegetation types, with heterogeneous patterns in the forested site mainly correlated with canopy cover and mirroring interception losses, with pronounced wetting cycles of the soil surrounding the bole of trees as a consequence of stem flow. Temporal variability in the forested site was greater, probably due to the interception, and increased evapotranspiration losses relative to the heather site, with drying typically being focussed on the areas around the trees, and reflecting the amount of water uptake. Moisture changes in the heather site were fairly heterogeneous are related to micro-topographic affects, lower interception ( 30% compared with 45%) and a smaller microclimatic effect of the canopy which serves to create greater fluctuations in soil moisture. Our results confirm the value in using geophysics to spatially elucidate subsurface plant-soil-water interactions.
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)
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.
Soil Nitrification and N2O Production: the connection with N concentration and Soil Water Content
NASA Astrophysics Data System (ADS)
Zhu-Barker, X.; Horwath, W. R.
2016-12-01
The development of mitigation strategies to reduce nitrous oxide (N2O) emission from soils is dependent on explicating the biophysical factors affecting different N2O production pathways. Ammonia oxidation and heterotrophic denitrification are the main pathways of N2O production, depending on soil conditions such as soil moisture content, oxygen (O2) content and N substrate. Many researchers have reported that N2O production increased as substrate concentration and soil moisture content increased. However, less understood is how N fertilizer concentration and moisture content interact to affect N2O production pathways. To investigate interaction and its effect on O2 consumption, we incubated three agricultural soils (clay, sandy loam, and peat) with different concentrations of (NH4)2SO4 (0-1000 µg N g-1) under 50 %, 75%, and 100% of water holding capacity. All treatments received 15N -KNO3 to bring the concentrations of NO3-_N in soils to 50 mg kg-1 soil and the NO3- pool to an enrichment of 10 atom% 15N. In all soils, the total amount of O2 consumption and N2O production increased as soil ammonical N concentration increased. The increased soil moisture significantly promoted N2O production in sandy loam and clay loam soils, compared to the peat soil. These results indicate that N2O production increased as substrate concentration increased likely due to the onset of O2 limitation caused by ammonia oxidation.
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.
Wang, Yi-Hao; Wang, Yan-Hui; Li, Zhen-Hua; Yu, Peng-Tao; Xiong, Wei; Hao, Jia; Duan, Jian
2012-10-01
From March 2009 to November 2011, an investigation was conducted on the spatiotemporal variation of soil moisture and its effects on the needle-fall in Masson pine (Pinus massoniana) forests in acid rain region of Chongqing, Southeast China, with the corresponding soil moisture thresholds determined. No matter the annual precipitation was abundant, normal or less than average, the seasonal variation of soil moisture in the forests could be obviously divided into four periods, i.e., sufficient (before May), descending (from June to July), drought (from August to September), and recovering (from October to November). With increasing soil depth, the soil moisture content increased after an initial decrease, but the difference of the soil moisture content among different soil layers decreased with decreasing annual precipitation. The amount of monthly needle-fall in the forests in growth season was significantly correlated with the water storage in root zone (0-60 cm soil layer), especially in the main root zone (20-50 cm soil layer). Soil field capacity (or capillary porosity) and 82% of field capacity (or 80% of capillary porosity) were the main soil moisture thresholds affecting the litter-fall. It was suggested that in acid rain region, Masson pine forest was easily to suffer from water deficit stress, especially in dry-summer period. The water deficit stress, together with already existed acid rain stress, would further threaten the health of the Masson forest.
NASA Astrophysics Data System (ADS)
Shafian, S.; Maas, S. J.
2015-12-01
Variations in soil moisture strongly affect surface energy balances, regional runoff, land erosion and vegetation productivity (i.e., potential crop yield). Hence, the estimation of soil moisture is very valuable in the social, economic, humanitarian (food security) and environmental segments of society. Extensive efforts to exploit the potential of remotely sensed observations to help quantify this complex variable are ongoing. This study aims at developing a new index, the Thermal Ground cover Moisture Index (TGMI), for estimating soil moisture content. This index is based on empirical parameterization of the relationship between raw image digital count (DC) data in the thermal infrared spectral band and ground cover (determined from raw image digital count data in the red and near-infrared spectral bands).The index uses satellite-derived information only, and the potential for its operational application is therefore great. This study was conducted in 18 commercial agricultural fields near Lubbock, TX (USA). Soil moisture was measured in these fields over two years and statistically compared to corresponding values of TGMI determined from Landsat image data. Results indicate statistically significant correlations between TGMI and field measurements of soil moisture (R2 = 0.73, RMSE = 0.05, MBE = 0.17 and AAE = 0.049), suggesting that soil moisture can be estimated using this index. It was further demonstrated that maps of TGMI developed from Landsat imagery could be constructed to show the relative spatial distribution of soil moisture across a region.
NASA Technical Reports Server (NTRS)
Van Den Hurk, Bart; Kim, Hyungjun; Krinner, Gerhard; Seneviratne, Sonia I.; Derksen, Chris; Oki, Taikan; Douville, Herve; Colin, Jeanne; Ducharne, Agnes; Cheruy, Frederique;
2016-01-01
The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow, and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth System Models (ESMs). The solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both strongly affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. However, models show divergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems).The experiments are subdivided in two components, the first addressing systematic land biases in offline mode (LMIP, building upon the 3rd phase of Global Soil Wetness Project; GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework (LFMIP, building upon the GLACE-CMIP blueprint).
Plant water use affects competition for nitrogen: why drought favors invasive species in California.
Everard, Katherine; Seabloom, Eric W; Harpole, W Stanley; de Mazancourt, Claire
2010-01-01
Abstract: Classic resource competition theory typically treats resource supply rates as independent; however, nutrient supplies can be affected by plants indirectly, with important consequences for model predictions. We demonstrate this general phenomenon by using a model in which competition for nitrogen is mediated by soil moisture, with competitive outcomes including coexistence and multiple stable states as well as competitive exclusion. In the model, soil moisture regulates nitrogen availability through soil moisture dependence of microbial processes, leaching, and plant uptake. By affecting water availability, plants also indirectly affect nitrogen availability and may therefore alter the competitive outcome. Exotic annual species from the Mediterranean have displaced much of the native perennial grasses in California. Nitrogen and water have been shown to be potentially limiting in this system. We parameterize the model for a Californian grassland and show that soil moisture-mediated competition for nitrogen can explain the annual species' dominance in drier areas, with coexistence expected in wetter regions. These results are concordant with larger biogeographic patterns of grassland invasion in the Pacific states of the United States, in which annual grasses have invaded most of the hot, dry grasslands in California but perennial grasses dominate the moister prairies of northern California, Oregon, and Washington.
Prescribed fire, soil inorganic nitrogen dynamics, and plant responses in a semiarid grassland
David J. Augustine; Paul Brewer; Dana M. Blumenthal; Justin D. Derner; Joseph C. von Fischer
2014-01-01
In arid and semiarid ecosystems, fire can potentially affect ecosystem dynamics through changes in soil moisture, temperature, and nitrogen cycling, as well as through direct effects on plant meristem mortality. We examined effects of annual and triennial prescribed fires conducted in early spring on soil moisture, temperature, and N, plant growth, and plant N content...
Impacts of soil moisture content on visual soil evaluation
NASA Astrophysics Data System (ADS)
Emmet-Booth, Jeremy; Forristal, Dermot; Fenton, Owen; Bondi, Giulia; Creamer, Rachel; Holden, Nick
2017-04-01
Visual Soil Examination and Evaluation (VSE) techniques offer tools for soil quality assessment. They involve the visual and tactile assessment of soil properties such as aggregate size and shape, porosity, redox morphology, soil colour and smell. An increasing body of research has demonstrated the reliability and utility of VSE techniques. However a number of limitations have been identified, including the potential impact of soil moisture variation during sampling. As part of a national survey of grassland soil quality in Ireland, an evaluation of the impact of soil moisture on two widely used VSE techniques was conducted. The techniques were Visual Evaluation of Soil Structure (VESS) (Guimarães et al., 2011) and Visual Soil Assessment (VSA) (Shepherd, 2009). Both generate summarising numeric scores that indicate soil structural quality, though employ different scoring mechanisms. The former requires the assessment of properties concurrently and the latter separately. Both methods were deployed on 20 sites across Ireland representing a range of soils. Additional samples were taken for soil volumetric water (θ) determination at 5-10 and 10-20 cm depth. No significant correlation was observed between θ 5-10 cm and either VSE technique. However, VESS scores were significantly related to θ 10-20 cm (rs = 0.40, sig = 0.02) while VSA scores were not (rs = -0.33, sig = 0.06). VESS and VSA scores can be grouped into quality classifications (good, moderate and poor). No significant mean difference was observed between θ 5-10 cm or θ 10-20 cm according to quality classification by either method. It was concluded that VESS scores may be affected by soil moisture variation while VSA appear unaffected. The different scoring mechanisms, where the separate assessment and scoring of individual properties employed by VSA, may limit soil moisture effects. However, moisture content appears not to affect overall structural quality classification by either method. References Guimarães, R.M.C., Ball, B.C. & Tormena, C.A. 2011. Improvements in the visual evaluation of soil structure, Soil Use and Management, 27, 3: 395-403 Shepherd, G.T. 2009. Visual Soil Assessment. Field guide for pastoral grazing and cropping on flat to rolling country. 2nd edn. Horizons regional council, New Zealand.
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.
USDA-ARS?s Scientific Manuscript database
An increase in abnormal climate change patterns and unsustainable irrigation in uplands cause drought and affect agricultural water security, crop productivity, and price fluctuations. In this study, we developed a soil moisture model to project irrigation requirements (IR) for upland crops under cl...
Prescribed fire, soil nitrogen dynamics, and plant responses in a semiarid grassland
USDA-ARS?s Scientific Manuscript database
Fire is a key driver of the structure and function of grassland ecosystems. In arid and semiarid ecosystems, where moisture limits plant production more than light, fire can potentially affect ecosystem dynamics through changes in soil moisture, temperature, and nitrogen cycling, as well as through ...
W.H. McNab
1991-01-01
Soil moisture content was intensively sampled in three, 1-acre blocks containing an opening and surrounding mature upland hardwoods. Openings covering 0.19-0.26 ac were created by group-selection cutting, and they were occupied by 1-year-old trees and shrubs.
NASA Astrophysics Data System (ADS)
Yatheendradas, S.; Vivoni, E.
2007-12-01
A common practice in distributed hydrological modeling is to assign soil hydraulic properties based on coarse textural datasets. For semiarid regions with poor soil information, the performance of a model can be severely constrained due to the high model sensitivity to near-surface soil characteristics. Neglecting the uncertainty in soil hydraulic properties, their spatial variation and their naturally-occurring horizonation can potentially affect the modeled hydrological response. In this study, we investigate such effects using the TIN-based Real-time Integrated Basin Simulator (tRIBS) applied to the mid-sized (100 km2) Sierra Los Locos watershed in northern Sonora, Mexico. The Sierra Los Locos basin is characterized by complex mountainous terrain leading to topographic organization of soil characteristics and ecosystem distributions. We focus on simulations during the 2004 North American Monsoon Experiment (NAME) when intensive soil moisture measurements and aircraft- based soil moisture retrievals are available in the basin. Our experiments focus on soil moisture comparisons at the point, topographic transect and basin scales using a range of different soil characterizations. We compare the distributed soil moisture estimates obtained using (1) a deterministic simulation based on soil texture from coarse soil maps, (2) a set of ensemble simulations that capture soil parameter uncertainty and their spatial distribution, and (3) a set of simulations that conditions the ensemble on recent soil profile measurements. Uncertainties considered in near-surface soil characterization provide insights into their influence on the modeled uncertainty, into the value of soil profile observations, and into effective use of on-going field observations for constraining the soil moisture response uncertainty.
GLACE: The Global Land-Atmosphere Coupling Experiment Part 2: Analysis
NASA Technical Reports Server (NTRS)
Guo, Zhichang; Dirmeyer, Paul A.; Koster, Randal D.; Bonan, Gordon; Chan, Edmond; Cox, Peter; Gordon, C. T.; Kanae, Shinjiro; Kowalczyk, Eva; Lawrence, David
2005-01-01
The twelve weather and climate models participating in the Global Land-Atmosphere Coupling Experiment (GLACE) show both a wide variation in the strength of land-atmosphere coupling and some intriguing commonalities. In this paper, we address the causes of variations in coupling strength - both the geographic variations within a given model and the model-to-model differences. The ability of soil moisture to affect precipitation is examined in two stages, namely, the ability of the soil moisture to affect evaporation, and the ability of evaporation to affect precipitation. Most of the differences between the models and within a given model are found to be associated with the first stage - an evaporation rate that varies strongly and consistently with soil moisture tends to lead to a higher coupling strength. The first stage differences reflect identifiable differences in model parameterization and model climate. Intermodel differences in the evaporation-precipitation connection, however, also play a key role.
NASA Astrophysics Data System (ADS)
Fischer, Christine; Hohenbrink, Tobias; Leimer, Sophia; Roscher, Christiane; Ravenek, Janneke; de Kroon, Hans; Kreutziger, Yvonne; Wirth, Christian; Eisenhauer, Nico; Gleixner, Gerd; Weigelt, Alexandra; Mommer, Liesje; Beßler, Holger; Schröder, Boris; Hildebrandt, Anke
2015-04-01
Soil moisture is the dynamic link between climate, soil and vegetation and the dynamics and variation are affected by several often interrelated factors such as soil texture, soil structural parameters (soil organic carbon) and vegetation parameters (belowground- and aboveground biomass). For the characterization and estimation of soil moisture and its variability and the resulting water fluxes and solute transports, the knowledge of the relative importance of these factors is of major challenge for hydrology and bioclimatology. Because of the heterogeneity of these factors, soil moisture varies strongly over time and space. Our objective was to assess the spatio-temporal variability of soil moisture and factors which could explain that variability, like soil properties and vegetation cover, in in a long term biodiversity experiment (Jena Experiment). The Jena Experiment consist 86 plots on which plant species richness (0, 1, 2, 4, 8, 16, and 60) and functional groups (legumes, grasses, tall herbs, and small herbs) were manipulated in a factorial design Soil moisture measurements were performed weekly April to September 2003-2005 and 2008-2013 using Delta T theta probe. Measurements were integrated to three depth intervals: 0.0 - 0.20, 0.20 - 0.40 and 0.40 - 0.70 m. We analyze the spatio-temporal patterns of soil water content on (i) the normalized time series and (ii) the first components obtained from a principal component analysis (PCA). Both were correlated with the design variables of the Jena Experiment (plant species richness and plant functional groups) and other influencing factors such as soil texture, soil structural variables and vegetation parameters. For the time stability of soil water content, the analysis showed that plots containing grasses was consistently drier than average at the soil surface in all observed years while plots containing legumes comparatively moister, but only up to the year 2008. In 0.40 - 0.70 m soil deep plots presence of small herbs led to higher than average soil moisture in some years (2008, 2012, 2013). Interestingly, plant species richness led to moister than average subsoil at the beginning of the experiment (2003 and 2004), which changed to lower than average up to the year 2010 in all depths. There was no effect of species diversity in the years since 2010, although species diversity generally increases leaf area index and aboveground biomass. The first component from the PCA analysis described the mean behavior in time of all soil moisture time series. The second component reflected the impact of soil depth. The first two components explained 76% of the data set total variance. The third component is linked to plant species richness and explained about 4 % of the total variance of soil moisture data. The fourth component, which explained 2.4 %, showed a high correlation to soil texture. Within this study we investigate the dominant factors controlling spatio-temporal patterns of soil moisture at several soil depths. Although climate and soil depths were the most important drivers, other factors like plant species richness and soil texture affected the temporal variation while certain plant functional groups were important for the spatial variability.
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.
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.
Evaluation of a cosmic-ray neutron sensor network for improved land surface model prediction
NASA Astrophysics Data System (ADS)
Baatz, Roland; Hendricks Franssen, Harrie-Jan; Han, Xujun; Hoar, Tim; Reemt Bogena, Heye; Vereecken, Harry
2017-05-01
In situ soil moisture sensors provide highly accurate but very local soil moisture measurements, while remotely sensed soil moisture is strongly affected by vegetation and surface roughness. In contrast, cosmic-ray neutron sensors (CRNSs) allow highly accurate soil moisture estimation on the field scale which could be valuable to improve land surface model predictions. In this study, the potential of a network of CRNSs installed in the 2354 km2 Rur catchment (Germany) for estimating soil hydraulic parameters and improving soil moisture states was tested. Data measured by the CRNSs were assimilated with the local ensemble transform Kalman filter in the Community Land Model version 4.5. Data of four, eight and nine CRNSs were assimilated for the years 2011 and 2012 (with and without soil hydraulic parameter estimation), followed by a verification year 2013 without data assimilation. This was done using (i) a regional high-resolution soil map, (ii) the FAO soil map and (iii) an erroneous, biased soil map as input information for the simulations. For the regional soil map, soil moisture characterization was only improved in the assimilation period but not in the verification period. For the FAO soil map and the biased soil map, soil moisture predictions improved strongly to a root mean square error of 0.03 cm3 cm-3 for the assimilation period and 0.05 cm3 cm-3 for the evaluation period. Improvements were limited by the measurement error of CRNSs (0.03 cm3 cm-3). The positive results obtained with data assimilation of nine CRNSs were confirmed by the jackknife experiments with four and eight CRNSs used for assimilation. The results demonstrate that assimilated data of a CRNS network can improve the characterization of soil moisture content on the catchment scale by updating spatially distributed soil hydraulic parameters of a land surface model.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yoon, Jin-Ho; Leung, Lai-Yung R.
This study assesses the relative influence of soil moisture memory and tropical sea surface temperature (SST) in seasonal rainfall over the contiguous United States. Using observed precipitation, the NINO3.4 index and soil moisture and evapotranspiration simulated by a land surface model for 61 years, analysis was performed using partial correlations to evaluate to what extent land surface and SST anomaly of El Niño and Southern Oscillation (ENSO) can affect seasonal precipitation over different regions and seasons. Results show that antecedent soil moisture is as important as concurrent ENSO condition in controlling rainfall anomalies over the U.S., but they generally dominatemore » in different seasons with SST providing more predictability during winter while soil moisture, through its linkages to evapotranspiration and snow water, has larger influence in spring and early summer. The proposed methodology is applicable to climate model outputs to evaluate the intensity of land-atmosphere coupling and its relative importance.« less
Verrot, Lucile; Destouni, Georgia
2015-01-01
Soil moisture influences and is influenced by water, climate, and ecosystem conditions, affecting associated ecosystem services in the landscape. This paper couples snow storage-melting dynamics with an analytical modeling approach to screening basin-scale, long-term soil moisture variability and change in a changing climate. This coupling enables assessment of both spatial differences and temporal changes across a wide range of hydro-climatic conditions. Model application is exemplified for two major Swedish hydrological basins, Norrström and Piteälven. These are located along a steep temperature gradient and have experienced different hydro-climatic changes over the time period of study, 1950-2009. Spatially, average intra-annual variability of soil moisture differs considerably between the basins due to their temperature-related differences in snow dynamics. With regard to temporal change, the long-term average state and intra-annual variability of soil moisture have not changed much, while inter-annual variability has changed considerably in response to hydro-climatic changes experienced so far in each basin.
How Has Human-induced Climate Change Affected California Drought Risk?
NASA Astrophysics Data System (ADS)
Cheng, L.; Hoerling, M. P.; Aghakouchak, A.; Livneh, B.; Quan, X. W.; Eischeid, J. K.
2015-12-01
The current California drought has cast a heavy burden on statewide agriculture and water resources, further exacerbated by concurrent extreme high temperatures. Furthermore, industrial-era global radiative forcing brings into question the role of long-term climate change on CA drought. How has human-induced climate change affected California drought risk? Here, observations and model experimentation are applied to characterize this drought employing metrics that synthesize drought duration, cumulative precipitation deficit, and soil moisture depletion. The model simulations show that increases in radiative forcing since the late 19th Century induces both increased annual precipitation and increased surface temperature over California, consistent with prior model studies and with observed long-term change. As a result, there is no material difference in the frequency of droughts defined using bivariate indicators of precipitation and near-surface (10-cm) soil moisture, because shallow soil moisture responds most sensitively to increased evaporation driven by warming, which compensates the increase in the precipitation. However, when using soil moisture within a deep root zone layer (1-m) as co-variate, droughts become less frequent because deep soil moisture responds most sensitively to increased precipitation. The results illustrate the different land surface responses to anthropogenic forcing that are relevant for near-surface moisture exchange and for root zone moisture availability. The latter is especially relevant for agricultural impacts as the deep layer dictates moisture availability for plants, trees, and many crops. The results thus indicate the net effect of climate change has made agricultural drought less likely, and that the current severe impacts of drought on California's agriculture has not been substantially caused by long-term climate changes.
NASA Astrophysics Data System (ADS)
Bogena, H. R.; Metzen, D.; Baatz, R.; Hendricks Franssen, H.; Huisman, J. A.; Montzka, C.; Vereecken, H.
2011-12-01
Measurements of low-energy secondary neutron intensity above the soil surface by cosmic-ray soil moisture probes (CRP) can be used to estimate soil moisture content. CRPs utilise the fact that high-energy neutrons initiated by cosmic rays are moderated (slowed to lower energies) most effectively by collisions with hydrogen atoms contained in water molecules in the soil. The conversion of neutron intensity to soil moisture content can potentially be complicated because neutrons are also moderated by aboveground water storage (e.g. vegetation water content, canopy storage of interception). Recently, it was demonstrated experimentally that soil moisture content derived from CRP measurements agrees well with average moisture content from gravimetric soil samples taken within the footprint of the cosmic ray probe, which is proposed to be up to several hundred meters in size [1]. However, the exact extension and shape of the CRP integration footprint is still an open question and it is also unclear how CRP measurements are affected by the soil moisture distribution within the footprint both in horizontal and vertical directions. In this paper, we will take advantage of an extensive wireless soil moisture sensor network covering most of the estimated footprint of the CRP. The network consists of 150 nodes and 900 soil moisture sensors which were installed in the small forested Wüstebach catchment (~27 ha) in the framework of the Transregio32 and the Helmholtz initiative TERENO (Terrestrial Environmental Observatories) [2]. This unique soil moisture data set provides a consistent picture of the hydrological status of the catchment in a high spatial and temporal resolution and thus the opportunity to evaluate the CRP measurements in a rigorous way. We will present first results of the comparison with a specific focus on the sensitivity of the CRP measurements to soil moisture variation in both the horizontal and vertical direction. Furthermore, the influence of forest biomass and shallow groundwater table fluctuations on the attenuation of cosmic-ray neutrons will be considered.
Daytime warming has stronger negative effects on soil nematodes than night-time warming.
Yan, Xiumin; Wang, Kehong; Song, Lihong; Wang, Xuefeng; Wu, Donghui
2017-03-07
Warming of the climate system is unequivocal, that is, stronger warming during night-time than during daytime. Here we focus on how soil nematodes respond to the current asymmetric warming. A field infrared heating experiment was performed in the western of the Songnen Plain, Northeast China. Three warming modes, i.e. daytime warming, night-time warming and diurnal warming, were taken to perform the asymmetric warming condition. Our results showed that the daytime and diurnal warming treatment significantly decreased soil nematodes density, and night-time warming treatment marginally affected the density. The response of bacterivorous nematode and fungivorous nematode to experimental warming showed the same trend with the total density. Redundancy analysis revealed an opposite effect of soil moisture and soil temperature, and the most important of soil moisture and temperature in night-time among the measured environment factors, affecting soil nematode community. Our findings suggested that daily minimum temperature and warming induced drying are most important factors affecting soil nematode community under the current global asymmetric warming.
Daytime warming has stronger negative effects on soil nematodes than night-time warming.
Yan, Xiumin; Wang, Kehong; Song, Lihong; Wang, Xuefeng; Wu, Donghui
2017-03-20
Warming of the climate system is unequivocal, that is, stronger warming during night-time than during daytime. Here we focus on how soil nematodes respond to the current asymmetric warming. A field infrared heating experiment was performed in the western of the Songnen Plain, Northeast China. Three warming modes, i.e. daytime warming, night-time warming and diurnal warming, were taken to perform the asymmetric warming condition. Our results showed that the daytime and diurnal warming treatment significantly decreased soil nematodes density, and night-time warming treatment marginally affected the density. The response of bacterivorous nematode and fungivorous nematode to experimental warming showed the same trend with the total density. Redundancy analysis revealed an opposite effect of soil moisture and soil temperature, and the most important of soil moisture and temperature in night-time among the measured environment factors, affecting soil nematode community. Our findings suggested that daily minimum temperature and warming induced drying are most important factors affecting soil nematode community under the current global asymmetric warming.
Daytime warming has stronger negative effects on soil nematodes than night-time warming
Yan, Xiumin; Wang, Kehong; Song, Lihong; Wang, Xuefeng; Wu, Donghui
2017-01-01
Warming of the climate system is unequivocal, that is, stronger warming during night-time than during daytime. Here we focus on how soil nematodes respond to the current asymmetric warming. A field infrared heating experiment was performed in the western of the Songnen Plain, Northeast China. Three warming modes, i.e. daytime warming, night-time warming and diurnal warming, were taken to perform the asymmetric warming condition. Our results showed that the daytime and diurnal warming treatment significantly decreased soil nematodes density, and night-time warming treatment marginally affected the density. The response of bacterivorous nematode and fungivorous nematode to experimental warming showed the same trend with the total density. Redundancy analysis revealed an opposite effect of soil moisture and soil temperature, and the most important of soil moisture and temperature in night-time among the measured environment factors, affecting soil nematode community. Our findings suggested that daily minimum temperature and warming induced drying are most important factors affecting soil nematode community under the current global asymmetric warming. PMID:28317914
Daytime warming has stronger negative effects on soil nematodes than night-time warming
NASA Astrophysics Data System (ADS)
Yan, Xiumin; Wang, Kehong; Song, Lihong; Wang, Xuefeng; Wu, Donghui
2017-03-01
Warming of the climate system is unequivocal, that is, stronger warming during night-time than during daytime. Here we focus on how soil nematodes respond to the current asymmetric warming. A field infrared heating experiment was performed in the western of the Songnen Plain, Northeast China. Three warming modes, i.e. daytime warming, night-time warming and diurnal warming, were taken to perform the asymmetric warming condition. Our results showed that the daytime and diurnal warming treatment significantly decreased soil nematodes density, and night-time warming treatment marginally affected the density. The response of bacterivorous nematode and fungivorous nematode to experimental warming showed the same trend with the total density. Redundancy analysis revealed an opposite effect of soil moisture and soil temperature, and the most important of soil moisture and temperature in night-time among the measured environment factors, affecting soil nematode community. Our findings suggested that daily minimum temperature and warming induced drying are most important factors affecting soil nematode community under the current global asymmetric warming.
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.
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.
The Influence of Soil Moisture and Wind on Rainfall Distribution and Intensity in Florida
NASA Technical Reports Server (NTRS)
Baker, R. David; Lynn, Barry H.; Boone, Aaron; Tao, Wei-Kuo
1998-01-01
Land surface processes play a key role in water and energy budgets of the hydrological cycle. For example, the distribution of soil moisture will affect sensible and latent heat fluxes, which in turn may dramatically influence the location and intensity of precipitation. However, mean wind conditions also strongly influence the distribution of precipitation. The relative importance of soil moisture and wind on rainfall location and intensity remains uncertain. Here, we examine the influence of soil moisture distribution and wind distribution on precipitation in the Florida peninsula using the 3-D Goddard Cumulus Ensemble (GCE) cloud model Coupled with the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) land surface model. This study utilizes data collected on 27 July 1991 in central Florida during the Convection and Precipitation Electrification Experiment (CaPE). The idealized numerical experiments consider a block of land (the Florida peninsula) bordered on the east and on the west by ocean. The initial soil moisture distribution is derived from an offline PLACE simulation, and the initial environmental wind profile is determined from the CaPE sounding network. Using the factor separation technique, the precise contribution of soil moisture and wind to rainfall distribution and intensity is determined.
Miller, Daniel N; Berry, Elaine D
2005-01-01
Beef cattle feedlots face serious environmental challenges associated with manure management, including greenhouse gas, odor, NH3, and dust emissions. Conditions affecting emissions are poorly characterized, but likely relate to the variability of feedlot surface moisture and manure contents, which affect microbial processes. Odor compounds, greenhouse gases, nitrogen losses, and dust potential were monitored at six moisture contents (0.11, 0.25, 0.43, 0.67, 1.00, and 1.50 g H2O g(-1) dry matter [DM]) in three artificial feedlot soil mixtures containing 50, 250, and 750 g manure kg(-1) total (manure + soil) DM over a two-week period. Moisture addition produced three microbial metabolisms: inactive, aerobic, and fermentative at low, moderate, and high moisture, respectively. Manure content acted to modulate the effect of moisture and enhanced some microbial processes. Greenhouse gas (CO2, N2O, and CH4) emissions were dynamic at moderate to high moisture. Malodorous volatile fatty acid (VFA) compounds did not accumulate in any treatments, but their persistence and volatility varied depending on pH and aerobic metabolism. Starch was the dominant substrate fueling both aerobic and fermentative metabolism. Nitrogen losses were observed in all metabolically active treatments; however, there was evidence for limited microbial nitrogen uptake. Finally, potential dust production was observed below defined moisture thresholds, which were related to manure content of the soil. Managing feedlot surface moisture within a narrow moisture range (0.2-0.4 g H2O g(-1) DM) and minimizing the accumulation of manure produced the optimum conditions that minimized the environmental impact from cattle feedlot production.
NASA Astrophysics Data System (ADS)
Zhang, Sibo; Roussel, Nicolas; Boniface, Karen; Ha, Minh Cuong; Frappart, Frédéric; Darrozes, José; Baup, Frédéric; Calvet, Jean-Christophe
2017-09-01
This work aims to estimate soil moisture and vegetation height from Global Navigation Satellite System (GNSS) Signal to Noise Ratio (SNR) data using direct and reflected signals by the land surface surrounding a ground-based antenna. Observations are collected from a rainfed wheat field in southwestern France. Surface soil moisture is retrieved based on SNR phases estimated by the Least Square Estimation method, assuming the relative antenna height is constant. It is found that vegetation growth breaks up the constant relative antenna height assumption. A vegetation-height retrieval algorithm is proposed using the SNR-dominant period (the peak period in the average power spectrum derived from a wavelet analysis of SNR). Soil moisture and vegetation height are retrieved at different time periods (before and after vegetation's significant growth in March). The retrievals are compared with two independent reference data sets: in situ observations of soil moisture and vegetation height, and numerical simulations of soil moisture, vegetation height and above-ground dry biomass from the ISBA (interactions between soil, biosphere and atmosphere) land surface model. Results show that changes in soil moisture mainly affect the multipath phase of the SNR data (assuming the relative antenna height is constant) with little change in the dominant period of the SNR data, whereas changes in vegetation height are more likely to modulate the SNR-dominant period. Surface volumetric soil moisture can be estimated (R2 = 0.74, RMSE = 0.009 m3 m-3) when the wheat is smaller than one wavelength (˜ 19 cm). The quality of the estimates markedly decreases when the vegetation height increases. This is because the reflected GNSS signal is less affected by the soil. When vegetation replaces soil as the dominant reflecting surface, a wavelet analysis provides an accurate estimation of the wheat crop height (R2 = 0.98, RMSE = 6.2 cm). The latter correlates with modeled above-ground dry biomass of the wheat from stem elongation to ripening. It is found that the vegetation height retrievals are sensitive to changes in plant height of at least one wavelength. A simple smoothing of the retrieved plant height allows an excellent matching to in situ observations, and to modeled above-ground dry biomass.
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.
Let's Break it Down: A Study of Organic Decomposition Rates in Clay Soil
NASA Astrophysics Data System (ADS)
Weiss, E.
2016-12-01
In this experiment I will be testing if temperature affects the organic decomposition rates in clay soil. I will need to be able to clean and weigh each filter paper without disrupting my data damaging or brushing off additional paper material. From there I need to be able to analyze and interpret my data to factor anything else that may affect the decomposition rates in the soil. Soil decomposers include bacteria and fungi. They obtain energy from plant and animal detritus through aerobic decomposition, which is similar to how humans break down sugar. The formula is: C6H12O6 + O2 → CO2 + H2O + energy. Besides oxygen and sugar the organisms need nutrients such as water and sustainable temperatures. Decomposition is important to us because it helps regulate soil structure, moisture, temperature, and provides nutrients to soil organisms. This matters on a global scale since decomposers release a large amount of carbon when breaking down matter, which contributes to greenhouse gasses such as carbon dioxide and methane. These greenhouse gasses affect the earth's climate. People who care about decomposition are farmers and those in agriculture, as well as environmental scientists. Even national parks might care because decomposition may affect park safety, how the park looks, and the amount of plants and wildlife. Things that can affect decomposition are the decomposers in the soil, temperature, and water or moisture. My secondary research also showed that PH and chemical composition of the soil affect the rate of decomposition.Cold or freezing temperatures can help preserve organic material in soil because it freezes the soil and moisture, making it too dense for the organic decomposers to break down the organic matter. Soil also can be preserved by drying out and being stored at 4º Celsius (or 39º Fahrenheit) for 28 days. However, soil can degrade slowly in these conditions because it is not frozen and can be oxidized.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Anderson, J.E.
1997-12-31
This paper describes application of a soil-plant cover system (SPCS) to preclude water from reaching interred wastes in arid and semiarid regions. Where potential evapotranspiration far exceeds precipitation, water can be kept from reaching buried wastes by (1) providing a sufficiently deep cap of soil to store precipitation that falls while plants are dormant and (2) maintaining plant cover to deplete soil moisture during the growing season, thereby emptying the storage reservoir. Research at the Idaho National Engineering Laboratory (INEL) has shown that 2 m of soil is adequate to store moisture from snowmelt and spring rains. Healthy stands ofmore » perennial grasses and shrubs adapted to the INEL climate use all available soil moisture, even during a very wet growing season. However, burrowing by small mammals or ants may affect the performance of a SPCS by increasing infiltration of water. Intrusion barriers of gravel and cobble can be used to restrict burrowing, but emplacement of such barriers affects soil moisture storage and plant rooting depths. A replicated field experiment to investigate the implications of those effects is in progress. Incorporation of an SPCS should be considered in the design of isolation barriers for shallow land burial of hazardous wastes in and regions.« less
Feng, Huihui
2016-09-07
Climate and vegetation change are two dominating factors for soil moisture trend. However, their individual contributions remain unknown due to their complex interaction. Here, I separated their contributions through a trajectory-based method across the global, regional and local scales. Our results demonstrated that climate change accounted for 98.78% and 114.64% of the global drying and wetting trend. Vegetation change exhibited a relatively weak influence (contributing 1.22% and -14.64% of the global drying and wetting) because it occurred in a limited area on land. Regionally, the impact of vegetation change cannot be neglected, which contributed -40.21% of the soil moisture change in the wetting zone. Locally, the contributions strongly correlated to the local environmental characteristics. Vegetation negatively affected soil moisture trends in the dry and sparsely vegetated regions and positively in the wet and densely vegetated regions. I conclude that individual contributions of climate and vegetation change vary at the global, regional and local scales. Climate change dominates the soil moisture trends, while vegetation change acts as a regulator to drying or wetting the soil under the changing climate.
NASA Astrophysics Data System (ADS)
Högström, Elin; Trofaier, Anna Maria; Gouttevin, Isabella; Bartsch, Annett
2015-04-01
Data from the Advanced Scatterometer (ASCAT) instrument provide the basis of a near real-time, coarse scale, global soil moisture product. Numerous studies have shown the applicability of this product, including recent operational use for numerical weather forecasts. Soil moisture is a key element in the global cycles of water, energy and carbon. Among many application areas, it is essential for the understanding of permafrost development in a future climate change scenario. Dramatic climate changes are expected in the Arctic, where ca 25% of the land is underlain by permafrost, and it is to a large extent remote and inaccessible. The availability and applicability of satellite derived land-surface data relevant for permafrost studies, such as surface soil moisture, is thus crucial to landscape-scale analyses of climate-induced change. However, there are challenges in the soil moisture retrieval that are specific to the Arctic. This study investigates backscatter variability unrelated to soil moisture variations in order to understand the possible impact on the soil moisture retrieval. The focus is on tundra lakes, which are a common feature in the Arctic and are expected to affect the retrieval. ENVISAT Advanced Synthetic Aperture Radar (ASAR) Wide Swath (120 m) data are used to resolve lakes and later understand and quantify their impacts on Metop ASCAT (25 km) soil moisture retrieval during the snow free period. Sites of interest are chosen according to high or low agreement between output from the land surface model ORCHIDEE and ASCAT derived SSM. The results show that in most cases low model agreement is related to high water fraction. The water fraction correlates with backscatter deviations (relative to a smooth water surface reference image) within the ASCAT footprint areas (R = 0.91-0.97). Backscatter deviations of up to 5 dB can occur in areas with less than 50% water fraction and an assumed soil moisture related range (sensitivity) of 7 dB in the ASCAT data. The study demonstrates that the usage of higher spatial resolution data than currently available for SSM is required in lowland permafrost environments. Furthermore, the results show that in the flat and open Arctic tundra areas, wind likely affects the soil moisture retrieval procedure rather than rain or remaining ice cover on the water surface. Therefore, the potential of a wind correction method is explored for sites where meteorological field data are available.
Soil Moisture and Snow Cover: Active or Passive Elements of Climate?
NASA Technical Reports Server (NTRS)
Oglesby, Robert J.; Marshall, Susan; Erickson, David J., III; Robertson, Franklin R.; Roads, John O.; Arnold, James E. (Technical Monitor)
2002-01-01
A key question in the study of the hydrologic cycle is the extent to which surface effects such as soil moisture and snow cover are simply passive elements or whether they can affect the evolution of climate on seasonal and longer time scales. We have constructed ensembles of predictability studies using the NCAR CCM3 in which we compared the relative roles of initial surface and atmospheric conditions over the central and western U.S. in determining the subsequent evolution of soil moisture and of snow cover. We have also made sensitivity studies with exaggerated soil moisture and snow cover anomalies in order to determine the physical processes that may be important. Results from simulations with realistic soil moisture anomalies indicate that internal climate variability may be the strongest factor, with some indication that the initial atmospheric state is also important. The initial state of soil moisture does not appear important, a result that held whether simulations were started in late winter or late spring. Model runs with exaggerated soil moisture reductions (near-desert conditions) showed a much larger effect, with warmer surface temperatures, reduced precipitation, and lower surface pressures; the latter indicating a response of the atmospheric circulation. These results suggest the possibility of a threshold effect in soil moisture, whereby an anomaly must be of a sufficient size before it can have a significant impact on the atmospheric circulation and hence climate. Results from simulations with realistic snow cover anomalies indicate that the time of year can be crucial. When introduced in late winter, these anomalies strongly affected the subsequent evolution of snow cover. When introduced in early winter, however, little or no effect is seen on the subsequent snow cover. Runs with greatly exaggerated initial snow cover indicate that the high reflectively of snow is the most important process by which snow cover cart impact climate, through lower surface temperatures and increased surface pressures. In early winter, the amount of solar radiation is very small and so this albedo effect is inconsequential while in late winter, with the sun higher in the sky and period of daylight longer, the effect is much stronger.
Jia, Jin Tian; Fu, Zhi Yong; Chen, Hong Song; Wang, Ke Lin; Zhou, Wei Jun
2016-06-01
Based on three manually excavated trenches (projection length of 21 m, width of 1 m) along a typical Karst hillslope, the changing trends for soil-bedrock structure, average water content of soil profile and soil-bedrock interface water content along each individual trench were studied. The effect of irregular bedrock topography on soil moisture distribution was discussed. The results showed that the surface topography was inconsistent with the bedrock topography in the Karst hill-slopes. The bedrock topography was highly irregular with a maximum variation coefficient of 82%. The distribution pattern of soil profile of moisture was significantly affected by the underlying undulant bedrock. The soil water content was related to slope position when the fluctuation was gentle, and displayed a linear increase from upslope to downslope. When the bedrock fluctuation increased, the downslope linear increasing trend for soil water content became unapparent, and the spatial continuity of soil moisture was weakened. The soil moisture was converged in rock dents and cracks. The average water content of soil profile was significantly positively correlated with the soil-bedrock interface water content, while the latter responded more sensitively to the bedrock fluctuation.
Waldrop, M.P.; Harden, J.W.
2008-01-01
Boreal forests contain significant quantities of soil carbon that may be oxidized to CO2 given future increases in climate warming and wildfire behavior. At the ecosystem scale, decomposition and heterotrophic respiration are strongly controlled by temperature and moisture, but we questioned whether changes in microbial biomass, activity, or community structure induced by fire might also affect these processes. We particularly wanted to understand whether postfire reductions in microbial biomass could affect rates of decomposition. Additionally, we compared the short-term effects of wildfire to the long-term effects of climate warming and permafrost decline. We compared soil microbial communities between control and recently burned soils that were located in areas with and without permafrost near Delta Junction, AK. In addition to soil physical variables, we quantified changes in microbial biomass, fungal biomass, fungal community composition, and C cycling processes (phenol oxidase enzyme activity, lignin decomposition, and microbial respiration). Five years following fire, organic surface horizons had lower microbial biomass, fungal biomass, and dissolved organic carbon (DOC) concentrations compared with control soils. Reductions in soil fungi were associated with reductions in phenol oxidase activity and lignin decomposition. Effects of wildfire on microbial biomass and activity in the mineral soil were minor. Microbial community composition was affected by wildfire, but the effect was greater in nonpermafrost soils. Although the presence of permafrost increased soil moisture contents, effects on microbial biomass and activity were limited to mineral soils that showed lower fungal biomass but higher activity compared with soils without permafrost. Fungal abundance and moisture were strong predictors of phenol oxidase enzyme activity in soil. Phenol oxidase enzyme activity, in turn, was linearly related to both 13C lignin decomposition and microbial respiration in incubation studies. Taken together, these results indicate that reductions in fungal biomass in postfire soils and lower soil moisture in nonpermafrost soils reduced the potential of soil heterotrophs to decompose soil carbon. Although in the field increased rates of microbial respiration can be observed in postfire soils due to warmer soil conditions, reductions in fungal biomass and activity may limit rates of decomposition. ?? 2008 The Authors Journal compilation ?? 2008 Blackwell Publishing.
Assessment of soil moisture dynamics on an irrigated maize field using cosmic ray neutron sensing
NASA Astrophysics Data System (ADS)
Scheiffele, Lena Maria; Baroni, Gabriele; Oswald, Sascha E.
2015-04-01
In recent years cosmic ray neutron sensing (CRS) developed as a valuable, indirect and non-invasive method to estimate soil moisture at a scale of tens of hectares, covering the gap between point scale measurements and large scale remote sensing techniques. The method is particularly promising in cropped and irrigated fields where invasive installation of belowground measurement devices could conflict with the agricultural management. However, CRS is affected by all hydrogen pools in the measurement footprint and a fast growing biomass provides some challenges for the interpretation of the signal and application of the method for detecting soil moisture. For this aim, in this study a cosmic ray probe was installed on a field near Braunschweig (Germany) during one maize growing season (2014). The field was irrigated in stripes of 50 m width using sprinkler devices for a total of seven events. Three soil sampling campaigns were conducted throughout the growing season to assess the effect of different hydrogen pools on calibration results. Additionally, leaf area index and biomass measurements were collected to provide the relative contribution of the biomass on the CRS signal. Calibration results obtained with the different soil sampling campaigns showed some discrepancy well correlated with the biomass growth. However, after the calibration function was adjusted to account also for lattice water and soil organic carbon, thus representing an equivalent water content of the soil, the differences decreased. Soil moisture estimated with CRS responded well to precipitation and irrigation events, confirming also the effective footprint of the method (i.e., radius 300 m) and showing occurring water stress for the crop. Thus, the dynamics are in agreement with the soil moisture determined with point scale measurements but they are less affected by the heterogeneous moisture conditions within the field. For this reason, by applying a detailed calibration, CRS proves to be a valuable method for the application on agricultural sites to assess and improve irrigation management.
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.
Soil organic carbon pools and stocks in permafrost-affected soils on the tibetan plateau.
Dörfer, Corina; Kühn, Peter; Baumann, Frank; He, Jin-Sheng; Scholten, Thomas
2013-01-01
The Tibetan Plateau reacts particularly sensitively to possible effects of climate change. Approximately two thirds of the total area is affected by permafrost. To get a better understanding of the role of permafrost on soil organic carbon pools and stocks, investigations were carried out including both discontinuous (site Huashixia, HUA) and continuous permafrost (site Wudaoliang, WUD). Three organic carbon fractions were isolated using density separation combined with ultrasonic dispersion: the light fractions (<1.6 g cm(-3)) of free particulate organic matter (FPOM) and occluded particulate organic matter (OPOM), plus a heavy fraction (>1.6 g cm(-3)) of mineral associated organic matter (MOM). The fractions were analyzed for C, N, and their portion of organic C. FPOM contained an average SOC content of 252 g kg(-1). Higher SOC contents (320 g kg(-1)) were found in OPOM while MOM had the lowest SOC contents (29 g kg(-1)). Due to their lower density the easily decomposable fractions FPOM and OPOM contribute 27% (HUA) and 22% (WUD) to the total SOC stocks. In HUA mean SOC stocks (0-30 cm depth) account for 10.4 kg m(-2), compared to 3.4 kg m(-2) in WUD. 53% of the SOC is stored in the upper 10 cm in WUD, in HUA only 39%. Highest POM values of 36% occurred in profiles with high soil moisture content. SOC stocks, soil moisture and active layer thickness correlated strongly in discontinuous permafrost while no correlation between SOC stocks and active layer thickness and only a weak relation between soil moisture and SOC stocks could be found in continuous permafrost. Consequently, permafrost-affected soils in discontinuous permafrost environments are susceptible to soil moisture changes due to alterations in quantity and seasonal distribution of precipitation, increasing temperature and therefore evaporation.
Bandow, Cornelia; Coors, Anja; Karau, Nora; Römbke, Jörg
2014-03-01
The authors investigated whether and how 2 environmental factors could influence the toxicity of a pyrethroid to 2 representatives of an important group of soil organisms. The impacts of different temperatures (20 °C and 26 °C) and soil moisture levels (30%, 50%, and 70% of water holding capacity) were investigated in combination with the insecticide λ-cyhalothrin on the reproduction success of Folsomia candida and Sinella curviseta in a full factorial design. Testing was based on the standard collembolan reproduction test (Organisation for Economic Co-operation and Development, guideline 232) following an effect concentration design. The results showed an effect of environmental and chemical factors on the number of juveniles of these animals. Particularly in dry soil, the reproduction of both species was reduced, while higher soil moisture levels influenced the number of juveniles positively compared with the middle soil moisture level. In general, however, higher soil moisture led to increased sensitivity to λ-cyhalothrin. In both organisms, temperature affected the toxicity of the pesticide but in different directions: high temperature led to higher toxicity in F. candida but to lower toxicity in S. curviseta. © 2013 SETAC.
NASA Technical Reports Server (NTRS)
Daughtry, C. S. T.; Bauer, M. E.; Crecelius, D. W.; Hixson, M. M. (Principal Investigator)
1980-01-01
The effects of available soil moisture, planting date, nitrogen fertilization, and cultivar on reflectance of spring wheat (Triticum aestivum L.) canopies were investigated. Spectral measurements were acquired on eight dates throughout the growing season, along with measurements of crop maturity stage, leaf area index, biomass, plant height, percent soil cover, and soil moisture. Planting date and available soil moisture were the primary agronomic factors which affected reflectance of spring wheat canopies from tillering to maturity. Comparisons of treatments indicated that during the seedling and tillering stages planting date was associated with 36 percent and 85 percent of variation in red and near infrared reflectances, respectively. As the wheat headed and matured, less of the variation in reflectance was associated with planting date and more with available soil moisture. By mid July, soil moisture accounted for 73 percent and 69 percent of the variation in reflectance in red and near infrared bands, respectively. Differences in spectral reflectance among treatments were attributed to changes in leaf area index, biomass, and percent soil cover. Cultivar and N fertilization rate were associated with very little of the variation in the reflectance of these canopies.
NASA Astrophysics Data System (ADS)
Azza, Gorrab; Zribi, Mehrez; Baghdadi, Nicolas; Mougenot, Bernard; Boulet, Gilles; Lili-Chabaane, Zohra
2015-04-01
Mapping surface soil moisture with meter-scale spatial resolution is appropriate for multi- domains particularly hydrology and agronomy. It allows water resources and irrigation management decisions, drought monitoring and validation of multi-hydrological water balance models. In the last years, various studies have demonstrated the large potential of radar remote sensing data, mainly from C frequency band, to retrieve soil moisture. However, the accuracy of the soil moisture estimation, by inversing backscattering radar coefficients (σ°), is affected by the influence of surface roughness and vegetation biomass contributions. In recent years, different empirical, semi empirical and physical approaches are developed for bare soil conditions, to estimate accurately spatial soil moisture variability. In this study, we propose an approach based on the change detection method for the retrieval of surface soil moisture at a higher spatial resolution. The proposal algorithm combines multi-temporal X-band SAR images (TerraSAR-X) with different continuous thetaprobe measurements. Seven thetaprobe stations are installed at different depths over the central semi arid region of Tunisia (9°23' - 10°17' E, 35° 1'-35°55' N). They cover approximately the entire of our study site and provide regional scale information. Ground data were collected over agricultural bare soil fields simultaneously to various TerraSAR-X data acquired during 2013-2014 and 2014-2015. More than fourteen test fields were selected for each spatial acquisition campaign, with variations in soil texture and in surface soil roughness. For each date, we considered the volumetric water content with thetaprobe instrument and gravimetric sampling; we measured also the roughness parameters with pin profilor. To retrieve soil moisture from X-band SAR data, we analyzed statistically the sensitivity between radar measurements and ground soil moisture derived from permanent thetaprobe stations. Our analyses are applied over bare soil class identified from an optical image SPOT / HRV acquired in the same period of the measurements. Results have shown linear relationship for the radar signals as a function of volumetric soil moisture with high sensitivity about 0.21 dB/vol%. For estimation of change in soil moisture, we considered two options: On the first one, we applied the change detection approach between successive radar images (∆σ°) assuming unchanged soil roughness effects. Our soil moisture retrieval algorithm was validated on the basis of comparisons between estimated and in situ soil moisture measurements over test fields. Using this option, results have shown an accuracy (RMSE) of about 4.8 %. Secondly, we corrected the sensitivity of the radar backscatter images to the surface roughness variability. Results have shown a reduction of the difference between the retrieved soil moisture and ground measurements with an RMSE about 3.7%.
Local Versus Remote Contributions of Soil Moisture to Near-Surface Temperature Variability
NASA Technical Reports Server (NTRS)
Koster, R.; Schubert, S.; Wang, H.; Chang, Y.
2018-01-01
Soil moisture variations have a straightforward impact on overlying air temperatures, wetter soils can induce higher evaporative cooling of the soil and thus, locally, cooler temperatures overall. Not known, however, is the degree to which soil moisture variations can affect remote air temperatures through their impact on the atmospheric circulation. In this talk we describe a two-pronged analysis that addresses this question. In the first segment, an extensive ensemble of NASA/GSFC GEOS-5 atmospheric model simulations is analyzed statistically to isolate and quantify the contributions of various soil moisture states, both local and remote, to the variability of air temperature at a given local site. In the second segment, the relevance of the derived statistical relationships is evaluated by applying them to observations-based data. Results from the second segment suggest that the GEOS-5-based relationships do, at least to first order, hold in nature and thus may provide some skill to forecasts of air temperature at subseasonal time scales, at least in certain regions.
Analysis the configuration of earthing system based on high-low and low-high soil structure
NASA Astrophysics Data System (ADS)
Ramani, A. N.; Ahmad, Abdul Rahman; Sulaima, M. F.; Nasir, M. N. M.; Ahmad, Arfah
2015-05-01
Each TNB transmission tower requires a tower footing resistance (TFR) with a lower grounding resistance value that depends on the transmission line voltage. For 132kV and 275kV tower, the TFR must less than 10Ω and 500kV tower must less than 5Ω. The TFR is changeable with variable factors such as soil resistivity. Low TFR provides essential protection to the fault such as lightning strike that may occur at any time. The fault current flow to the lowest resistance path and easily disperses to earth. Back flashover voltage across the insulator of transmission lines may occur when the TFR is high. The TFR is influenced by soil resistivity. There are three parameters affecting the soil resistivity; moisture content, salt content and temperature of the soil. High moisture content in soil will reduce the soil resistivity and resultant low TFR. Small scale moisture control by using Micro Reservoir (MR) irrigation with semi-permeable membranes have the power to offer the stable moisture in soil. By using osmosis concept, it is the process of net movement of water molecules from high potential water to lower potential water though a semi permeable membrane. The MR can withstand for 3 to 5 days without continuous water supply. The MR installed in the centre of the tower that contains a multiple parallel of electrode rods. The concentrated of electrode rods grounding configuration with a combination of MR will improve the TFR even at multilayer soil. As a result, MR gives a little improvement to TFR. The MR in area of concentrated electrode rod configuration to ensure the soil always wet and moist at all times. The changes in soil affect the tower-footing-resistance. The tower-footing-resistance measurement at afternoon is higher than at evening because of the temperature and moisture content in soil is change due to sun radiation.
Analysis the configuration of earthing system based on high-low and low-high soil structure
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ramani, A. N.; Ahmad, Abdul Rahman; Sulaima, M. F.
2015-05-15
Each TNB transmission tower requires a tower footing resistance (TFR) with a lower grounding resistance value that depends on the transmission line voltage. For 132kV and 275kV tower, the TFR must less than 10Ω and 500kV tower must less than 5Ω. The TFR is changeable with variable factors such as soil resistivity. Low TFR provides essential protection to the fault such as lightning strike that may occur at any time. The fault current flow to the lowest resistance path and easily disperses to earth. Back flashover voltage across the insulator of transmission lines may occur when the TFR is high.more » The TFR is influenced by soil resistivity. There are three parameters affecting the soil resistivity; moisture content, salt content and temperature of the soil. High moisture content in soil will reduce the soil resistivity and resultant low TFR. Small scale moisture control by using Micro Reservoir (MR) irrigation with semi-permeable membranes have the power to offer the stable moisture in soil. By using osmosis concept, it is the process of net movement of water molecules from high potential water to lower potential water though a semi permeable membrane. The MR can withstand for 3 to 5 days without continuous water supply. The MR installed in the centre of the tower that contains a multiple parallel of electrode rods. The concentrated of electrode rods grounding configuration with a combination of MR will improve the TFR even at multilayer soil. As a result, MR gives a little improvement to TFR. The MR in area of concentrated electrode rod configuration to ensure the soil always wet and moist at all times. The changes in soil affect the tower-footing-resistance. The tower-footing-resistance measurement at afternoon is higher than at evening because of the temperature and moisture content in soil is change due to sun radiation.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pattathil, Sivakumar; Ingwers, Miles W.; Victoriano, Olivia L.
The composition, integrity, and architecture of the macromolecular matrix of cell walls, collectively referred to as cell wall ultrastructure, exhibits variation across species and organs and among cell types within organs. Indirect approaches have suggested that modifications to cell wall ultrastructure occur in response to abiotic stress; however, modifications have not been directly observed. Glycome profiling was used to study cell wall ultrastructure by examining variation in composition and extractability of non-cellulosic glycans in cell walls of stem wood, roots, and needles of loblolly pine saplings exposed to high and low soil moisture. Soil moisture influenced physiological processes and themore » overall composition and extractability of cell wall components differed as a function of soil moisture treatments. The strongest response of cell wall ultrastructure to soil moisture was increased extractability of pectic backbone epitopes in the low soil moisture treatment. The higher abundance of these pectic backbone epitopes in the oxalate extract indicate that the loosening of cell wall pectic components could be associated with the release of pectic signals as a stress response. The increased extractability of pectic backbone epitopes in response to low soil moisture availability was more pronounced in stem wood than in roots or needles. Additional responses to low soil moisture availability were observed in lignin associated carbohydrates released in chlorite extracts of stem wood, including an increased abundance of pectic arabinogalactan epitopes. Overall, these results indicate that cell walls of loblolly pine organs undergo changes in their ultrastructural composition and extractability as a response to soil moisture availability and that cell walls of the stem wood are more responsive to low soil moisture availability compared to cell walls of roots and needles. In conclusion, to our knowledge, this is the first direct evidence, delineated by glycomic analyses, that abiotic stress affects cell wall ultrastructure. This study is also unique in that glycome profiling of pine needles has never before been reported.« less
Pattathil, Sivakumar; Ingwers, Miles W; Victoriano, Olivia L; Kandemkavil, Sindhu; McGuire, Mary Anne; Teskey, Robert O; Aubrey, Doug P
2016-01-01
The composition, integrity, and architecture of the macromolecular matrix of cell walls, collectively referred to as cell wall ultrastructure, exhibits variation across species and organs and among cell types within organs. Indirect approaches have suggested that modifications to cell wall ultrastructure occur in response to abiotic stress; however, modifications have not been directly observed. Glycome profiling was used to study cell wall ultrastructure by examining variation in composition and extractability of non-cellulosic glycans in cell walls of stem wood, roots, and needles of loblolly pine saplings exposed to high and low soil moisture. Soil moisture influenced physiological processes and the overall composition and extractability of cell wall components differed as a function of soil moisture treatments. The strongest response of cell wall ultrastructure to soil moisture was increased extractability of pectic backbone epitopes in the low soil moisture treatment. The higher abundance of these pectic backbone epitopes in the oxalate extract indicate that the loosening of cell wall pectic components could be associated with the release of pectic signals as a stress response. The increased extractability of pectic backbone epitopes in response to low soil moisture availability was more pronounced in stem wood than in roots or needles. Additional responses to low soil moisture availability were observed in lignin-associated carbohydrates released in chlorite extracts of stem wood, including an increased abundance of pectic arabinogalactan epitopes. Overall, these results indicate that cell walls of loblolly pine organs undergo changes in their ultrastructural composition and extractability as a response to soil moisture availability and that cell walls of the stem wood are more responsive to low soil moisture availability compared to cell walls of roots and needles. To our knowledge, this is the first direct evidence, delineated by glycomic analyses, that abiotic stress affects cell wall ultrastructure. This study is also unique in that glycome profiling of pine needles has never before been reported.
Pattathil, Sivakumar; Ingwers, Miles W.; Victoriano, Olivia L.; ...
2016-06-24
The composition, integrity, and architecture of the macromolecular matrix of cell walls, collectively referred to as cell wall ultrastructure, exhibits variation across species and organs and among cell types within organs. Indirect approaches have suggested that modifications to cell wall ultrastructure occur in response to abiotic stress; however, modifications have not been directly observed. Glycome profiling was used to study cell wall ultrastructure by examining variation in composition and extractability of non-cellulosic glycans in cell walls of stem wood, roots, and needles of loblolly pine saplings exposed to high and low soil moisture. Soil moisture influenced physiological processes and themore » overall composition and extractability of cell wall components differed as a function of soil moisture treatments. The strongest response of cell wall ultrastructure to soil moisture was increased extractability of pectic backbone epitopes in the low soil moisture treatment. The higher abundance of these pectic backbone epitopes in the oxalate extract indicate that the loosening of cell wall pectic components could be associated with the release of pectic signals as a stress response. The increased extractability of pectic backbone epitopes in response to low soil moisture availability was more pronounced in stem wood than in roots or needles. Additional responses to low soil moisture availability were observed in lignin associated carbohydrates released in chlorite extracts of stem wood, including an increased abundance of pectic arabinogalactan epitopes. Overall, these results indicate that cell walls of loblolly pine organs undergo changes in their ultrastructural composition and extractability as a response to soil moisture availability and that cell walls of the stem wood are more responsive to low soil moisture availability compared to cell walls of roots and needles. In conclusion, to our knowledge, this is the first direct evidence, delineated by glycomic analyses, that abiotic stress affects cell wall ultrastructure. This study is also unique in that glycome profiling of pine needles has never before been reported.« less
NASA Astrophysics Data System (ADS)
Harper, A.; Denning, A. S.; Baker, I.; Randall, D.; Dazlich, D.
2008-12-01
Several climate models have predicted an increase in long-term droughts in tropical South America due to increased greenhouse gases in the atmosphere. Although the Amazon rainforest is resilient to seasonal drought, multi-year droughts pose a definite problem for the ecosystem's health. Furthermore, drought- stressed vegetation participates in feedbacks with the atmosphere that can exacerbate drought. Namely, reduced evapotranspiration further dries out the atmosphere and affects the regional climate. Trees in the rainforest survive seasonal drought by using deep roots to access adequate stores of soil moisture. We investigate the climatic impacts of deep roots and soil moisture by coupling the Simple Biosphere (SiB3) model to Colorado State University's general circulation model (BUGS5). We compare two versions of SiB3 in the GCM during years with anomalously low rainfall. The first has strong vegetative stress due to soil moisture limitations. The second experiences less stress and has more realistic representations of surface biophysics. In the model, basin-wide reductions in soil moisture stress result in increased evapotranspiration, precipitation, and moisture recycling in the Amazon basin. In the savannah region of southeastern Brazil, the unstressed version of SiB3 produces decreased precipitation and weaker moisture flux, which is more in-line with observations. The improved simulation of precipitation and evaporation also produces a more realistic Bolivian high and Nordeste low. These changes highlight the importance of subsurface biophysics for the Amazonian climate. The presence of deep roots and soil moisture will become even more important if climate change brings more frequent droughts to this region in the future.
NASA Astrophysics Data System (ADS)
Zhao, W.; Zhang, X.; Liu, Y.; Fang, X.
2017-12-01
Currently, the ecological restoration of the Loess Plateau has led to significant achievements such as increases in vegetation coverage, decreases in soil erosion, and enhancement of ecosystem services. Soil moisture shortages, however, commonly occur as a result of limited rainfall and strong evaporation in this semiarid region of China. Since soil moisture is critical in regulating plant growth in these semiarid regions, it is crucial to identify the spatial variation and factors affecting soil moisture at multi-scales in the Loess Plateau of China. In the last several years, extensive studies on soil moisture have been carried out by our research group at the plot, small watershed, watershed, and regional scale in the Loess Plateau, providing some information for vegetation restoration in the region. The main research results are as follows: (1) the highest soil moisture content was in the 0-0.1 m layer with a large coefficient of variation; (2) in the 0-0.1m layer, soil moisture content was negatively correlated with relative elevation, slope and vegetation cover, the correlations among slope, aspect and soil moisture increased with depth increased; (3) as for the deep soil moisture content, the higher spatial variation of deep SMC occurred at 1.2-1.4 m and 4.8-5.0m; (4) the deep soil moisture content in native grassland and farmland were significant higher than that of introduced vegetation; (5) at regional scale, the soil water content under different precipitation zones increased following the increase of precipitation, while, the influencing factors of deep SMC at watershed scale varied with land management types; (6) in the areas with multi-year precipitation of 370 - 440mm, natural grass is more suitable for restoration, and this should be treated as the key areas in vegetation restoration; (7) appropriate planting density and species selection should be taken into account for introduced vegetation management; (8) it is imperative to take the local reality into account and to balance the economic and ecological benefits so that the ratio of artificial vegetation and natural restoration can be optimized to realize sustainability of vegetation restoration
Soil moisture profile variability in land-vegetation- atmosphere continuum
NASA Astrophysics Data System (ADS)
Wu, Wanru
Soil moisture is of critical importance to the physical processes governing energy and water exchanges at the land-air boundary. With respect to the exchange of water mass, soil moisture controls the response of the land surface to atmospheric forcing and determines the partitioning of precipitation into infiltration and runoff. Meanwhile, the soil acts as a reservoir for the storage of liquid water and slow release of water vapor into the atmosphere. The major motivation of the study is that the soil moisture profile is thought to make a substantial contribution to the climate variability through two-way interactions between the land-surface and the atmosphere in the coupled ocean-atmosphere-land climate system. The characteristics of soil moisture variability with soil depth may be important in affecting the atmosphere. The natural variability of soil moisture profile is demonstrated using observations. The 16-year field observational data of soil moisture with 11-layer (top 2.0 meters) measured soil depths over Illinois are analyzed and used to identify and quantify the soil moisture profile variability, where the atmospheric forcing (precipitation) anomaly propagates down through the land-branch of the hydrological cycle with amplitude damping, phase shift, and increasing persistence. Detailed statistical data analyses, which include application of the periodogram method, the wavelet method and the band-pass filter, are made of the variations of soil moisture profile and concurrently measured precipitation for comparison. Cross-spectral analysis is performed to obtain the coherence pattern and phase correlation of two time series for phase shift and amplitude damping calculation. A composite of the drought events during this time period is analyzed and compared with the normal (non-drought) case. A multi-layer land surface model is applied for modeling the soil moisture profile variability characteristics and investigating the underlying mechanisms. Numerical experiments are conducted to examine the impacts of some potential controlling factors, which include atmospheric forcing (periodic and pulse) at the upper boundary, the initial soil moisture profile, the relative root abundance and the soil texture, on the variability of soil moisture profile and the corresponding evapotranspiration. Similar statistical data analyses are performed for the experimental data. Observations from the First International Satellite Land Surface Climatological Project (ISLSCP) Field Experiment (FIFE) are analyzed and used for the testing of model. The integration of the observational and modeling approaches makes it possible to better understand the mechanisms by which the soil moisture profile variability is generated with phase shift, fluctuation amplitude damping and low-pass frequency filtering with soil depth, to improve the strategies of parameterizations in land surface schemes, and furthermore, to assess its contribution to climate variability.
Controls on surface soil drying rates observed by SMAP and simulated by the Noah land surface model
NASA Astrophysics Data System (ADS)
Shellito, Peter J.; Small, Eric E.; Livneh, Ben
2018-03-01
Drydown periods that follow precipitation events provide an opportunity to assess controls on soil evaporation on a continental scale. We use SMAP (Soil Moisture Active Passive) observations and Noah simulations from drydown periods to quantify the role of soil moisture, potential evaporation, vegetation cover, and soil texture on soil drying rates. Rates are determined using finite differences over intervals of 1 to 3 days. In the Noah model, the drying rates are a good approximation of direct soil evaporation rates, and our work suggests that SMAP-observed drying is also predominantly affected by direct soil evaporation. Data cover the domain of the North American Land Data Assimilation System Phase 2 and span the first 1.8 years of SMAP's operation. Drying of surface soil moisture observed by SMAP is faster than that simulated by Noah. SMAP drying is fastest when surface soil moisture levels are high, potential evaporation is high, and when vegetation cover is low. Soil texture plays a minor role in SMAP drying rates. Noah simulations show similar responses to soil moisture and potential evaporation, but vegetation has a minimal effect and soil texture has a much larger effect compared to SMAP. When drying rates are normalized by potential evaporation, SMAP observations and Noah simulations both show that increases in vegetation cover lead to decreases in evaporative efficiency from the surface soil. However, the magnitude of this effect simulated by Noah is much weaker than that determined from SMAP observations.
The impact of soil moisture extremes and their spatiotemporal variability on Zambian maize yields
NASA Astrophysics Data System (ADS)
Zhao, Y.; Estes, L. D.; Vergopolan, N.
2017-12-01
Food security in sub-Saharan Africa is highly sensitive to climate variability. While it is well understood that extreme heat has substantial negative impacts on crop yield, the impacts of precipitation extremes, particularly over large spatial extents, are harder to quantify. There are three primary reasons for this difficulty, which are (1) lack of high quality, high resolution precipitation data, (2) rainfall data provide incomplete information on plant water availability, the variable that most directly affects crop performance, and (3) the type of rainfall extreme that most affects crop yields varies throughout the crop development stage. With respect to the first reason, the spatial and temporal variation of precipitation is much greater than that of temperature, yet the spatial resolution of rainfall data is typically even coarser than it is for temperature, particularly within Africa. Even if there were high-resolution rainfall data, the amount of water available to crops also depends on other physical factors that affect evapotranspiration, which are strongly influenced by heterogeneity in the land surface related to topography, soil properties, and land cover. In this context, soil moisture provides a better measure of crop water availability than rainfall. Furthermore, soil moisture has significantly different influences on crop yield depending on the crop's growth stage. The goal of this study is to understand how the spatiotemporal scales of soil moisture extremes interact with crops, more specifically, the timing and the spatial scales of extreme events like droughts and flooding. In this study, we simulate daily-1km soil moisture using HydroBlocks - a physically based land surface model - and compare it with precipitation and remote sensing derived maize yields between 2000 and 2016 in Zambia. We use a novel combination of the SCYM (scalable satellite-based yield mapper) method with DSSAT crop model, which is a mechanistic model responsive to water stress. Understanding the relationships between soil moisture spatiotemporal variability and yields can help to improve agricultural drought risk assessment and seasonal crop yield forecasting as well as early season warning of potential famines.
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.
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.
Waring, Bonnie G; Hawkes, Christine V
2015-05-01
Many wet tropical forests, which contain a quarter of global terrestrial biomass carbon stocks, will experience changes in precipitation regime over the next century. Soil microbial responses to altered rainfall are likely to be an important feedback on ecosystem carbon cycling, but the ecological mechanisms underpinning these responses are poorly understood. We examined how reduced rainfall affected soil microbial abundance, activity, and community composition using a 6-month precipitation exclusion experiment at La Selva Biological Station, Costa Rica. Thereafter, we addressed the persistent effects of field moisture treatments by exposing soils to a controlled soil moisture gradient in the lab for 4 weeks. In the field, compositional and functional responses to reduced rainfall were dependent on initial conditions, consistent with a large degree of spatial heterogeneity in tropical forests. However, the precipitation manipulation significantly altered microbial functional responses to soil moisture. Communities with prior drought exposure exhibited higher respiration rates per unit microbial biomass under all conditions and respired significantly more CO2 than control soils at low soil moisture. These functional patterns suggest that changes in microbial physiology may drive positive feedbacks to rising atmospheric CO2 concentrations if wet tropical forests experience longer or more intense dry seasons in the future.
Soil Moisture Retrieval During a Corn Growth Cycle using L-band (1.6 GHz) Radar Observations
NASA Technical Reports Server (NTRS)
Joseph, Alicia T.; vanderVelde, Rogier; O'Neill, Peggy E.; Lang, Roger; Gish, Tim
2007-01-01
New opportunities for large-scale soil moisture monitoring will emerge with the launch of two low frequency (L-band 1.4 GHz) radiometers: the Aquarius mission in 2009 and the Soil Moisture and Ocean Salinity (SMOS) mission in 2008. Soil moisture is an important land surface variable affecting water and heat exchanges between atmosphere, land surface and deeper ground water reservoirs. The data products from these sensors provide valuable information in a range of climate and hydrologic applications (e.g., numecal weather prediction, drought monitoring, flood forecasting, water resources management, etc.). This paper describes a unique data set that was collected during a field campaign at OPE^ (Optimizing Production Inputs for Economic and Environmental Enhancements) site in Beltsville, Maryland throughout the eompj2ete corn growing in 2002. This investigation describes a simple methodology to correct active microwave observations for vegetation effects, which could potentially be implemented in a global soil moisture monitoring algorithm. The methodology has been applied to radar observation collected during the entire corn growth season and validation against ground measurements showed that the top 5-cm soil moisture can be retrieved with an accuracy up to 0.033 [cu cm/cu cm] depending on the sensing configuration.
Soil Moisture, Coastline Curvature, and Sea Breeze Initiated Precipitation Over Florida
NASA Technical Reports Server (NTRS)
Baker, R. David; Lynn, Barry H.; Boone, Aaron; Tao, Wei-Kuo
1999-01-01
Land surface-atmosphere interaction plays a key role in the development of summertime convection and precipitation over the Florida peninsula. Land-ocean temperature contrasts induce sea-breeze circulations along both coasts. Clouds develop along sea-breeze fronts, and significant precipitation can occur during the summer months. However, other factors such as soil moisture distribution and coastline curvature may modulate the timing, location, and intensity of sea breeze initiated precipitation. Here, we investigate the role of soil moisture and coastline curvature on Florida precipitation using the 3-D Goddard Cumulus Ensemble (GCE) cloud model coupled with the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) land surface model. This study utilizes data from the Convection and Precipitation Electrification Experiment (CaPE) collected on 27 July 1991. Our numerical simulations suggest that a realistic distribution of soil moisture influences the location and intensity of precipitation but not the timing of precipitation. In contrast, coastline curvature affects the timing and location of precipitation but has little influence on peak rainfall rates. However, both factors (soil moisture and coastline curvature) are required to fully account for observed rainfall amounts.
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.
Is soil moisture initialization important for seasonal to decadal predictions?
NASA Astrophysics Data System (ADS)
Stacke, Tobias; Hagemann, Stefan
2014-05-01
The state of soil moisture can can have a significant impact on regional climate conditions for short time scales up to several months. However, focusing on seasonal to decadal time scales, it is not clear whether the predictive skill of global a Earth System Model might be enhanced by assimilating soil moisture data or improving the initial soil moisture conditions with respect to observations. As a first attempt to provide answers to this question, we set up an experiment to investigate the life time (memory) of extreme soil moisture states in the coupled land-atmosphere model ECHAM6-JSBACH, which is part of the Max Planck Institute for Meteorology's Earth System Model (MPI-ESM). This experiment consists of an ensemble of 3 years simulations which are initialized with extreme wet and dry soil moisture states for different seasons and years. Instead of using common thresholds like wilting point or critical soil moisture, the extreme states were extracted from a reference simulation to ensure that they are within the range of simulated climate variability. As a prerequisite for this experiment, the soil hydrology in JSBACH was improved by replacing the bucket-type soil hydrology scheme with a multi-layer scheme. This new scheme is a more realistic representation of the soil, including percolation and diffusion fluxes between up to five separate layers, the limitation of bare soil evaporation to the uppermost soil layer and the addition of a long term water storage below the root zone in regions with deep soil. While the hydrological cycle is not strongly affected by this new scheme, it has some impact on the simulated soil moisture memory which is mostly strengthened due to the additional deep layer water storage. Ensemble statistics of the initialization experiment indicate perturbation lengths between just a few days up to several seasons for some regions. In general, the strongest effects are seen for wet initialization during northern winter over cold and humid regions, while the shortest memory is found during northern spring. For most regions, the soil moisture memory is either sensitive to wet or to dry perturbations, indicating that soil moisture anomalies interact with the respective weather pattern for a given year and might be able to enhance or dampen extreme conditions. To further investigate this effect, the simulations will be repeated using JSBACH with prescribed meteorological forcing to better disentangle the direct effects of soil moisture initialization and the atmospheric response.
Spatial and temporal variability of soil moisture on the field with and without plants*
NASA Astrophysics Data System (ADS)
Usowicz, B.; Marczewski, W.; Usowicz, J. B.
2012-04-01
Spatial and temporal variability of the natural environment is its inherent and unavoidable feature. Every element of the environment is characterized by its own variability. One of the kinds of variability in the natural environment is the variability of the soil environment. To acquire better and deeper knowledge and understanding of the temporal and spatial variability of the physical, chemical and biological features of the soil environment, we should determine the causes that induce a given variability. Relatively stable features of soil include its texture and mineral composition; examples of those variables in time are the soil pH or organic matter content; an example of a feature with strong dynamics is the soil temperature and moisture content. The aim of this study was to identify the variability of soil moisture on the field with and without plants using geostatistical methods. The soil moisture measurements were taken on the object with plant canopy and without plants (as reference). The measurements of soil moisture and meteorological components were taken within the period of April-July. The TDR moisture sensors covered 5 cm soil layers and were installed in the plots in the soil layers of 0-0.05, 0.05-0.1, 0.1-0.15, 0.2-0.25, 0.3-0.35, 0.4-0.45, 0.5-0.55, 0.8-0.85 m. Measurements of soil moisture were taken once a day, in the afternoon hours. For the determination of reciprocal correlation, precipitation data and data from soil moisture measurements with the TDR meter were used. Calculations of reciprocal correlation of precipitation and soil moisture at various depths were made for three objects - spring barley, rye, and bare soil, at the level of significance of p<0.05. No significant reciprocal correlation was found between the precipitation and soil moisture in the soil profile for any of the objects studied. Although the correlation analysis indicates a lack of correlation between the variables under consideration, observation of the soil moisture runs in particular objects and of precipitation distribution shows clearly that rainfall has an effect on the soil moisture. The amount of precipitation water that increased the soil moisture depended on the strength of the rainfall, on the hydrological properties of the soil (primarily the soil density), the status of the plant cover, and surface runoff. Basing on the precipitation distribution and on the soil moisture runs, an attempt was made at finding a temporal and spatial relationship between those variables, employing for the purpose the geostatistical methods which permit time and space to be included in the analysis. The geostatistical parameters determined showed the temporal dependence of moisture distribution in the soil profile, with the autocorrelation radius increasing with increasing depth in the profile. The highest values of the radius were observed in the plots with plant cover below the arable horizon, and the lowest in the arable horizon on the barley and fallow plots. The fractal dimensions showed a clear decrease in values with increasing depth in the plots with plant cover, while in the bare plots they were relatively constant within the soil profile under study. Therefore, they indicated that the temporal distribution of soil moisture within the soil profile in the bare field was more random in character than in the plots with plants. The results obtained and the analyses indicate that the moisture in the soil profile, its variability and determination, are significantly affected by the type and condition of plant canopy. The differentiation in moisture content between the plots studied resulted from different precipitation interception and different intensity of water uptake by the roots. * The work was financially supported in part by the ESA Programme for European Cooperating States (PECS), No.98084 "SWEX-R, Soil Water and Energy Exchange/Research", AO-3275.
NASA Astrophysics Data System (ADS)
Jin, Z.; Guo, L.; Lin, H.; Wang, Y.; Chu, G.
2017-12-01
In this study, a paired of small watersheds, which are artificial forestland and natural grassland, respectively, were selected. The two watersheds have been set up since 1954 and the time of revegetation is more than 60 years. Their differences in event and seasonal dynamics of soil moisture were investigated and the effects of vegetation and landform were analyzed. Results showed that consecutive small events higher than 22 mm and single events higher than 16.6 mm could recharge the soil moisture of the two watersheds, but no rainfall event was observed to recharge the soil moisture of 100 cm within 2 weeks after rainfall initiation. Moreover, the two contrasting watersheds showed no difference in rainfall threshold for effective soil moisture replenishment and also had similar patterns of soil water increment with the increase of initial soil water content and rainfall intensity. The changing vegetation cover and coverage at different landforms (uphill slope land and downhill gully) showed the most significant impact on event and seasonal dynamics of soil moisture. The strong interception, evaporation and transpiration of tree canopy and understory vegetation in the gully of the forestland showed the most negative impacts on soil moisture replenishment. Moreover, dense surface grass biomass (living and dead) in the grassland also showed negative impacts on effective soil moisture recharge. Landform itself showed no significant impact on event soil moisture dynamics through changing the initial soil water content and soil texture, while site differences in slope gradient and soil temperature could affect the seasonal soil water content. During the growing season of May-October, the forestland showed 1.3% higher soil water content than that of the grassland in the landform of uphill slope land; while in the landform of downhill gully, the grassland showed 4.3% higher soil water content than that of the forestland. Many studies have predicted that there will be more extreme precipitation in the global and local dry regions in the 21st century, and thus the threshold and mechanisms of effective rainfall replenishment should be strengthened. Keywords: Soil water monitoring; paired watersheds; afforestation; natural recovery; landform Corresponding author: Prof. Dr. Zhao Jin, jinzhao@ieecas.cn
Correlation Between Soil Moisture and Dust Emissions: An Investigation for Global Climate Modeling
NASA Technical Reports Server (NTRS)
Fredrickson, Carley; Tan, Qian
2017-01-01
This work is using the newly available NASA SMAP soil moisture measurement data to evaluate its impact on the atmospheric dust emissions. Dust is an important component of atmospheric aerosols, which affects both climate and air quality. In this work, we focused on semi-desert regions, where dust emissions show seasonal variations due to soil moisture changes, i.e. in Sahel of Africa. We first identified three Aerosol Robotic Network (AERONET) sites in the Sahel (IER_Cinzana, Banizoumbou, and Zinder_Airport). We then utilized measurements of aerosol optical depth (AOD), fine mode fraction, size distribution, and single-scattering albedo and its wave-length dependence to select dust plumes from the available measurements We matched the latitude and longitude of the AERONET station to the corresponding SMAP data cell in the years 2015 and 2016, and calculated their correlation coefficient. Additionally, we looked at the correlation coefficient with a three-day and a five-day shift to check the impact of soil moisture on dust plumes with some time delay. Due to the arid nature of Banizoumbou and Zinder_Airport, no correlation was found to exist between local soil moisture and dust aerosol load. While IER_Cinzana had soil moisture levels above the satellite threshold of 0.02cm3/cm3, R-value approaching zero indicated no presence of a correlation. On the other hand, Ilorin demonstrated a significant negative correlation between aerosol optical depth and soil moisture. When isolating the analysis to Ilorin's dry season, a negative correlation of -0.593 was the largest dust-isolated R-value recorded, suggesting that soil moisture is driven the dust emission in this semi-desert region during transitional season.
NASA Astrophysics Data System (ADS)
Hao, X.; Qu, J. J.; Motha, R. P.; Stefanski, R.; Malherbe, J.
2014-12-01
Drought is one of the most complicated natural hazards, and causes serious environmental, economic and social consequences. Agricultural production systems, which are highly susceptible to weather and climate extremes, are often the first and most vulnerable sector to be affected by drought events. In Africa, crop yield potential and grazing quality are already nearing their limit of temperature sensitivity, and, rapid population growth and frequent drought episodes pose serious complications for food security. It is critical to promote sustainable agriculture development in Africa under conditions of climate extremes. Soil moisture is one of the most important indicators for agriculture drought, and is a fundamentally critical parameter for decision support in crop management, including planting, water use efficiency and irrigation. While very significant technological advances have been introduced for remote sensing of surface soil moisture from space, in-situ measurements are still critical for calibration and validation of soil moisture estimation algorithms. For operational applications, synergistic collaboration is needed to integrate measurements from different sensors at different spatial and temporal scales. In this presentation, a collaborative effort is demonstrated for drought monitoring in Africa, supported and coordinated by WMO, including surface soil moisture and crop status monitoring. In-situ measurements of soil moisture, precipitation and temperature at selected sites are provided by local partners in Africa. Measurements from the Soil Moisture and Ocean Salinity (SMOS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) are integrated with in-situ observations to derive surface soil moisture at high spatial resolution. Crop status is estimated through temporal analysis of current and historical MODIS measurements. Integrated analysis of soil moisture data and crop status provides both in-depth understanding of drought conditions and potential impacts on crop yield. This information is extremely useful in local decision support for agricultural management.
NASA Astrophysics Data System (ADS)
Hao, X.; Qu, J. J.; Motha, R. P.; Stefanski, R.; Malherbe, J.
2015-12-01
Drought is one of the most complicated natural hazards, and causes serious environmental, economic and social consequences. Agricultural production systems, which are highly susceptible to weather and climate extremes, are often the first and most vulnerable sector to be affected by drought events. In Africa, crop yield potential and grazing quality are already nearing their limit of temperature sensitivity, and, rapid population growth and frequent drought episodes pose serious complications for food security. It is critical to promote sustainable agriculture development in Africa under conditions of climate extremes. Soil moisture is one of the most important indicators for agriculture drought, and is a fundamentally critical parameter for decision support in crop management, including planting, water use efficiency and irrigation. While very significant technological advances have been introduced for remote sensing of surface soil moisture from space, in-situ measurements are still critical for calibration and validation of soil moisture estimation algorithms. For operational applications, synergistic collaboration is needed to integrate measurements from different sensors at different spatial and temporal scales. In this presentation, a collaborative effort is demonstrated for drought monitoring in Africa, supported and coordinated by WMO, including surface soil moisture and crop status monitoring. In-situ measurements of soil moisture, precipitation and temperature at selected sites are provided by local partners in Africa. Measurements from the Soil Moisture and Ocean Salinity (SMOS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) are integrated with in-situ observations to derive surface soil moisture at high spatial resolution. Crop status is estimated through temporal analysis of current and historical MODIS measurements. Integrated analysis of soil moisture data and crop status provides both in-depth understanding of drought conditions and potential impacts on crop yield. This information is extremely useful in local decision support for agricultural management.
Variation among four white ash families in response to competition and allelopathy
George Rink; J.W. Van Sambeek
1987-01-01
Analysis of three environmental variables affecting seedling growth of four half-sib white ash families was dominated by a three-way interaction between soil moisture stress, fescue leachate, and family. Of these, soil moisture stress contributed by far the most to the interaction and resulted in an average growth decline of 62%. Although fescue leachate appeared to be...
Evapotranspiration (ET) is driven by evaporative demand, available solar energy and soil moisture as well as by physiological plant activity which may be substantially affected by elevated CO2 and O3. A multi-year study was conducted in outdoor sun-lit controlled-environment cha...
Evapotranspiration (ET) is driven by evaporative demand, available solar energy and soil moisture (SM) as well as by plant physiological activity which may be substantially affected by elevated CO2 and O3. A multi-year study was conducted in outdoor sunlit-controlled environment ...
Anthropogenic warming exacerbates European soil moisture droughts
NASA Astrophysics Data System (ADS)
Samaniego, L.; Thober, S.; Kumar, R.; Wanders, N.; Rakovec, O.; Pan, M.; Zink, M.; Sheffield, J.; Wood, E. F.; Marx, A.
2018-05-01
Anthropogenic warming is anticipated to increase soil moisture drought in the future. However, projections are accompanied by large uncertainty due to varying estimates of future warming. Here, using an ensemble of hydrological and land-surface models, forced with bias-corrected downscaled general circulation model output, we estimate the impacts of 1-3 K global mean temperature increases on soil moisture droughts in Europe. Compared to the 1.5 K Paris target, an increase of 3 K—which represents current projected temperature change—is found to increase drought area by 40% (±24%), affecting up to 42% (±22%) more of the population. Furthermore, an event similar to the 2003 drought is shown to become twice as frequent; thus, due to their increased occurrence, events of this magnitude will no longer be classified as extreme. In the absence of effective mitigation, Europe will therefore face unprecedented increases in soil moisture drought, presenting new challenges for adaptation across the continent.
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.
Effects of Recent Regional Soil Moisture Variability on Global Net Ecosystem CO2 Exchange
NASA Astrophysics Data System (ADS)
Jones, L. A.; Madani, N.; Kimball, J. S.; Reichle, R. H.; Colliander, A.
2017-12-01
Soil moisture exerts a major regional control on the inter-annual variability of the global land sink for atmospheric CO2. In semi-arid regions, annual biomass production is closely coupled to variability in soil moisture availability, while in cold-season-affected regions, summer drought offsets the effects of advancing spring phenology. Availability of satellite solar-induced fluorescence (SIF) observations and improvements in atmospheric inversions has led to unprecedented ability to monitor atmospheric sink strength. However, discrepancies still exist between such top-down estimates as atmospheric inversion and bottom-up process and satellite driven models, indicating that relative strength, mechanisms, and interaction of driving factors remain poorly understood. We use soil moisture fields informed by Soil Moisture Active Passive Mission (SMAP) observations to compare recent (2015-2017) and historic (2000-2014) variability in net ecosystem land-atmosphere CO2 exchange (NEE). The operational SMAP Level 4 Carbon (L4C) product relates ground-based flux tower measurements to other bottom-up and global top-down estimates to underlying soil moisture and other driving conditions using data-assimilation-based SMAP Level 4 Soil Moisture (L4SM). Droughts in coastal Brazil, South Africa, Eastern Africa, and an anomalous wet period in Eastern Australia were observed by L4C. A seasonal seesaw pattern of below-normal sink strength at high latitudes relative to slightly above-normal sink strength for mid-latitudes was also observed. Whereas SMAP-based soil moisture is relatively informative for short-term temporal variability, soil moisture biases that vary in space and with season constrain the ability of the L4C estimates to accurately resolve NEE. Such biases might be caused by irrigation and plant-accessible ground-water. Nevertheless, SMAP L4C daily NEE estimates connect top-down estimates to variability of effective driving factors for accurate estimates of regional-to-global land-atmosphere CO2 exchange.
Satellite Based Soil Moisture Product Validation Using NOAA-CREST Ground and L-Band Observations
NASA Astrophysics Data System (ADS)
Norouzi, H.; Campo, C.; Temimi, M.; Lakhankar, T.; Khanbilvardi, R.
2015-12-01
Soil moisture content is among most important physical parameters in hydrology, climate, and environmental studies. Many microwave-based satellite observations have been utilized to estimate this parameter. The Advanced Microwave Scanning Radiometer 2 (AMSR2) is one of many remotely sensors that collects daily information of land surface soil moisture. However, many factors such as ancillary data and vegetation scattering can affect the signal and the estimation. Therefore, this information needs to be validated against some "ground-truth" observations. NOAA - Cooperative Remote Sensing and Technology (CREST) center at the City University of New York has a site located at Millbrook, NY with several insitu soil moisture probes and an L-Band radiometer similar to Soil Moisture Passive and Active (SMAP) one. This site is among SMAP Cal/Val sites. Soil moisture information was measured at seven different locations from 2012 to 2015. Hydra probes are used to measure six of these locations. This study utilizes the observations from insitu data and the L-Band radiometer close to ground (at 3 meters height) to validate and to compare soil moisture estimates from AMSR2. Analysis of the measurements and AMSR2 indicated a weak correlation with the hydra probes and a moderate correlation with Cosmic-ray Soil Moisture Observing System (COSMOS probes). Several differences including the differences between pixel size and point measurements can cause these discrepancies. Some interpolation techniques are used to expand point measurements from 6 locations to AMSR2 footprint. Finally, the effect of penetration depth in microwave signal and inconsistencies with other ancillary data such as skin temperature is investigated to provide a better understanding in the analysis. The results show that the retrieval algorithm of AMSR2 is appropriate under certain circumstances. This validation algorithm and similar study will be conducted for SMAP mission. Keywords: Remote Sensing, Soil Moisture, AMSR2, SMAP, L-Band.
van den Hurk, Bart; Kim, Hyungjun; Krinner, Gerhard; ...
2016-08-24
The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth system models (ESMs). Furthermore, the solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both stronglymore » affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. But, models show divergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems). The experiments are subdivided in two components, the first addressing systematic land biases in offline mode (“LMIP”, building upon the 3rd phase of Global Soil Wetness Project; GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework (“LFMIP”, building upon the GLACE-CMIP blueprint).« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
van den Hurk, Bart; Kim, Hyungjun; Krinner, Gerhard
The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth system models (ESMs). Furthermore, the solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both stronglymore » affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. But, models show divergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems). The experiments are subdivided in two components, the first addressing systematic land biases in offline mode (“LMIP”, building upon the 3rd phase of Global Soil Wetness Project; GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework (“LFMIP”, building upon the GLACE-CMIP blueprint).« less
NASA Astrophysics Data System (ADS)
Gupta, Manika; Bolten, John; Lakshmi, Venkat
2016-04-01
Efficient and sustainable irrigation systems require optimization of operational parameters such as irrigation amount which are dependent on the soil hydraulic parameters that affect the model's accuracy in simulating soil water content. However, it is a scientific challenge to provide reliable estimates of soil hydraulic parameters and irrigation estimates, given the absence of continuously operating soil moisture and rain gauge network. For agricultural water resource management, the in-situ measurements of soil moisture are currently limited to discrete measurements at specific locations, and such point-based measurements do not represent the spatial distribution at a larger scale accurately, as soil moisture is highly variable both spatially and temporally (Wang and Qu 2009). In the current study, flood irrigation scheme within the land surface model is triggered when the root-zone soil moisture deficit reaches below a threshold of 25%, 50% and 75% with respect to the maximum available water capacity (difference between field capacity and wilting point) and applied until the top layer is saturated. An additional important criterion needed to activate the irrigation scheme is to ensure that it is irrigation season by assuming that the greenness vegetation fraction (GVF) of the pixel exceed 0.40 of the climatological annual range of GVF (Ozdogan et al. 2010). The main hypothesis used in this study is that near-surface remote sensing soil moisture data contain useful information that can describe the effective hydrological conditions of the basin such that when appropriately inverted, it would provide field capacity and wilting point soil moisture, which may be representative of that basin. Thus, genetic algorithm inverse method is employed to derive the effective parameters and derive the soil moisture deficit for the root zone by coupling of AMSR-E soil moisture with the physically based hydrological model. Model performance is evaluated using MODIS-evapotranspiration (ET) and MODIS land surface temperature (LST) products. The soil moisture estimates for the root zone are also validated with the in-situ field data, for three sites (2- irrigated and 1- rainfed) located at the University of Nebraska Agricultural Research and Development Center near Mead, NE and monitored by three AmeriFlux installations (Verma et al., 2005) by evaluating the root mean square error (RMSE) and Mean Bias error (MBE).
NASA Astrophysics Data System (ADS)
Piles, Maria; Sánchez, Nilda; Vall-llossera, Mercè; Ballabrera, Joaquim; Martínez, Justino; Martínez-Fernández, José; Camps, Adriano; Font, Jordi
2014-05-01
Soil moisture plays an important role in determining the likelihood of droughts and floods that may affect an area. Knowledge of soil moisture distribution as a function of time and space is highly relevant for hydrological, ecological and agricultural applications, especially in water-limited or drought-prone regions. However, measuring soil moisture is challenging because of its high variability; point-scale in-situ measurements are scarce being remote sensing the only practical means to obtain regional- and global-scale soil moisture estimates. The ESA's Soil Moisture and Ocean Salinity (SMOS) is the first satellite mission ever designed to measuring the Earth's surface soil moisture at near daily time scales with levels of accuracy previously not attained. Since its launch in November 2009, significant efforts have been dedicated to validate and fine-tune the retrieval algorithms so that SMOS-derived soil moisture estimates meet the standards required for a wide variety of applications. In this line, the SMOS Barcelona Expert Center (BEC) is distributing daily, monthly, and annual temporal averages of 0.25-deg global soil moisture maps, which have proved useful for assessing drought and water-stress conditions. In addition, a downscaling algorithm has been developed to combine SMOS and NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) data into fine-scale (< 1km) soil moisture estimates, which permits extending the applicability of the data to regional and local studies. Fine-scale soil moisture maps are currently limited to the Iberian Peninsula but the algorithm is dynamic and can be transported to any region. Soil moisture maps are generated in a near real-time fashion at BEC facilities and are used by Barcelona's fire prevention services to detect extremely dry soil and vegetation conditions posing a risk of fire. Recently, they have been used to explain drought-induced tree mortality episodes and forest decline in the Catalonia region. These soil moisture products can also be a useful tool to monitor the effectiveness of land restoration management practices. The aim of this work is to demonstrate the feasibility of using SMOS soil moisture maps for monitoring drought and water-stress conditions. In previous research, SMOS-derived Soil Moisture Anomalies (SSMA), calculated in a ten-day basis, were shown to be in close relationship with well-known drought indices (the Standardized Precipitation Index and the Standardized Precipitation Evapotranspiration Index). In this work, SSMA have been calculated for the period 2010-2013 in representative arid, semi-arid, sub-humid and humid areas across global land biomes. The SSMA reflect the cumulative precipitation anomalies and is known to provide 'memory' in the climate and hydrological system; the water retained in the soil after a rainfall event is temporally more persistent than the rainfall event itself, and has a greater persistence during periods of low precipitation. Besides, the Normalized Difference Vegetation Index (NDVI) from MODIS is used as an indicator of vegetation activity and growth. The NDVI time series are expected to reflect the changes in surface vegetation density and status induced by water-deficit conditions. Understanding the relationships between SSMA and NDVI concurrent time series should provide new insight about the sensitivity of land biomes to drought.
NASA Astrophysics Data System (ADS)
Walmsley, Alena; Vachová, Pavla; Vach, Marek
2016-04-01
This research was investigating whether topographic features, which determine soil nutrient and moisture distribution, in combination with soil fauna (wireworm and earthworm) presence, affect plant community composition at a spontaneously revegetated post mining area with an undulating surface. Two sites of different age with 3 types of topographic features were selected, soil moisture and nutrient content were measured, plant community composition and soil macrofauna community was sampled at each position. Wireworms were present at all positions and were most abundant at bottoms of waves at the younger site; their presence was correlated with several plant species, but the direction of the interaction isn't clear. Earthworms were only present at the older site and had highest abundance at flat sections. Earthworm presence affected the amount of nitrogen in soil - the most nitrogen content was at the site with highest earthworm density and was followed by higher diversity of plant community. The plant community composition was generally correlated with plant available nutrient content - especially P and N. We infer that topographic features affect nutrient and soil fauna distribution, which consequently influences plant community composition.
NASA Astrophysics Data System (ADS)
Lanka, K.; Pan, M.; Wanders, N.; Kumar, D. N.; Wood, E. F.
2017-12-01
The satellite based passive and active microwave sensors enhanced our ability to retrieve soil moisture at global scales. It has been almost four decades since the first passive microwave satellite sensor was launched in 1978. Since then soil moisture has gained considerable attention in hydro-meteorological, climate, and agricultural research resulting in the deployment of two dedicated missions in the last decade, SMOS and SMAP. Signifying the four decades of microwave remote sensing of soil moisture, this work aims to present an overview of how our knowledge in this field has improved in terms of the design of sensors and their accuracy of retrieving soil moisture. We considered daily coverage, temporal performance, and spatial performance to assess the accuracy of products corresponding to eight passive sensors (SMMR, SSM/I, TMI, AMSR-E, WindSAT, AMSR2, SMOS and SMAP), two active sensors (ERS-Scatterometer, MetOp-ASCAT), and one active/passive merged soil moisture product (ESA-CCI combined product), using 1058 ISMN in-situ stations and the VIC LSM soil moisture simulations (VICSM) over the CONUS. Our analysis indicated that the daily coverage has increased from 30 % during 1980s to 85 % (during non-winter months) with the launch of dedicated soil moisture missions SMOS and SMAP. The temporal validation of passive and active soil moisture products with the ISMN data place the range of median RMSE as 0.06-0.10 m3/m3 and median correlation as 0.20-0.68. When TMI, AMSR-E and WindSAT are evaluated, the AMSR-E sensor is found to have produced the brightness temperatures with better quality, given that these sensors are paired with same retrieval algorithm (LPRM). The ASCAT product shows a significant improvement during the temporal validation of retrievals compared to its predecessor ERS, thanks to enhanced sensor configuration. The SMAP mission, through its improved sensor design and RFI handling, shows a high retrieval accuracy under all-topography conditions. Although the retrievals from the SMOS mission are affected by issues such as RFI, the accuracy is still comparable to or better than that of AMSR-E and ASCAT sensors. All soil moisture products have indicated better agreement with the ISMN data than the VICSM, which indicate that they produce soil moisture with better accuracy than the VICSM over the CONUS.
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.
Feng, Wei; Zhang, Yuqing; Jia, Xin; Wu, Bin; Zha, Tianshan; Qin, Shugao; Wang, Ben; Shao, Chenxi; Liu, Jiabin; Fa, Keyu
2014-01-01
The responses of soil respiration to environmental conditions have been studied extensively in various ecosystems. However, little is known about the impacts of temperature and moisture on soils respiration under biological soil crusts. In this study, CO2 efflux from biologically-crusted soils was measured continuously with an automated chamber system in Ningxia, northwest China, from June to October 2012. The highest soil respiration was observed in lichen-crusted soil (0.93±0.43 µmol m−2 s−1) and the lowest values in algae-crusted soil (0.73±0.31 µmol m−2 s−1). Over the diurnal scale, soil respiration was highest in the morning whereas soil temperature was highest in the midday, which resulted in diurnal hysteresis between the two variables. In addition, the lag time between soil respiration and soil temperature was negatively correlated with the soil volumetric water content and was reduced as soil water content increased. Over the seasonal scale, daily mean nighttime soil respiration was positively correlated with soil temperature when moisture exceeded 0.075 and 0.085 m3 m−3 in lichen- and moss-crusted soil, respectively. However, moisture did not affect on soil respiration in algae-crusted soil during the study period. Daily mean nighttime soil respiration normalized by soil temperature increased with water content in lichen- and moss-crusted soil. Our results indicated that different types of biological soil crusts could affect response of soil respiration to environmental factors. There is a need to consider the spatial distribution of different types of biological soil crusts and their relative contributions to the total C budgets at the ecosystem or landscape level. PMID:25050837
Hawke, Richard; McConchie, Jack
2011-02-01
The immediate cost of shallow regolith landslides in New Zealand has been estimated to exceed US$33M annually. Since the majority of these landslides occur during prolonged wet conditions, or intense rainstorms, moisture conditions are a critical control. The nature, dynamics, and character of soil moisture conditions, and the piezometric response to rainfall, have been recorded within an 'incipient' landslide for more than 5 years. The study site, on pastoral hill country within the Lake Tutira catchment in northern Hawkes Bay, is typical of large areas of New Zealand episodically affected by extensive landsliding. Detailed continuous measurements show that both the soil moisture and piezometric response within the regolith are highly storm- and site-specific. The development of positive pore pressures is infrequent; they form only during intense rainstorms, and persist for a short time. The hydraulic response of the soil is primarily a function of storm characteristics, but this response can be modified by antecedent moisture conditions, topographic position, and heterogeneity of soil properties. Stability analysis shows that most slopes in the study area are significantly steeper than can be explained by the frictional strength of the regolith. Measured hydraulic conditions also show that positive pore-water pressures alone do not trigger slope instability. A recent slope failure followed a period of extremely high antecedent moisture conditions, and occurred when maximum soil moisture conditions, though not pore-water pressures, were recorded. Increased moisture content of the regolith reduces matric tension, and therefore effective cohesion of the soil. This cohesion is critical to maintaining stability of the regolith on these slopes. Copyright © 2009 Elsevier Ltd. All rights reserved.
O'Brien, S. L.; Jastrow, J.D.; Grimley, D.A.; Gonzalez-Meler, M. A.
2010-01-01
Revitalization of degraded landscapes may provide sinks for rising atmospheric CO2, especially in reconstructed prairies where substantial belowground productivity is coupled with large soil organic carbon (SOC) deficits after many decades of cultivation. The restoration process also provides opportunities to study the often-elusive factors that regulate soil processes. Although the precise mechanisms that govern the rate of SOC accrual are unclear, factors such as soil moisture or vegetation type may influence the net accrual rate by affecting the balance between organic matter inputs and decomposition. A resampling approach was used to assess the control that soil moisture and plant community type each exert on SOC and total nitrogen (TN) accumulation in restored grasslands. Five plots that varied in drainage were sampled at least four times over two decades to assess SOC, TN, and C4- and C3-derived C. We found that higher long-term soil moisture, characterized by low soil magnetic susceptibility, promoted SOC and TN accrual, with twice the SOC and three times the TN gain in seasonally saturated prairies compared with mesic prairies. Vegetation also influenced SOC and TN recovery, as accrual was faster in the prairies compared with C3-only grassland, and C4-derived C accrual correlated strongly to total SOC accrual but C3-C did not. High SOC accumulation at the surface (0-10 cm) combined with losses at depth (10-20 cm) suggested these soils are recovering the highly stratified profiles typical of remnant prairies. Our results suggest that local hydrology and plant community are critical drivers of SOC and TN recovery in restored grasslands. Because these factors and the way they affect SOC are susceptible to modification by climate change, we contend that predictions of the C-sequestration performance of restored grasslands must account for projected climatic changes on both soil moisture and the seasonal productivity of C4 and C3 plants. ?? 2009 Blackwell Publishing Ltd.
NASA Astrophysics Data System (ADS)
Chifflard, Peter; Weishaupt, Philipp; Reiss, Martin
2017-04-01
Spatial and temporal patterns of throughfall can affect the heterogeneity of ecological, biogeochemical and hydrological processes at a forest floor and further the underlying soil. Previous research suggests different factors controlling the spatial and temporal patterns of throughfall, but most studies focus on coniferous forest, where the vegetation coverage is more or less constant over time. In deciduous forests the leaf area index varies due to the leaf fall in autumn which implicates a specific spatial and temporal variability of throughfall and furthermore of the soil moisture. Therefore, in the present study, the measurements of throughfall and soil moisture in a deciduous forest in the low mountain ranges focused especially on the period of leaf fall. The aims of this study were: 1) to detect the spatial and temporal variability of both the throughfall and the soil moisture, 2) to examine the temporal stability of the spatial patterns of the throughfall and soil moisture and 3) relate the soil moisture patterns to the throughfall patterns and further to the canopy characteristics. The study was carried out in a small catchment on middle Hesse (Germany) which is covered by beech forest. Annual mean air temperature is 9.4°C (48.9˚F) and annual mean precipitation is 650 mm. Base materials for soil genesis is greywacke and clay shale from Devonian deposits. The soil type at the study plot is a shallow cambisol. The study plot covers an area of about 150 m2 where 77 throughfall samplers where installed. The throughfall and the soil moisture (FDR-method, 20 cm depth) was measured immediately after every rainfall event at the 77 measurement points. During the period of October to December 2015 altogether 7 events were investigated. The geostatistical method kriging was used to interpolate between the measurements points to visualize the spatial patterns of each investigated parameter. Time-stability-plots were applied to examine temporal scatters of each investigated parameter. The spearmen and pearson correlation coefficients were applied to detect the relationship between the different investigated parameters. First results show that the spatial variability of throughfall decreases if the total amount of the throughfall increases. The soil moisture shows a similar behavior. It`s spatial variability decreases if higher soil moisture values were measured. Concerning the temporal stability of throughfall it can be shown that it is very high during the leaf-free period, although the rainfall events have different total througfall amounts. The soil moisture patterns consists of a low temporal stability and additionally only during one event a significant correlations between throughfall and soil moisture patterns exists. This implies that other factors than the throughfall patterns control the spatial patterns of soil moisture.
On the relationship between land surface infrared emissivity and soil moisture
NASA Astrophysics Data System (ADS)
Zhou, Daniel K.; Larar, Allen M.; Liu, Xu
2018-01-01
The relationship between surface infrared (IR) emissivity and soil moisture content has been investigated based on satellite measurements. Surface soil moisture content can be estimated by IR remote sensing, namely using the surface parameters of IR emissivity, temperature, vegetation coverage, and soil texture. It is possible to separate IR emissivity from other parameters affecting surface soil moisture estimation. The main objective of this paper is to examine the correlation between land surface IR emissivity and soil moisture. To this end, we have developed a simple yet effective scheme to estimate volumetric soil moisture (VSM) using IR land surface emissivity retrieved from satellite IR spectral radiance measurements, assuming those other parameters impacting the radiative transfer (e.g., temperature, vegetation coverage, and surface roughness) are known for an acceptable time and space reference location. This scheme is applied to a decade of global IR emissivity data retrieved from MetOp-A infrared atmospheric sounding interferometer measurements. The VSM estimated from these IR emissivity data (denoted as IR-VSM) is used to demonstrate its measurement-to-measurement variations. Representative 0.25-deg spatially-gridded monthly-mean IR-VSM global datasets are then assembled to compare with those routinely provided from satellite microwave (MW) multisensor measurements (denoted as MW-VSM), demonstrating VSM spatial variations as well as seasonal-cycles and interannual variability. Initial positive agreement is shown to exist between IR- and MW-VSM (i.e., R2 = 0.85). IR land surface emissivity contains surface water content information. So, when IR measurements are used to estimate soil moisture, this correlation produces results that correspond with those customarily achievable from MW measurements. A decade-long monthly-gridded emissivity atlas is used to estimate IR-VSM, to demonstrate its seasonal-cycle and interannual variation, which is spatially coherent and consistent with that from MW measurements, and, moreover, to achieve our objective of investigating the relationship between land surface IR emissivity and soil moisture.
Soil moisture dynamics and their effect on bioretention performance in Northeast Ohio
NASA Astrophysics Data System (ADS)
Bush, S. A.; Jefferson, A.; Jarden, K.; Kinsman-Costello, L. E.; Grieser, J.
2014-12-01
Urban impervious surfaces lead to increases in stormwater runoff. Green infrastructure, like bioretention cells, is being used to mitigate negative impacts of runoff by disconnecting impervious surfaces from storm water systems and redirecting flow to decentralized treatment areas. While bioretention soil characteristics are carefully designed, little research is available on soil moisture dynamics within the cells and how these might relate to inter-storm variability in performance. Bioretentions have been installed along a residential street in Parma, Ohio to determine the impact of green infrastructure on the West Creek watershed, a 36 km2 subwatershed of the Cuyahoga River. Bioretentions were installed in two phases (Phase I in 2013 and Phase II in 2014); design and vegetation density vary slightly between the two phases. Our research focuses on characterizing soil moisture dynamics of multiple bioretentions and assessing their impact on stormwater runoff at the street scale. Soil moisture measurements were collected in transects for eight bioretentions over the course of one summer. Vegetation indices of canopy height, percent vegetative cover, species richness and NDVI were also measured. A flow meter in the storm drain at the end of the street measured storm sewer discharge. Precipitation was recorded from a meteorological station 2 km from the research site. Soil moisture increased in response to precipitation and decreased to relatively stable conditions within 3 days following a rain event. Phase II bioretentions exhibited greater soil moisture and less vegetation than Phase I bioretentions, though the relationship between soil moisture and vegetative cover is inconclusive for bioretentions constructed in the same phase. Data from five storms suggest that pre-event soil moisture does not control the runoff-to-rainfall ratio, which we use as a measure of bioretention performance. However, discharge data indicate that hydrograph characteristics, such as lag time and peak flow, are altered relative to a control street. This analysis suggests that street-scale implementation of bioretention can reduce the impact of impervious surface on stormflows, but more information is needed to fully understand how soil moisture of the bioretentions affects inter-storm variability in performance.
NASA Astrophysics Data System (ADS)
Shongwe, M.
2014-12-01
The warming rates projected by an ensemble of the Coupled Model Intercomparion Project Phase 5 (CMIP5) global climate models (GCMs) over southern Africa (south of 10 degrees latitude) are investigated. In all RCPs, CMIP5 models project a higher warming rate over the southwestern parts centred around the arid Kalahari and Namib deserts. The higher warming rates over these areas outpace global warming by up to a factor 2 in some GCMs. The projected warming is associated with an increase in heat waves. There is notable consensus across the models with little intermodel spread, suggesting a strong robustness of the projections. Mechanisms underlying the enhanced warming are investigated. A positive soil moisture-temperature feedback is suggested to contribute to the accelerated temperature increase. A decrease in soil moisture is projected by the GCMs over the area of highest warming. The reduction in soil wetness reduces evapotranspiration rates over the area where evaporation is dependent on available soil moisture. The reduction is evapotranspiration affects the partitioning of turbulent energy fluxes from the soil surface into the atmosphere and translates into an increase of the Bowen ratio featuring an increase in sensible relative to latent heat flux. An increase in sensible heat flux leads to an increase in near-surface temperature. The increase in temperature leads to a higher vapour pressure deficit and evaporative demand and evapotranspiration from the dry soils, possibly leading to a further decrease in soil moisture. A precipitation-soil moisture feedback is also suggested. A decrease in mean precipitation and an increase in drought conditions are projected over the area of enhanced warming. The reduced precipitation results in drier soils. The drier soil translates to reduced evapotranspiration for cloud and rainfall formation. However, the role played by the soil moisture-precipitation feedback loop is still inconclusive and characterized by some degree of uncertainty given that the strength of the local moisture recycling has not been explicitly quantified. An alternative mechanism involving the impact of soil moisture anomalies on boundary-layer stability and precipitation formation will be investigated.
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.
Soil Organic Carbon Pools and Stocks in Permafrost-Affected Soils on the Tibetan Plateau
Dörfer, Corina; Kühn, Peter; Baumann, Frank; He, Jin-Sheng; Scholten, Thomas
2013-01-01
The Tibetan Plateau reacts particularly sensitively to possible effects of climate change. Approximately two thirds of the total area is affected by permafrost. To get a better understanding of the role of permafrost on soil organic carbon pools and stocks, investigations were carried out including both discontinuous (site Huashixia, HUA) and continuous permafrost (site Wudaoliang, WUD). Three organic carbon fractions were isolated using density separation combined with ultrasonic dispersion: the light fractions (<1.6 g cm−3) of free particulate organic matter (FPOM) and occluded particulate organic matter (OPOM), plus a heavy fraction (>1.6 g cm−3) of mineral associated organic matter (MOM). The fractions were analyzed for C, N, and their portion of organic C. FPOM contained an average SOC content of 252 g kg−1. Higher SOC contents (320 g kg−1) were found in OPOM while MOM had the lowest SOC contents (29 g kg−1). Due to their lower density the easily decomposable fractions FPOM and OPOM contribute 27% (HUA) and 22% (WUD) to the total SOC stocks. In HUA mean SOC stocks (0–30 cm depth) account for 10.4 kg m−2, compared to 3.4 kg m−2 in WUD. 53% of the SOC is stored in the upper 10 cm in WUD, in HUA only 39%. Highest POM values of 36% occurred in profiles with high soil moisture content. SOC stocks, soil moisture and active layer thickness correlated strongly in discontinuous permafrost while no correlation between SOC stocks and active layer thickness and only a weak relation between soil moisture and SOC stocks could be found in continuous permafrost. Consequently, permafrost-affected soils in discontinuous permafrost environments are susceptible to soil moisture changes due to alterations in quantity and seasonal distribution of precipitation, increasing temperature and therefore evaporation. PMID:23468904
The desorptivity model of bulk soil-water evaporation
NASA Technical Reports Server (NTRS)
Clapp, R. B.
1983-01-01
Available models of bulk evaporation from a bare-surfaced soil are difficult to apply to field conditions where evaporation is complicated by two main factors: rate-limiting climatic conditions and redistribution of soil moisture following infiltration. Both factors are included in the "desorptivity model', wherein the evaporation rate during the second stage (the soil-limiting stage) of evaporation is related to the desorptivity parameter, A. Analytical approximations for A are presented. The approximations are independent of the surface soil moisture. However, calculations using the approximations indicate that both soil texture and soil moisture content at depth significantly affect A. Because the moisture content at depth decreases in time during redistribution, it follows that the A parameter also changes with time. Consequently, a method to calculate a representative value of A was developed. When applied to field data, the desorptivity model estimated cumulative evaporation well. The model is easy to calculate, but its usefulness is limited because it requires an independent estimate of the time of transition between the first and second stages of evaporation. The model shows that bulk evaporation after the transition to the second stage is largely independent of climatic conditions.
Evaporative losses from soils covered by physical and different types of biological soil crusts
Chamizo, S.; Cantón, Y.; Domingo, F.; Belnap, J.
2013-01-01
Evaporation of soil moisture is one of the most important processes affecting water availability in semiarid ecosystems. Biological soil crusts, which are widely distributed ground cover in these ecosystems, play a recognized role on water processes. Where they roughen surfaces, water residence time and thus infiltration can be greatly enhanced, whereas their ability to clog soil pores or cap the soil surface when wetted can greatly decrease infiltration rate, thus affecting evaporative losses. In this work, we compared evaporation in soils covered by physical crusts, biological crusts in different developmental stages and in the soils underlying the different biological crust types. Our results show that during the time of the highest evaporation (Day 1), there was no difference among any of the crust types or the soils underlying them. On Day 2, when soil moisture was moderately low (11%), evaporation was slightly higher in well-developed biological soil crusts than in physical or poorly developed biological soil crusts. However, crust removal did not cause significant changes in evaporation compared with the respective soil crust type. These results suggest that the small differences we observed in evaporation among crust types could be caused by differences in the properties of the soil underneath the biological crusts. At low soil moisture (<6%), there was no difference in evaporation among crust types or the underlying soils. Water loss for the complete evaporative cycle (from saturation to dry soil) was similar in both crusted and scraped soils. Therefore, we conclude that for the specific crust and soil types tested, the presence or the type of biological soil crust did not greatly modify evaporation with respect to physical crusts or scraped soils.
Extended monitoring and analysis of moisture-temperature data
DOT National Transportation Integrated Search
2001-10-01
The performance of asphalt concrete pavements is in part affected by the seasonal variations of the resilient modulus of the AC layer and of the subgrade soil. To determine the variation of these parameters throughout Ohio, nine moisture-temperature-...
NASA Astrophysics Data System (ADS)
McKnight, J.; Klein, E. S.; Welker, J. M.; Schaeffer, S. M.; Franklin, M.
2015-12-01
High Arctic landscapes are composed of watershed basins that vary in size and ecohydrology, but typically have a plant community complex that ranges from dry tundra to moist tundra to wet sedge systems along water body shorelines. The spatial extent of these plant communities reflects mean annual soil moisture and temperature, and is vulnerable to changes in climate conditions. Soil moisture and temperature significantly influence organic matter microbial activity and decomposition, and can affect the fate of soil carbon in tundra soils. Consequently, due to the unique soil carbon differences between tundra plant communities, shifts in their spatial extent may drive future High Arctic biosphere-atmosphere interactions. Understanding this terrestrial-atmosphere trace gas feedback, however, requires quantification of the rates and patterns of CO2 exchange along soil moisture gradients and the associated soil properties. In summer of 2015, soil CO2 flux rate, soil moisture and temperature were measured along a soil moisture gradient spanning three vegetation zones (dry tundra, wet tundra, and wet grassland) in a snow melt-fed lake basin near Thule Greenland. Mean soil temperature during the 2015 growing season was greater in dry tundra than in wet tundra and wet grassland (13.0 ± 1.2, 7.8 ± 0.8, and 5.5 ± 0.9°C, respectively). Mean volumetric soil moisture differed among all three vegetation zones where the soil moisture gradient ranged from 9 % (dry tundra) to 34 % (wet tundra) to 51 % (wet grassland). Mean soil CO2 flux was significantly greater in the wet grassland (1.7 ± 0.1 μmol m-2 s-1) compared to wet tundra (0.9 ± 0.2 μmol m-2 s-1) and dry tundra (1.2 ± 0.2 μmol m-2 s-1). Soil CO2 flux increased and decreased with seasonal warming and cooling of soil temperature. Although soil temperature was an important seasonal driver of soil CO2 flux rates, differences in mean seasonal soil CO2 flux rates among vegetation zones appeared to be a function of the combined effects of soil temperature and soil moisture conditions. These results suggest that the response of vegetation distribution to shifts in precipitation and warmer climate conditions may have significant implications for release of soil carbon as CO2 in High Arctic tundra ecosystems in Northwest Greenland.
Zhang, Jianguo; Xu, Xinwen; Li, Shengyu; Zhao, Ying; Zhang, Afeng; Zhang, Tibin; Jiang, Rui
2016-01-01
Freshwater resources are scarce in desert regions. Highly saline groundwater of different salinity is being used to drip irrigate the Taklimakan Desert Highway Shelterbelt with a double-branch-pipe system controlling the irrigation cycles. In this study, to evaluate the dynamics of soil moisture and salinity under the current irrigation system, soil samples were collected to a 2-m depth in the shelterbelt planted for different years and irrigated with different groundwater salinities, and soil moisture and salinity were analyzed. The results showed that both depletion of soil moisture and increase of topsoil salinity occurred simultaneously during one irrigation cycle. Soil moisture decreased from 27.4% to 2.4% for a 15-day irrigation cycle and from 26.4% to 2.7% for a 10-day-cycle, respectively. Topsoil electrical conductivity (EC) increased from 0.64 to 3.32 dS/m and 0.70 to 3.99 dS/m for these two irrigation cycles. With increased shelterbelt age, profiled average soil moisture (0–200 cm) reduced from 12.8% (1-year) to 7.1% (10-year); however, soil moisture in 0–20-cm increased, while topsoil salinity decreased. In addition, irrigation salinity mainly affected soil salinity in the 0–20-cm range. We conclude that water supply with the double-branch-pipe is a feasible irrigation method for the Taklimakan Desert Highway Shelterbelt, and our findings provide a model for shelterbelt construction and sustainable management when using highly saline water for irrigation in analogous habitats. PMID:27711244
Bayesian Hierarchical Modeling for Big Data Fusion in Soil Hydrology
NASA Astrophysics Data System (ADS)
Mohanty, B.; Kathuria, D.; Katzfuss, M.
2016-12-01
Soil moisture datasets from remote sensing (RS) platforms (such as SMOS and SMAP) and reanalysis products from land surface models are typically available on a coarse spatial granularity of several square km. Ground based sensors on the other hand provide observations on a finer spatial scale (meter scale or less) but are sparsely available. Soil moisture is affected by high variability due to complex interactions between geologic, topographic, vegetation and atmospheric variables. Hydrologic processes usually occur at a scale of 1 km or less and therefore spatially ubiquitous and temporally periodic soil moisture products at this scale are required to aid local decision makers in agriculture, weather prediction and reservoir operations. Past literature has largely focused on downscaling RS soil moisture for a small extent of a field or a watershed and hence the applicability of such products has been limited. The present study employs a spatial Bayesian Hierarchical Model (BHM) to derive soil moisture products at a spatial scale of 1 km for the state of Oklahoma by fusing point scale Mesonet data and coarse scale RS data for soil moisture and its auxiliary covariates such as precipitation, topography, soil texture and vegetation. It is seen that the BHM model handles change of support problems easily while performing accurate uncertainty quantification arising from measurement errors and imperfect retrieval algorithms. The computational challenge arising due to the large number of measurements is tackled by utilizing basis function approaches and likelihood approximations. The BHM model can be considered as a complex Bayesian extension of traditional geostatistical prediction methods (such as Kriging) for large datasets in the presence of uncertainties.
Yargicoglu, Erin N; Reddy, Krishna R
2017-05-15
Alternate landfill covers designed to enhance microbial methane (CH 4 ) oxidation and reduce the negative impacts of landfill gas emissions on global climate have recently been proposed and investigated. In this study, the use of biochar as a soil amendment is examined in order to assess the feasibility and effectiveness for enhanced CH 4 removal in landfill covers when incorporated under high compaction conditions and relatively low soil moisture. Four different cover configurations were tested in large soil columns for ∼510 days and potential CH 4 oxidation rates were determined following long-term incubation in small batch assays. Cover designs tested include: a thin biochar layer at 15-18 cm; 2% mixed soil-biochar layer at 20-40 cm; 2% mixed soil-uncharred wood pellets at 20-40 cm; and soil obtained from intermediate cover at an active landfill site. The placement of a thin biochar layer in the cover significantly impacted moisture distribution and infiltration, which in turn affected CH 4 oxidation potential with depth. An increase in CH 4 removal rates was observed among all columns over the 500 day incubation period, with steady-state CH 4 removal efficiencies ranging from ∼60 to 90% in the final stages of incubation (inlet load ∼80 g CH 4 m -2 d -1 ). The thin biochar layer had the lowest average removal efficiency as a result of reduced moisture availability below the biochar layer. The addition of 2% biochar to soil yielded similar CH 4 oxidation rates in terminal assays as the 2% uncharred wood pellet amendment. CH 4 oxidation rates in terminal assays were positively correlated with soil moisture, which was affected by the materials' water holding capacity. The high water holding capacity of biochar led to higher oxidation rates within the thin biochar layer, supporting the initial hypothesis that biochar may confer more favorable physical conditions for methanotrophy. Ultimate performance was apparently affected by soil type and CH 4 exposure history, with the highest oxidation rates observed in the unamended field soil with higher initial methanotrophic activity. Copyright © 2017 Elsevier Ltd. All rights reserved.
Climate change reduces the net sink of CH4 and N2O in a semiarid grassland.
Dijkstra, Feike A; Morgan, Jack A; Follett, Ronald F; Lecain, Daniel R
2013-06-01
Atmospheric concentrations of methane (CH4 ) and nitrous oxide (N2 O) have increased over the last 150 years because of human activity. Soils are important sources and sinks of both potent greenhouse gases where their production and consumption are largely regulated by biological processes. Climate change could alter these processes thereby affecting both rate and direction of their exchange with the atmosphere. We examined how a rise in atmospheric CO2 and temperature affected CH4 and N2 O fluxes in a well-drained upland soil (volumetric water content ranging between 6% and 23%) in a semiarid grassland during five growing seasons. We hypothesized that responses of CH4 and N2 O fluxes to elevated CO2 and warming would be driven primarily by treatment effects on soil moisture. Previously we showed that elevated CO2 increased and warming decreased soil moisture in this grassland. We therefore expected that elevated CO2 and warming would have opposing effects on CH4 and N2 O fluxes. Methane was taken up throughout the growing season in all 5 years. A bell-shaped relationship was observed with soil moisture with highest CH4 uptake at intermediate soil moisture. Both N2 O emission and uptake occurred at our site with some years showing cumulative N2 O emission and other years showing cumulative N2 O uptake. Nitrous oxide exchange switched from net uptake to net emission with increasing soil moisture. In contrast to our hypothesis, both elevated CO2 and warming reduced the sink of CH4 and N2 O expressed in CO2 equivalents (across 5 years by 7% and 11% for elevated CO2 and warming respectively) suggesting that soil moisture changes were not solely responsible for this reduction. We conclude that in a future climate this semiarid grassland may become a smaller sink for atmospheric CH4 and N2 O expressed in CO2 -equivalents. © 2013 Blackwell Publishing Ltd.
Teng, Jia Ling; Jia, Rong Liang; Hu, Yi Gang; Xu, Bing Xin; Chen, Meng Chen; Zhao, Yun
2016-03-01
Based on the measurements of the fluxes of CO 2 , CH 4 and N 2 O from the soil covered by two types of biocrusts dominated separately by moss and algae-lichen, followed by 0 (control), 1 (shallow) and 10 (deep) mm depths of sand burial treatments, we studied the effects of sand burial on greenhouse gases fluxes and their relationships with soil temperature and moisture at Shapotou, southeastern edge of the Tengger Desert. The results showed that sand burial had significantly positive effects on CO 2 emission fluxes and CH 4 uptake fluxes of the soil covered by the two types of biocrusts, but imposed differential effects on N 2 O fluxes depending on the type of biocrust and the depth of burial. Deep burial (10 mm) dramatically increased the N 2 O uptake fluxes of the soil co-vered by the two types of biocrusts, while shallow burial (1 mm) decreased the N 2 O uptake flux of the soil co-vered by moss crust only and had no significant effects on N 2 O uptake flux of the soil covered by algae-lichen crust. In addition, CO 2 fluxes of the two biocrusts were closely related to the soil temperature and soil moisture, thereby increasing with the raised soil surface temperature and soil moisture caused by sand burial. However, the relationships of burial-induced changes of soil temperature and moisture with the changes in the other two greenhouse gases fluxes were not evident, indicating that the variations of soil temperature and moisture caused by sand burial were not the key factors affecting the fluxes of CH 4 and N 2 O of the soil covered by the two types of biocrusts.
The impact of extreme environmental factors on the mineralization potential of the soil
NASA Astrophysics Data System (ADS)
Zinyakova, Natalia; Semenov, Vyacheslav
2016-04-01
Warming, drying, wetting are the prevalent disturbing natural impacts that affect the upper layers of uncultivated and arable soils. The effect of drying-wetting cycles act as a physiological stress for the soil microbial community and cause changes in its structure, the partial death or lysis of the microbial biomass. The mobilization of the SOM and the stabilization of the potentially mineralizable components lead to change of mineralization potential in the soil. To test the effects of different moisture regime on plant growth and soil biological properties, plot experiment with the gray forest soil including trials with plants (corn) and bare fallow was performed. Different regimes of soil moisture (conditionally optimal, relatively deficient soil moisture and repeated cycles of drying-wetting) were created. Control of soil moisture was taken every two or three days. Gas sampling was carried out using closed chambers. Soil samples were collected at the end of the pot experiment. The potentially mineralizable content of soil organic carbon (SOC) was measured by biokinetic method based on (1) aerobic incubation of soil samples under constant temperature and moisture conditions during 158 days, (2) quantitation of C-CO2, and (3) fitting of C-CO2 cumulative curve by a model of first-order kinetic. Total soil organic carbon was measured by Tyrin's wet chemical oxidation method. Permanent deficient moisture in the soil favored the preservation of potentially mineralizable SOC. Two repeated cycles of drying-wetting did not reduce the potentially mineralizable carbon content in comparison with control under optimal soil moisture during 90 days of experiment. The emission loss of C-CO2 from the soil with plants was 1.4-1.7 times higher than the decrease of potentially mineralizable SOC due to the contribution of root respiration. On the contrary, the decrease of potentially mineralized SOC in the soil without plants was 1.1-1.2 times larger than C-CO2 emissions from the soil as a result of stabilization processes. Thus, the alternation of drying-wetting cycles results in 1) the death of microbial biomass and recolonization of the soil microorganisms; 2) favors the splitting and degradation of soil aggregates, as well as the reaggregation and stabilization of aggregates; 3) contributes to the mobilization of the SOM and also 4) initiates the stabilization of the potentially mineralizable components. The effect of drying-wetting cycles is expressed not so much in the loss of the total soil organic carbon as in the degradation of the SOM quality with decreasing its mineralization potential. We can conclude that different soil moisture regimes lead to essential changes of mineralization potential in the gray forest soil. The amount of mineralization loss soil carbon via C-CO2 emission is directly associated with the decrease of potentially mineralizable carbon. Deficient moisture is a reason for temporarily sequestration of SOC potentially mineralizable under optimal moisture. This work was supported by RSF. Project number 14-14-00625
Soil Moisture and Snow Cover: Active or Passive Elements of Climate
NASA Technical Reports Server (NTRS)
Oglesby, Robert J.; Marshall, Susan; Erickson, David J., III; Robertson, Franklin R.; Roads, John O.; Arnold, James E. (Technical Monitor)
2002-01-01
A key question is the extent to which surface effects such as soil moisture and snow cover are simply passive elements or whether they can affect the evolution of climate on seasonal and longer time scales. We have constructed ensembles of predictability studies using the NCAR CCM3 in which we compared the relative roles of initial surface and atmospheric conditions over the central and western U.S. in determining the subsequent evolution of soil moisture and of snow cover. Results from simulations with realistic soil moisture anomalies indicate that internal climate variability may be the strongest factor, with some indication that the initial atmospheric state is also important. Model runs with exaggerated soil moisture reductions (near-desert conditions) showed a much larger effect, with warmer surface temperatures, reduced precipitation, and lower surface pressures; the latter indicating a response of the atmospheric circulation. These results suggest the possibility of a threshold effect in soil moisture, whereby an anomaly must be of a sufficient size before it can have a significant impact on the atmospheric circulation and climate. Results from simulations with realistic snow cover anomalies indicate that the time of year can be crucial. When introduced in late winter, these anomalies strongly affected the subsequent evolution of snow cover. When introduced in early winter, however, little or no effect is seen on the subsequent snow cover. Runs with greatly exaggerated initial snow cover indicate that the high reflectivity of snow is the most important process by which snow cover can impact climate, through lower surface temperatures and increased surface pressures. The results to date were obtained for model runs with present-day conditions. We are currently analyzing runs made with projected forcings for the 21st century to see if these results are modified in any way under likely scenarios of future climate change. An intriguing new statistical technique involving 'clustering' is developed to assist in this analysis.
Microstrip transmission line for soil moisture measurement
NASA Astrophysics Data System (ADS)
Chen, Xuemin; Li, Jing; Liang, Renyue; Sun, Yijie; Liu, C. Richard; Rogers, Richard; Claros, German
2004-12-01
Pavement life span is often affected by the amount of voids in the base and subgrade soils, especially moisture content in pavement. Most available moisture sensors are based on the capacitive sensing using planar blades. Since the planar sensor blades are fabricated on the same surface to reduce the overall size of the sensor, such structure cannot provide very high accuracy for moisture content measurement. As a consequence, a typical capacitive moisture sensor has an error in the range of 30%. A more accurate measurement is based on the time domain refelctometer (TDR) measurement. However, typical TDR system is fairly expensive equipment, very large in size, and difficult to operate, the moisture content measurement is limited. In this paper, a novel microstrip transmission line based moisture sensor is presented. This sensor uses the phase shift measurement of RF signal going through a transmission line buried in the soil to be measured. Since the amplitude of the transmission measurement is a strong function of the conductivity (loss of the media) and the imaginary part of dielectric constant, and the phase is mainly a strong function of the real part of the dielectric constant, measuring phase shift in transmission mode can directly obtain the soil moisture information. This sensor was designed and implemented. Sensor networking was devised. Both lab and field data show that this sensor is sensitive and accurate.
USDA-ARS?s Scientific Manuscript database
Climate models predict increased variability in precipitation regimes, which will likely increase frequency/duration of drought. Reductions in soil moisture affect physical and chemical characteristics of the soil habitat and can influence soil organisms such as mites and nematodes. These organisms ...
Soil Fumigation: Principles and Application Technology
Lembright, H. W.
1990-01-01
The principal soil fumigants and their order of discovery are carbon disulfide, chloropicrin, methyl bromide, 1,3-dichloropropene, ethylene dibromide, 1,2-dibromo-3-chloropropane, and methyl isothiocyanate. Biological activity of soil fumigants ranges from limited to broad spectrum. Fumigants diffuse through the continuous soil air space as gases. Physical and chemical characteristics determine diffusion rates, distribution between the soil air and moisture, and sorption onto and into the soil particles. The principal soil factors affecting the efficacy of each treatment are the size and continuity of air space, moisture, temperature, organic matter, and depth of placement. Application can be made overall with tractor injection or plow-sole, or as a row or bed treatment. Treatment for trees is best made in conjunction with tree site backhoeing. PMID:19287772
NASA Astrophysics Data System (ADS)
Hamlet, A. F.; Wood, A.; Lettenmaier, D. P.
The role of soil moisture storage in the hydrologic cycle is well understood at a funda- mental level. Antecedent conditions are known to have potentially significant effects on streamflow forecasts, especially for short (e.g., flood) lead times. For this reason, the U.S. Geological Survey defines its "water year" as extending from October through September, a time period selected because over most of the U.S., soil moisture is at a seasonal low at summer's end. The effects of carryover soil moisture storage in the Columbia River basin have usually been considered to be minimal when forecasts are made on a water year or seasonal basis. Our study demonstrates that the role of carry- over soil moisture storage can be important. Absent direct observations of ET and soil moisture that would permit a closing of the water balance from observations, we use a physically based hydrologic model to estimate the soil moisture state at the begin- ning of the forecast period (Oct 1). We then evaluate, in a self-consistent manner, the subsequent effects of interannual variations in fall soil moisture on streamflow during the subsequent spring and summer snowmelt season (April-September). We analyze the period from 1950-1999, and the subsequent effects to the seasonal water balance at The Dalles, OR for representative high, medium, and low water years. The effects of initial soil state in fall are remarkably persistent, with significant effects occurring in the summer of the following water year. For a representative low flow year (1992), the simulated variability of the soil moisture state in September produces a range of summer streamflows (April-September mean) equivalent to about 16 percent of the mean summer flows for all initial soil conditions, with analogous, but smaller, relative changes for medium and high flow years. Winter flows are also affected, and the rel- ative intensity of effects in winter and summer is variable, an effect that is probably attributable to the amount of soil recharge that occurs (or does not occur) in early fall in a particular water year. Issues relating to hydrologic model calibration and some applications to experimental long-lead forecasts in the Columbia basin are also dis- cussed.
Seasonal Parameterizations of the Tau-Omega Model Using the ComRAD Ground-Based SMAP Simulator
NASA Technical Reports Server (NTRS)
O'Neill, P.; Joseph, A.; Srivastava, P.; Cosh, M.; Lang, R.
2014-01-01
NASA's Soil Moisture Active Passive (SMAP) mission is scheduled for launch in November 2014. In the prelaunch time frame, the SMAP team has focused on improving retrieval algorithms for the various SMAP baseline data products. The SMAP passive-only soil moisture product depends on accurate parameterization of the tau-omega model to achieve the required accuracy in soil moisture retrieval. During a field experiment (APEX12) conducted in the summer of 2012 under dry conditions in Maryland, the Combined Radar/Radiometer (ComRAD) truck-based SMAP simulator collected active/passive microwave time series data at the SMAP incident angle of 40 degrees over corn and soybeans throughout the crop growth cycle. A similar experiment was conducted only over corn in 2002 under normal moist conditions. Data from these two experiments will be analyzed and compared to evaluate how changes in vegetation conditions throughout the growing season in both a drought and normal year can affect parameterizations in the tau-omega model for more accurate soil moisture retrieval.
Climate change hampers endangered species through intensified moisture-related plant stresses
NASA Astrophysics Data System (ADS)
(Ruud) Bartholomeus, R. P.; (Flip) Witte, J. P. M.; (Peter) van Bodegom, P. M.; (Jos) van Dam, J. C.; (Rien) Aerts, R.
2010-05-01
With recent climate change, extremes in meteorological conditions are forecast and observed to increase globally, and to affect vegetation composition. More prolonged dry periods will alternate with more intensive rainfall events, both within and between years, which will change soil moisture dynamics. In temperate climates, soil moisture, in concert with nutrient availability and soil acidity, is the most important environmental filter in determining local plant species composition, as it determines the availability of both oxygen and water to plant roots. These resources are indispensable for meeting the physiological demands of plants. The consequences of climate change for our natural environment are among the most pressing issues of our time. The international research community is beginning to realise that climate extremes may be more powerful drivers of vegetation change and species extinctions than slow-and-steady climatic changes, but the causal mechanisms of such changes are presently unknown. The roles of amplitudes in water availability as drivers of vegetation change have been particularly elusive owing to the lack of integration of the key variables involved. Here we show that the combined effect of increased rainfall variability, temperature and atmospheric CO2-concentration will lead to an increased variability in both wet and dry extremes in stresses faced by plants (oxygen and water stress, respectively). We simulated these plant stresses with a novel, process-based approach, incorporating in detail the interacting processes in the soil-plant-atmosphere interface. In order to quantify oxygen and water stress with causal measures, we focused on interacting meteorological, soil physical, microbial, and plant physiological processes in the soil-plant-atmosphere system. The first physiological process inhibited at high soil moisture contents is plant root respiration, i.e. oxygen consumption in the roots, which responds to increased temperatures. High soil moisture contents hamper oxygen transport from the atmosphere, through the soil - where part of the oxygen additionally disappears by soil microbial oxygen consumption - and to the root cells. Reduced respiration negatively affects the energy supply to plant metabolism. Plant transpiration, which responds to increased temperatures and atmospheric CO2-concentrations, is the first physiological process that will be inhibited by low soil moisture contents, negatively affecting both photosynthesis and cooling. As both the supply and demand of oxygen and water depend strongly on the prevailing meteorological conditions, both oxygen and water stress were calculated dynamically in time to capture climate change effects. We demonstrate that increased rainfall variability in interaction with predicted changes in temperature and CO2, affects soil moisture conditions and plant oxygen and water demands such, that both oxygen stress and water stress will intensify due to climate change. Moreover, these stresses will increasingly coincide, causing variable stress conditions. These variable stress conditions were found to decrease future habitat suitability, especially for plant species that are presently endangered. The future existence of such species is thus at risk by climate change, which has direct implications for policies to maintain endangered species, as applied by international nature management organisations (e.g. IUCN). Our integrated mechanistic analysis of two stresses combined, which has never been done so far, reveals large impacts of climate change on species extinctions and thereby on biodiversity.
NASA Technical Reports Server (NTRS)
Wang, J. R.; Shiue, J. C.; Engman, E. T.; Rusek, M.; Steinmeier, C.
1986-01-01
An experiment was conducted from an L-band SAR aboard Space Shuttle Challenger in October 1984 to study the microwave backscatter dependence on soil moisture, surface roughness, and vegetation cover. The results based on the analyses of an image obtained at 21-deg incidence angle show a positive correlatlion between scattering coefficient and soil moisture content, with a sensitivity comparable to that derived from the ground radar measurements reported by Ulaby et al. (1978). The surface roughness strongly affects the microwave backscatter. A factor of two change in the standard deviation of surface roughness height gives a corresponding change of about 8 dB in the scattering coefficient. The microwave backscatter also depends on the vegetation types. Under the dry soil conditions, the scattering coefficient is observed to change from about -24 dB for an alfalfa or lettuce field to about -17 dB for a mature corn field. These results suggest that observations with a SAR system of multiple frequencies and polarizations are required to unravel the effects of soil moisture, surface roughness, and vegetation cover.
Ecohydrologic relationships of two juniper woodlands with different precipitation regimes
NASA Astrophysics Data System (ADS)
Ochoa, C. G.; Guldan, S. J.; Deboodt, T.; Fernald, A.; Ray, G.
2015-12-01
The significant expansion of juniper (Juniperus spp.) woodlands throughout the western U.S. during the last two centuries has disrupted important ecological functions and hydrologic processes. The relationships between water and vegetation distribution are highly impacted by the ongoing shift from shrub steppe and grassland to woodland-dominated landscapes. We investigated vegetation dynamics and hydrologic processes occurring in two distinct juniper landscapes with different precipitation regimes in the Intermountain West region: A winter snow-dominated (Oregon) and a summer rain-dominated with some winter precipitation (New Mexico) landscape. Results from the Oregon site showed marginal differences (1-2%) in soil moisture in treated vs untreated watersheds throughout the dry and wet seasons. In general, soil moisture was greater in the treated watershed in both seasons. Canopy cover affected soil moisture over time. Perennial grass cover was positively correlated with changes in soil moisture, whereas juniper cover was negatively correlated with changes in soil moisture. Shallow groundwater response observed in upland and valley monitoring wells indicate there are temporary hydrologic connections between upland and valley locations during the winter precipitation season. Results from the New Mexico site provided valuable information regarding timing and intensity of monsoon-driven precipitation and the rainfall threshold (5 mm/15 min) that triggers runoff. Long-term vegetation dynamics and hydrologic processes were evaluated based on pre- and post-juniper removal (70%) in three watersheds. In general, less runoff and greater forage response was observed in the treated watersheds. During rainfall events, soil moisture was less under juniper canopy compared with inter-canopy; this difference in soil moisture was intensified during high intensity, short duration rainstorms in the summer months. We found that winter snow precipitation helped recharge soil moisture prior to plant growth in the springtime, but it did not generate streamflow. Study results provide valuable information towards understanding ecohydrologic differences and similarities of woody vegetation expansion in semiarid areas on both sides of the continental divide in the Intermountain West.
ESA's Soil Moisture dnd Ocean Salinity Mission - Contributing to Water Resource Management
NASA Astrophysics Data System (ADS)
Mecklenburg, S.; Kerr, Y. H.
2015-12-01
The Soil Moisture and Ocean Salinity (SMOS) mission, launched in November 2009, is the European Space Agency's (ESA) second Earth Explorer Opportunity mission. The scientific objectives of the SMOS mission directly respond to the need for global observations of soil moisture and ocean salinity, two key variables used in predictive hydrological, oceanographic and atmospheric models. SMOS observations also provide information on the characterisation of ice and snow covered surfaces and the sea ice effect on ocean-atmosphere heat fluxes and dynamics, which affects large-scale processes of the Earth's climate system. The focus of this paper will be on SMOS's contribution to support water resource management: SMOS surface soil moisture provides the input to derive root-zone soil moisture, which in turn provides the input for the drought index, an important monitoring prediction tool for plant available water. In addition to surface soil moisture, SMOS also provides observations on vegetation optical depth. Both parameters aid agricultural applications such as crop growth, yield forecasting and drought monitoring, and provide input for carbon and land surface modelling. SMOS data products are used in data assimilation and forecasting systems. Over land, assimilating SMOS derived information has shown to have a positive impact on applications such as NWP, stream flow forecasting and the analysis of net ecosystem exchange. Over ocean, both sea surface salinity and severe wind speed have the potential to increase the predictive skill on the seasonal and short- to medium-range forecast range. Operational users in particular in Numerical Weather Prediction and operational hydrology have put forward a requirement for soil moisture data to be available in near-real time (NRT). This has been addressed by developing a fast retrieval for a NRT level 2 soil moisture product based on Neural Networks, which will be available by autumn 2015. This paper will focus on presenting the above applications and used SMOS data products.
Soil Moisture Extremes Observed by METOP ASCAT: Was 2012 an Exceptional Year?
NASA Astrophysics Data System (ADS)
Wagner, Wolfgang; Paulik, Christoph; Hahn, Sebastian; Melzer, Thomas; Parinussa, Robert; de Jeu, Richard; Dorigo, Wouter; Chung, Daniel; Enenkel, Markus
2013-04-01
In summer 2012 the international press reported widely about the severe drought that had befallen large parts of the United States. Yet, the US drought was only one of several major droughts that occurred in 2012: Southeastern Europe, Central Asia, Brazil, India, Southern Australia and several other regions suffered from similarly dry soil conditions. This raises the question whether 2012 was an exceptionally dry year? In this presentation we will address this question by analyzing global soil moisture patterns as observed by the Advanced Scatterometer (ASCAT) flown on board of the METOP-A satellite. We firstly compare the 2012 ASCAT soil moisture data to all available ASCAT measurements acquired by the instrument since the launch of METOP-A in November 2006. Secondly, we compare the 2012 data to a long-term soil moisture data set derived by merging the ASCAT soil moisture data with other active and passive microwave soil moisture retrievals as described by Liu et al. (2012) and Wagner et al. (2012) (see also http://www.esa-soilmoisture-cci.org/). A first trend analysis of the latter long-term soil moisture data set carried out by Dorigo et al. (2012) has revealed that over the period 1988-2010 significant trends were observed over 27 % of the area covered by the data set, of which 73 % were negative (soil drying) and only 27 % were positive (soil wetting). In this presentation we will show how the inclusion of the years 2011 and 2012 affects the areal extent and strengths of these significant trends. REFERENCES Dorigo, W., R. de Jeu, D. Chung, R. Parinussa, Y. Liu, W. Wagner, D. Fernández-Prieto (2012) Evaluating global trends (1988-2010) in harmonized multi-satellite surface soil moisture, Geophysical Research Letters, 39, L18405, 1-7. Liu, Y.Y., W.A. Dorigo, R.M. Parinussa, R.A.M. de Jeu, W. Wagner, M.F. McCabe, J.P. Evans, A.I.J.M. van Dijk (2012) Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297. Wagner, W., W. Dorigo, R. de Jeu, D. Fernandez, J. Benveniste, E. Haas, M. Ertl (2012) Fusion of active and passive microwave observations to create an Essential Climate Variable data record on soil moisture, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS Annals), Volume I-7, XXII ISPRS Congress, Melbourne, Australia, 25 August-1 September 2012, 315-321.
Extended monitoring and analysis of moisture temperature data : [executive summary].
DOT National Transportation Integrated Search
2001-01-01
The performance of asphalt concrete pavements is in part affected by the seasonal variations of the resilient modulus of the AC layer and of the subgrade soil. To determine the variation of these parameters throughout Ohio, nine moisture-temperature-...
Song, Xiao Lin; Zhao, Xi Ning; Gao, Xiao Dong; Wu, Pu Te; Ma, Wen; Yao, Jie; Jiang, Xiao Li; Zhang, Wei
2017-11-01
Water scarcity is a critical factor influencing rain-fed agricultural production on the Loess Plateau, and the exploitation of rainwater is an effective avenue to alleviate water scarcity in this area. This study was conducted to investigate the spatial and temporal distribution of soil moisture in the 0-300 cm under a 21-year-old apple orchard with the rainwater collection and infiltration (RWCI) system by using a time domain reflectometer (TDR) probe on the Loess Plateau. The results showed that there was a low soil moisture zone in the 40-80 cm under the CK, and the RWCI system significantly increased soil moisture in this depth interval. Over this depth, the annual average soil moisture under RWCI 40 , RWCI 60 and RWCI 80 was 39.2%, 47.2% and 29.1% higher than that of bare slope (BS) and 75.3%, 85.4% and 62.7% higher than that of CK, respectively. The maximum infiltration depth of water under RWCI 40 , RWCI 60 and RWCI 80 was 80 cm, 120 cm and 180 cm, respectively, and the soil moisture in the 0-60, 0-100 and 0-120 cm was more affected by RWCI 40 , RWCI 60 and RWCI 80 , respectively. Over the whole growth period of apple tree, the maximum value of soil moisture content in the 0-300 cm existed in the RWCI 80 treatment, followed by the RWCI 40 and RWCI 60 treatments. Overall, the RWCI system is an effective meaning of transforming rainwater to available water resources and realizing efficient use of agricultural water on the Loess Plateau.
Danyagri, Gabriel; Dang, Qing-Lai
2013-01-01
Global climate change is expected to affect how plants respond to their physical and biological environments. In this study, we examined the effects of elevated CO2 ([CO2]) and low soil moisture on the physiological responses of mountain maple (Acer spicatum L.) seedlings to light availability. The seedlings were grown at ambient (392 µmol mol(-1)) and elevated (784 µmol mol(-1)) [CO2], low and high soil moisture (M) regimes, at high light (100%) and low light (30%) in the greenhouse for one growing season. We measured net photosynthesis (A), stomatal conductance (g s), instantaneous water use efficiency (IWUE), maximum rate of carboxylation (V cmax), rate of photosynthetic electron transport (J), triose phosphate utilization (TPU)), leaf respiration (R d), light compensation point (LCP) and mid-day shoot water potential (Ψx). A and g s did not show significant responses to light treatment in seedlings grown at low soil moisture treatment, but the high light significantly decreased the C i/C a in those seedlings. IWUE was significantly higher in the elevated compared with the ambient [CO2], and the effect was greater at high than the low light treatment. LCP did not respond to the soil moisture treatments when seedlings were grown in high light under both [CO2]. The low soil moisture significantly reduced Ψx but had no significant effect on the responses of other physiological traits to light or [CO2]. These results suggest that as the atmospheric [CO2] rises, the physiological performance of mountain maple seedlings in high light environments may be enhanced, particularly when soil moisture conditions are favourable.
Danyagri, Gabriel; Dang, Qing-Lai
2013-01-01
Global climate change is expected to affect how plants respond to their physical and biological environments. In this study, we examined the effects of elevated CO2 ([CO2]) and low soil moisture on the physiological responses of mountain maple (Acer spicatum L.) seedlings to light availability. The seedlings were grown at ambient (392 µmol mol−1) and elevated (784 µmol mol−1) [CO2], low and high soil moisture (M) regimes, at high light (100%) and low light (30%) in the greenhouse for one growing season. We measured net photosynthesis (A), stomatal conductance (g s), instantaneous water use efficiency (IWUE), maximum rate of carboxylation (V cmax), rate of photosynthetic electron transport (J), triose phosphate utilization (TPU)), leaf respiration (R d), light compensation point (LCP) and mid-day shoot water potential (Ψx). A and g s did not show significant responses to light treatment in seedlings grown at low soil moisture treatment, but the high light significantly decreased the C i/C a in those seedlings. IWUE was significantly higher in the elevated compared with the ambient [CO2], and the effect was greater at high than the low light treatment. LCP did not respond to the soil moisture treatments when seedlings were grown in high light under both [CO2]. The low soil moisture significantly reduced Ψx but had no significant effect on the responses of other physiological traits to light or [CO2]. These results suggest that as the atmospheric [CO2] rises, the physiological performance of mountain maple seedlings in high light environments may be enhanced, particularly when soil moisture conditions are favourable. PMID:24146894
Evaluation of Assimilated SMOS Soil Moisture Data for US Cropland Soil Moisture Monitoring
NASA Technical Reports Server (NTRS)
Yang, Zhengwei; Sherstha, Ranjay; Crow, Wade; Bolten, John; Mladenova, Iva; Yu, Genong; Di, Liping
2016-01-01
Remotely sensed soil moisture data can provide timely, objective and quantitative crop soil moisture information with broad geospatial coverage and sufficiently high resolution observations collected throughout the growing season. This paper evaluates the feasibility of using the assimilated ESA Soil Moisture Ocean Salinity (SMOS)Mission L-band passive microwave data for operational US cropland soil surface moisture monitoring. The assimilated SMOS soil moisture data are first categorized to match with the United States Department of Agriculture (USDA)National Agricultural Statistics Service (NASS) survey based weekly soil moisture observation data, which are ordinal. The categorized assimilated SMOS soil moisture data are compared with NASSs survey-based weekly soil moisture data for consistency and robustness using visual assessment and rank correlation. Preliminary results indicate that the assimilated SMOS soil moisture data highly co-vary with NASS field observations across a large geographic area. Therefore, SMOS data have great potential for US operational cropland soil moisture monitoring.
NASA Astrophysics Data System (ADS)
Bouda, Martin; Saiers, James E.
2017-12-01
Root system architecture (RSA) can significantly affect plant access to water, total transpiration, as well as its partitioning by soil depth, with implications for surface heat, water, and carbon budgets. Despite recent advances in land surface model (LSM) descriptions of plant hydraulics, descriptions of RSA have not been included because of their three-dimensional complexity, which makes them generally too computationally costly. Here we demonstrate a new, process-based 1D layered model that captures the dynamic shifts in water potential gradients of 3D RSA under different soil moisture conditions: the RSA stencil. Using root systems calibrated to the rooting profiles of four plant functional types (PFT) of the Community Land Model, we show that the RSA stencil predicts plant water potentials within 2% to the outputs of a full 3D model, under the same assumptions on soil moisture heterogeneity, despite its trivial computational cost, resulting in improved predictions of water uptake and soil moisture compared to a model without RSA in a transient simulation. Our results suggest that LSM predictions of soil moisture dynamics and dependent variables can be improved by the implementation of this model, calibrated for individual PFTs using field observations.
Uptake and translocation of imidacloprid, clothianidin and flupyradifurone in seed-treated soybeans.
Stamm, Mitchell D; Heng-Moss, Tiffany M; Baxendale, Frederick P; Siegfried, Blair D; Blankenship, Erin E; Nauen, Ralf
2016-06-01
Seed treatment insecticides have become a popular management option for early-season insect control. This study investigated the total uptake and translocation of seed-applied [(14) C]imidacloprid, [(14) C]clothianidin and [(14) C]flupyradifurone into different plant parts in three soybean vegetative stages (VC, V1 and V2). The effects of soil moisture stress on insecticide uptake and translocation were also assessed among treatments. We hypothesized that (1) uptake and translocation would be different among the insecticides owing to differences in water solubility, and (2) moisture stress would increase insecticide uptake and translocation. Uptake and translocation did not follow a clear trend in the three vegetative stages. Initially, flupyradifurone uptake was greater than clothianidin uptake in VC soybeans. In V1 soybeans, differences in uptake among the three insecticides were not apparent and unaffected by soil moisture stress. Clothianidin was negatively affected by soil moisture stress in V2 soybeans, while imidacloprid and flupyradifurone were unaffected. Specifically, soil moisture stress had a positive effect on the distribution of flupyradifurone in leaves. This was not observed with the neonicotinoids. This study enhances our understanding of the uptake and distribution of insecticides used as seed treatments in soybean. The uptake and translocation of these insecticides differed in response to soil moisture stress. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.
Zhang, Yong; Dong, Shikui; Gao, Qingzhu; Liu, Shiliang; Zhou, Huakun; Ganjurjav, Hasbagan; Wang, Xuexia
2016-08-15
Alpine ecosystems are known to be sensitive to climate change and human disturbances. However, the knowledge about the changes of their underground microbial communities is inadequate. We explored the diversity and structure of soil bacterial and fungal communities using Ilumina MiSeq sequencing in native alpine grasslands (i.e. the alpine meadow, alpine steppe) and cultivated grassland of the Qinghai-Tibetan Plateau (QTP) under three-year treatments of overgrazing, warming and enhanced rainfall. Enhanced rainfall rather than warming significantly reduced soil microbial diversity in native alpine grasslands. Variable warming significantly reduced it in the cultivated grassland. Over 20% and 40% variations of microbial diversity could be explained by soil nutrients and moisture in the alpine meadow and cultivated grassland, separately. Soil microbial communities could be clustered into different groups according to different treatments in the alpine meadow and cultivated grassland. For the alpine steppe, with the lowest soil nutrients and moistures, <10% variations of microbial diversity was explained by soil properties; and the soil microbial communities among different treatments were similar. The soil microbial community in the cultivated grassland was varied from it in native grasslands. Over 50% variations of soil microbial communities among different treatments were explained by soil nutrients and moisture in each grassland type. Our results suggest that climate change and human activities strongly affected soil microbial communities by changing soil nutrients and moistures in alpine grassland ecosystems. Copyright © 2016 Elsevier B.V. All rights reserved.
Soil Moisture and Snow Cover: Active or Passive Elements of Climate?
NASA Technical Reports Server (NTRS)
Oglesby, Robert J.; Marshall, Susan; Robertson, Franklin R.; Roads, John O.; Arnold, James E. (Technical Monitor)
2001-01-01
A key question in the study of the hydrologic cycle is the extent to which surface effects such as soil moisture and snow cover are simply passive elements or whether they can affect the evolution of climate on seasonal and longer time scales. We have constructed ensembles of predictability studies using the NCAR CCM3 in which we compared the relative roles of initial surface and atmospheric conditions over the central and western U.S. GAPP region in determining the subsequent evolution of soil moisture and of snow cover. We have also made sensitivity studies with exaggerated soil moisture and snow cover anomalies in order to determine the physical processes that may be important. Results from simulations with realistic soil moisture anomalies indicate that internal climate variability may be the strongest factor, with some indication that the initial atmospheric state is also important. The initial state of soil moisture does not appear important, a result that held whether simulations were started in late winter or late spring. Model runs with exaggerated soil moisture reductions (near-desert conditions) showed a much larger effect, with warmer surface temperatures, reduced precipitation, and lower surface pressures; the latter indicating a response of the atmospheric circulation. These results suggest the possibility of a threshold effect in soil moisture, whereby an anomaly must be of a sufficient size before it can have a significant impact on the atmospheric circulation and hence climate. Results from simulations with realistic snow cover anomalies indicate that the time of year can be crucial. When introduced in late winter, these anomalies strongly affected the subsequent evolution of snow cover. When introduced in early winter, however, little or no effect is seen on the subsequent snow cover. Runs with greatly exaggerated initial snow cover indicate that the high reflectivity of snow is the most important process by which snow cover can impact climate, through lower surface temperatures and increased surface pressures. In early winter, the amount of solar radiation is very small and so this albedo, effect is inconsequential while in late winter, with the sun higher in the sky and period of daylight longer, the effect is much stronger. The results to date were obtained for model runs with present-day conditions. We are currently analyzing runs made with projected forcings for the 21st century to see if these results are modified in any way under likely scenarios of future climate change.
Virginia C. Meyer
2002-01-01
The lack of valley oak (Quercus lobata Neé) regeneration throughout much of its historical range appears to be related to both habitat destruction and soil moisture availability. The water relations, growth and survival of greenhouse potted seedlings, field-planted and natural seedlings were monitored through the growing season, 1989. The age...
NASA Technical Reports Server (NTRS)
Burke, H. H. K.
1980-01-01
Three tasks related to soil moisture sensing at microwave wavelengths were undertaken: (1) analysis of data at L, X and K sub 21 band wavelengths over bare and vegetated fields from the 1975 NASA sponsored flight experiment over Phoenix, Arizona; (2) modeling of vegetation canopy at microwave wavelengths taking into consideration both absorption and volume scattering effects; and (3) investigation of overall atmospheric effects at microwave wavelengths that can affect soil moisture retrieval. Data for both bare and vegetated fields are found to agree well with theoretical estimates. It is observed that the retrieval of surface and near surface soil moisture information is feasible through multi-spectral and multi-temporal analysis. It is also established that at long wavelengths, which are optimal for surface sensing, atmospheric effects are generally minimal. At shorter wavelengths, which are optimal for atmosheric retrieval, the background surface properties are also established.
Impacts of single and recurrent wildfires on topsoil moisture regime
NASA Astrophysics Data System (ADS)
González-Pelayo, Oscar; Malvar, Maruxa; van den Elsen, Erik; Hosseini, Mohammadreza; Coelho, Celeste; Ritsema, Coen; Bautista, Susana; Keizer, Jacob
2017-04-01
The increasing fire recurrence on forest in the Mediterranean basin is well-established by future climate scenarios due to land use changes and climate predictions. By this, shifts on mature pine woodlands to shrub rangelands are of major importance on forest ecosystems buffer functions, since historical patterns of established vegetation help to recover from fire disturbances. This fact, together with the predicted expansion of the drought periods, will affect feedback processes of vegetation patterns since water availability on these seasons are driven by post-fire local soil properties. Although fire impacts of soil properties and water availability has been widely studied using the fire severity as the main factor, little research is developed on post-fire soil moisture patterns, including the fire recurrence as a key explanatory variable. The following research investigated, in pine woodlands of north central Portugal, the short-term consequences (one year after a fire) of wildfire recurrence on the surface soil moisture content (SMC) and on effective soil water (SWEFF, parameter that includes actual daily soil moisture, soil field capacity-FC and permanent wilting point-PWP). The study set-up includes analyses at two fire recurrence scenarios (1x- and 4x-burnt since 1975), at a patch level (shrub patch/interpatch) and at two soil depths (2.5 and 7.5 cm) in a nested approach. Understanding how fire recurrence affects water in soil over space and time is the main goal of this research. The use of soil moisture sensors in a nested approach, the rainfall features and analyses on basic soil properties as soil organic matter, texture, bulk density, pF curves, soil water repellency and soil surface components will establish which factors has the largest role in controlling soil moisture behavior. Main results displayed, in a seasonal and yearly basis, no differences on SMC as increasing fire recurrence (1x- vs 4x-burnt) neither between patch/interpatch microsites at both two soil depths. Otherwise, in a yearly basis and during soil drying cycles, it was found less effective water on soil at the surface layers of the 4x-burnt and between shrub interpatches, based on the worst soil hydrological conditions (PWP) and the increasing percentage of abiotic soil surface components as increasing fire recurrence. Our results suggest that the inclusion of soil hydrological properties, as pF-curves, on the soil water effectiveness calculation seems to be a better indicator of water availability that volumetric SM per se. Otherwise, the use of a nested approach methodology, stresses how fire recurrence, expected increases in the summer drought spells and, the increasing dominance of abiotic soil surface components, are the factors that much influence soil eco-hydrological functioning in fire prone ecosystems. Furthermore, this research point out how post-fire soil structural quality into plant interpatches could provoke looping feedback processes triggering desertification situations also in humid Mediterranean forestlands.
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).
Code of Federal Regulations, 2014 CFR
2014-07-01
... of the tank system will be in contact with the soil or with water, a determination by a corrosion expert of: (1) Factors affecting the potential for corrosion, such as: (i) Soil moisture content. (ii) Soil pH. (iii) Soil sulfides level. (iv) Soil resistivity. (v) Structure to soil potential. (vi...
Code of Federal Regulations, 2010 CFR
2010-07-01
... of the tank system will be in contact with the soil or with water, a determination by a corrosion expert of: (1) Factors affecting the potential for corrosion, such as: (i) Soil moisture content. (ii) Soil pH. (iii) Soil sulfides level. (iv) Soil resistivity. (v) Structure to soil potential. (vi...
Code of Federal Regulations, 2012 CFR
2012-07-01
... of the tank system will be in contact with the soil or with water, a determination by a corrosion expert of: (1) Factors affecting the potential for corrosion, such as: (i) Soil moisture content. (ii) Soil pH. (iii) Soil sulfides level. (iv) Soil resistivity. (v) Structure to soil potential. (vi...
Code of Federal Regulations, 2013 CFR
2013-07-01
... of the tank system will be in contact with the soil or with water, a determination by a corrosion expert of: (1) Factors affecting the potential for corrosion, such as: (i) Soil moisture content. (ii) Soil pH. (iii) Soil sulfides level. (iv) Soil resistivity. (v) Structure to soil potential. (vi...
Code of Federal Regulations, 2011 CFR
2011-07-01
... of the tank system will be in contact with the soil or with water, a determination by a corrosion expert of: (1) Factors affecting the potential for corrosion, such as: (i) Soil moisture content. (ii) Soil pH. (iii) Soil sulfides level. (iv) Soil resistivity. (v) Structure to soil potential. (vi...
Zhang, Xinfang; Xu, Shijian; Li, Changming; Zhao, Lin; Feng, Huyuan; Yue, Guangyang; Ren, Zhengwei; Cheng, Guogdong
2014-01-01
In the Tibetan permafrost region, vegetation types and soil properties have been affected by permafrost degradation, but little is known about the corresponding patterns of their soil microbial communities. Thus, we analyzed the effects of vegetation types and their covariant soil properties on bacterial and fungal community structure and membership and bacterial community-level physiological patterns. Pyrosequencing and Biolog EcoPlates were used to analyze 19 permafrost-affected soil samples from four principal vegetation types: swamp meadow (SM), meadow (M), steppe (S) and desert steppe (DS). Proteobacteria, Acidobacteria, Bacteroidetes and Actinobacteria dominated bacterial communities and the main fungal phyla were Ascomycota, Basidiomycota and Mucoromycotina. The ratios of Proteobacteria/Acidobacteria decreased in the order: SM>M>S>DS, whereas the Ascomycota/Basidiomycota ratios increased. The distributions of carbon and nitrogen cycling bacterial genera detected were related to soil properties. The bacterial communities in SM/M soils degraded amines/amino acids very rapidly, while polymers were degraded rapidly by S/DS communities. UniFrac analysis of bacterial communities detected differences among vegetation types. The fungal UniFrac community patterns of SM differed from the others. Redundancy analysis showed that the carbon/nitrogen ratio had the main effect on bacteria community structures and their diversity in alkaline soil, whereas soil moisture was mainly responsible for structuring fungal communities. Thus, microbial communities and their functioning are probably affected by soil environmental change in response to permafrost degradation. Copyright © 2014 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.
NASA Astrophysics Data System (ADS)
Gorobtsova, O. N.; Khezheva, F. V.; Uligova, T. S.; Tembotov, R. Kh.
2015-03-01
The biochemical properties inherent to the main types of automorphic soils developed in different bioclimatic conditions of Elbrus and Terek variants of the vertical zonality within Kabardino-Balkaria were compared. The natural-climatic conditions of these variants noticeably affect the soil cover pattern. The ratio of the oxidase and hydrolase activities is sensitive to the moisture conditions in which these soils are formed. The redox processes are more active in drier conditions, whereas hydrolytic processes are more active under higher moisture. The level of the biological activity of the automorphic soils is estimated using the integral index of the ecological-biological soil status.
NASA Astrophysics Data System (ADS)
Peddinti, S. R.; Kbvn, D. P.; Ranjan, S.; Suradhaniwar, S.; J, P. A.; R M, G.
2015-12-01
Vidarbha region in Maharashtra, India (home for mandarin Orange) experience severe climatic uncertainties resulting in crop failure. Phytopthora are the soil-borne fungal species that accumulate in the presence of moisture, and attack the root / trunk system of Orange trees at any stage. A scientific understanding of soil-moisture-disease relations within the active root zone under different climatic, irrigation, and crop cycle conditions can help in practicing management activities for improved crop yield. In this study, we developed a protocol for performing 3-D time-lapse electrical resistivity tomography (ERT) at micro scale resolution to monitor the changes in resistivity distribution within the root zone of Orange trees. A total of 40 electrodes, forming a grid of 3.5 m x 2 m around each Orange tree were used in ERT survey with gradient and Wenner configurations. A laboratory test on un-disturbed soil samples of the region was performed to plot the variation of electrical conductivity with saturation. Curve fitting techniques were applied to get the modified Archie's model parameters. The calibrated model was further applied to generate the 3-D soil moisture profiles of the study area. The point estimates of soil moisture were validated using TDR probe measurements at 3 different depths (10, 20, and 40 cm) near to the root zone. In order to understand the effect of soil-water relations on plant-disease relations, we performed ERT analysis at two locations, one at healthy and other at Phytopthora affected Orange tree during the crop cycle, under dry and irrigated conditions. The degree to which an Orange tree is affected by Phytopthora under each condition is evaluated using 'grading scale' approach following visual inspection of the canopy features. Spatial-temporal distribution of moisture profiles is co-related with grading scales to comment on the effect of climatic and irrigation scenarios on the degree and intensity of crop disease caused by Phytopthora.
NASA Astrophysics Data System (ADS)
Chen, Weijing; Huang, Chunlin; Shen, Huanfeng; Wang, Weizhen
2016-04-01
The optimal estimation of hydrothermal conditions in irrigation field is restricted by the deficiency of accurate irrigation information (when and how much to irrigate). However, the accurate estimation of soil moisture and temperature profile and surface turbulent fluxes are crucial to agriculture and water management in irrigated field. In the framework of land surface model, soil temperature is a function of soil moisture - subsurface moisture influences the heat conductivity at the interface of layers and the heat storage in different layers. In addition, soil temperature determines the phase of soil water content with the transformation between frozen and unfrozen. Furthermore, surface temperature affects the partitioning of incoming radiant energy into ground (sensible and latent heat flux), as a consequence changes the delivery of soil moisture and temperature. Given the internal positive interaction lying in these variables, we attempt to retrieve the accurate estimation of soil moisture and temperature profile via assimilating the observations from the surface under unknown irrigation. To resolve the input uncertainty of imprecise irrigation quantity, original EnKS is implemented with inflation and localization (referred to as ESIL) aiming at solving the underestimation of the background error matrix and the extension of observation information from the top soil to the bottom. EnKS applied in this study includes the states in different time points which tightly connect with adjacent ones. However, this kind of relationship gradually vanishes along with the increase of time interval. Thus, the localization is also employed to readjust temporal scale impact between states and filter out redundant or invalid correlation. Considering the parameter uncertainty which easily causes the systematic deviation of model states, two parallel filters are designed to recursively estimate both states and parameters. The study area consists of irrigated farmland and is located in an artificial oasis in the semi-arid region of northwestern China. Land surface temperature (LST) and soil volumetric water content (SVW) at first layer measured at Daman station are taken as observations in the framework of data assimilation. The study demonstrates the feasibility of ESIL in improving the soil moisture and temperature profile under unknown irrigation. ESIL promotes the coefficient correlation with in-situ measurements for soil moisture and temperature at first layer from 0.3421 and 0.7027 (ensemble simulation) to 0.8767 and 0.8304 meanwhile all the RMSE of soil moisture and temperature in deeper layers dramatically decrease more than 40 percent in different degree. To verify the reliability of ESIL in practical application, thereby promoting the utilization of satellite data, we test ESIL with varying observation internal interval and standard deviation. As a consequence, ESIL shows stabilized and promising effectiveness in soil moisture and soil temperature estimation.
Moment Analysis Characterizing Water Flow in Repellent Soils from On- and Sub-Surface Point Sources
NASA Astrophysics Data System (ADS)
Xiong, Yunwu; Furman, Alex; Wallach, Rony
2010-05-01
Water repellency has a significant impact on water flow patterns in the soil profile. Flow tends to become unstable in such soils, which affects the water availability to plants and subsurface hydrology. In this paper, water flow in repellent soils was experimentally studied using the light reflection method. The transient 2D moisture profiles were monitored by CCD camera for tested soils packed in a transparent flow chamber. Water infiltration experiments and subsequent redistribution from on-surface and subsurface point sources with different flow rates were conducted for two soils of different repellency degrees as well as for wettable soil. We used spatio-statistical analysis (moments) to characterize the flow patterns. The zeroth moment is related to the total volume of water inside the moisture plume, and the first and second moments are affinitive to the center of mass and spatial variances of the moisture plume, respectively. The experimental results demonstrate that both the general shape and size of the wetting plume and the moisture distribution within the plume for the repellent soils are significantly different from that for the wettable soil. The wetting plume of the repellent soils is smaller, narrower, and longer (finger-like) than that of the wettable soil compared with that for the wettable soil that tended to roundness. Compared to the wettable soil, where the soil water content decreases radially from the source, moisture content for the water-repellent soils is higher, relatively uniform horizontally and gradually increases with depth (saturation overshoot), indicating that flow tends to become unstable. Ellipses, defined around the mass center and whose semi-axes represented a particular number of spatial variances, were successfully used to simulate the spatial and temporal variation of the moisture distribution in the soil profiles. Cumulative probability functions were defined for the water enclosed in these ellipses. Practically identical cumulative probability functions (beta distribution) were obtained for all soils, all source types, and flow rates. Further, same distributions were obtained for the infiltration and redistribution processes. This attractive result demonstrates the competence and advantage of the moment analysis method.
Moisture controls decomposition rate in thawing tundra
C.E. Hicks-Pries; E.A.G. Schuur; S.M. Natali; J.G. Vogel
2013-01-01
Permafrost thaw can affect decomposition rates by changing environmental conditions and litter quality. As permafrost thaws, soils warm and thermokarst (ground subsidence) features form, causing some areas to become wetter while other areas become drier. We used a common substrate to measure how permafrost thaw affects decomposition rates in the surface soil in a...
Uncertainty Assessment of Space-Borne Passive Soil Moisture Retrievals
NASA Technical Reports Server (NTRS)
Quets, Jan; De Lannoy, Gabrielle; Reichle, Rolf; Cosh, Michael; van der Schalie, Robin; Wigneron, Jean-Pierre
2017-01-01
The uncertainty associated with passive soil moisture retrieval is hard to quantify, and known to be underlain by various, diverse, and complex causes. Factors affecting space-borne retrieved soil moisture estimation include: (i) the optimization or inversion method applied to the radiative transfer model (RTM), such as e.g. the Single Channel Algorithm (SCA), or the Land Parameter Retrieval Model (LPRM), (ii) the selection of the observed brightness temperatures (Tbs), e.g. polarization and incidence angle, (iii) the definition of the cost function and the impact of prior information in it, and (iv) the RTM parameterization (e.g. parameterizations officially used by the SMOS L2 and SMAP L2 retrieval products, ECMWF-based SMOS assimilation product, SMAP L4 assimilation product, and perturbations from those configurations). This study aims at disentangling the relative importance of the above-mentioned sources of uncertainty, by carrying out soil moisture retrieval experiments, using SMOS Tb observations in different settings, of which some are mentioned above. The ensemble uncertainties are evaluated at 11 reference CalVal sites, over a time period of more than 5 years. These experimental retrievals were inter-compared, and further confronted with in situ soil moisture measurements and operational SMOS L2 retrievals, using commonly used skill metrics to quantify the temporal uncertainty in the retrievals.
Remote Sensing for Agriculture, Ecosystems and Hydrology III
NASA Technical Reports Server (NTRS)
Engman, Edwin T.
1999-01-01
The science need for remotely sensed soil moisture has been well established in the hydrologic, climate change and weather forecasting communities. In spite of this well documented science need there are currently no satellite missions flying or funded to make this very important geophysical measurement. There have been a number of experimental aircraft programs that have demonstrated the feasibility of using long wave microwave sensors for estimating soil moisture. Unfortunately, this science driver, soil moisture, imposes very difficult technical requirements for a satellite sensor system. Global soil moisture is driven by a spatial resolution on the order of 20 to 30 km and measurements need to be taken every two to three days to be useful to the science community. The principal sensor to accomplish the soil moisture measurements is an L- band passive microwave radiometer and achieving the spatial and temporal requirements requires a very large antenna. This paper describes the several alternatives to solve the very large antenna challenge and still meet the radiometer sensitivity requirement. The paper also discusses the alternatives considered to obtain the necessary ancillary data for characterizing the surface roughness, the surface temperature and the attenuation affects of vegetation needed to derive the geophysical parameter. Finally, the paper discusses proposed missions and how well they will meet the science requirements.
Influence of Soil Heterogeneity on Mesoscale Land Surface Fluxes During Washita '92
NASA Technical Reports Server (NTRS)
Jasinski, Michael F.; Jin, Hao
1998-01-01
The influence of soil heterogeneity on the partitioning of mesoscale land surface energy fluxes at diurnal time scales is investigated over a 10(exp 6) sq km domain centered on the Little Washita Basin, Oklahoma, for the period June 10 - 18, 1992. The sensitivity study is carried out using MM5/PLACE, the Penn State/NCAR MM5 model enhanced with the Parameterization for Land-Atmosphere-Cloud Exchange or PLACE. PLACE is a one-dimensional land surface model possessing detailed plant and soil water physics algorithms, multiple soil layers, and the capacity to model subgrid heterogeneity. A series of 12-hour simulations were conducted with identical atmospheric initialization and land surface characterization but with different initial soil moisture and texture. A comparison then was made of the simulated land surface energy flux fields, the partitioning of net radiation into latent and sensible heat, and the soil moisture fields. Results indicate that heterogeneity in both soil moisture and texture affects the spatial distribution and partitioning of mesoscale energy balance. Spatial averaging results in an overprediction of latent heat flux, and an underestimation of sensible heat flux. In addition to the primary focus on the partitioning of the land surface energy, the modeling effort provided an opportunity to examine the issue of initializing the soil moisture fields for coupled three-dimensional models. For the present case, the initial soil moisture and temperature were determined from off-line modeling using PLACE at each grid box, driven with a combination of observed and assimilated data fields.
2015-16 ENSO Drove Tropical Soil Moisture Dynamics and Methane Fluxes
NASA Astrophysics Data System (ADS)
Aronson, E. L.; Dierick, D.; Botthoff, J.; Swanson, A. C.; Johnson, R. F.; Allen, M. F.
2017-12-01
The El Niño/Southern Oscillation Event (ENSO) cycle drives large-scale climatic trends globally. Within the new world tropics, El Niño brings dryer weather than the counterpart La Niña. Atmospheric methane growth rates have shown extreme variability over the past three decades. One proposed driver is the proportion of tropical land surface saturated, affecting methane production or consumption. We measured methane flux bimonthly through the transition of 2015-16 ENSO. The date of measurement, across El Niño and La Niña within the typical "rainy" and "dry" seasons, to be the most significant driver of methane flux. Soil moisture varied across this time period, and regulated methane flux. During the strong El Niño, extreme dry soil conditions occurred in a typical "rainy" season month reducing soil moisture. Wetter than usual soil conditions appeared during the "rainy" season month of the moderate La Niña. The dry El Niño soils corresponded to greater methane consumption by tropical forest soils, and a reduced local atmospheric column methane concentration. Conversely, the wet La Niña soils had lower methane consumption and higher local atmospheric column methane concentrations. The ENSO cycle is a strong driver of tropical terrestrial and wetland soil moisture conditions, and can regulate global atmospheric methane dynamics.
Conceptualizing the self organization of cloud cells, cold pools and soil moisture
NASA Astrophysics Data System (ADS)
Henneberg, O.; Härter, J. O. M.
2017-12-01
Convective-type cloud is the cause of extreme, short-duration precipitation, challenging weather forecasting and climate modeling. Such extremes are ultimately tied to the uneven redistribution of water in the course of convective self organization and possibly the interaction between clouds [1]. Over land, moisture is organized through: cloud cells, cold pools, and the land surface. Each of these generally capture and release moisture at different rates, e.g. cold pools form quickly but dissipate slowly. Such distinct timescales have implications for the emergent dynamics.Incorporating such distinct time scales, we here present a conceptual model for the spatio-temporal self organization within the diurnal cycle of convection and describe the possible role of soil moisture memory in serving as a predisposition for extremes.We bolster our findings by high resolution, large eddy simulations: Sensible and latent heat fluxes, which are determined by the soil moisture content, can influence the stability of the atmosphere. The onset of initial precipitation is affected by such heat release, which in turn is modified by previous precipitation. Starting from static heat sources, we quantify how their spatial distribution affects the self organization and thus onset, duration and strength of precipitation events in an idealized model setup. Furthermore, an extended model setup with inhomogeneous, self organized distributions of latent and sensible heat fluxes is used to contrast how emergent soil moisture patterns impact on the selforganization structure of convection. Our findings may have implications for the role of land use changes regarding the development of extreme convective precipitation.Reference[1] Moseley et al. (2016) "Intensification of convective extremes driven by cloud-cloud interaction", Nature Geosc. , 9, 748-752
NASA Astrophysics Data System (ADS)
Zhang, Y.; Guo, S.; Zhao, M.; Du, L.; Li, R.; Jiang, J.; Wang, R.; Li, N.
2015-01-01
Temperature sensitivity of SOC mineralization (Q10) determines how strong the feedback from global warming may be on the atmospheric CO2 concentration, thus understanding the factors influencing the interannual variation in Q10 is important to accurately estimate the local soil carbon cycle. In situ SOC mineralization was measured using an automated CO2 flux system (Li-8100) in long-term bare fallow soil in the Loess Plateau (35° 12' N, 107° 40' E) in Changwu, Shaanxi, China form 2008 to 2013. The results showed that the annual cumulative SOC mineralization ranged from 226 to 298 g C m-2 y-1 (mean =253 g C m-2 y-1; CV =13%), annual Q10 ranged from 1.48 to 1.94 (mean =1.70; CV =10%), and annual soil moisture content ranged from 38.6 to 50.7% WFPS (mean =43.8% WFPS; CV =11%), which were mainly affected by the frequency and distribution of precipitation. Annual Q10 showed a negative quadratic correlation with soil moisture. In conclusion, understanding of the relationships between interannual variation in Q10 of SOC mineralization, soil moisture and precipitation is important to accurately estimate the local carbon cycle, especially under the changing climate.
Zeolite Soil Application Method Affects Inorganic Nitrogen, Moisture, and Corn Growth
USDA-ARS?s Scientific Manuscript database
Adoption of new management techniques which improve soil water storage and soil nitrogen plant availability yet limit nitrogen leaching may help improve environmental quality. A benchtop study was conducted to determine the influence of a single urea fertilizer rate (224 kilograms of Nitrogen per ...
DOT National Transportation Integrated Search
2001-09-01
The performance of asphalt concrete pavements is in part affected by the seasonal variations of the resilient modulus of the AC layer and of the subgrade soil. To determine the variation of these parameters throughout Ohio, seven moisture-temperature...
DOT National Transportation Integrated Search
2001-09-01
The performance of asphalt concrete pavements is in part affected by the seasonal variations of the resilient modulus of the AC layer and of the subgrade soil. To determine the variation of these parameters throughout Ohio, seven moisture-temperature...
NASA Astrophysics Data System (ADS)
Tromp-van Meerveld, I.; McDonnell, J.
2009-05-01
We present an assessment of electromagnetic induction (EM) as a potential rapid and non-invasive method to map soil moisture patterns at the Panola (GA, USA) hillslope. We address the following questions regarding the applicability of EM measurements for hillslope hydrological investigations: (1) Can EM be used for soil moisture measurements in areas with shallow soils?; (2) Can EM represent the temporal and spatial patterns of soil moisture throughout the year?; and (3) can multiple frequencies be used to extract additional information content from the EM approach and explain the depth profile of soil moisture? We found that the apparent conductivity measured with the multi-frequency GEM-300 was linearly related to soil moisture measured with an Aqua-pro capacitance sensor below a threshold conductivity and represented the temporal patterns in soil moisture well. During spring rainfall events that wetted only the surface soil layers the apparent conductivity measurements explained the soil moisture dynamics at depth better than the surface soil moisture dynamics. All four EM frequencies (7290, 9090, 11250, and 14010 Hz) were highly correlated and linearly related to each other and could be used to predict soil moisture. This limited our ability to use the four different EM frequencies to obtain a soil moisture profile with depth. The apparent conductivity patterns represented the observed spatial soil moisture patterns well when the individually fitted relationships between measured soil moisture and apparent conductivity were used for each measurement point. However, when the same (master) relationship was used for all measurement locations, the soil moisture patterns were smoothed and did not resemble the observed soil moisture patterns very well. In addition, the range in calculated soil moisture values was reduced compared to observed soil moisture. Part of the smoothing was likely due to the much larger measurement area of the GEM-300 compared to the Aqua-pro soil moisture measurements.
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.
Temperature and moisture effects on greenhouse gas emissions from deep active-layer boreal soils
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bond-Lamberty, Ben; Smith, A. Peyton; Bailey, Vanessa L.
Rapid climatic changes, rising air temperatures, and increased fires are expected to drive permafrost degradation and alter soil carbon (C) cycling in many high-latitude ecosystems. How these soils will respond to changes in their temperature, moisture, and overlying vegetation is uncertain but critical to understand given the large soil C stocks in these regions. We used a laboratory experiment to examine how temperature and moisture control CO 2 and CH 4 emissions from mineral soils sampled from the bottom of the annual active layer, i.e., directly above permafrost, in an Alaskan boreal forest. Gas emissions from 30 cores, subjected tomore » two temperatures and either field moisture conditions or experimental drought, were tracked over a 100-day incubation; we also measured a variety of physical and chemical characteristics of the cores. Gravimetric water content was 0.31 ± 0.12 (unitless) at the beginning of the incubation; cores at field moisture were unchanged at the end, but drought cores had declined to 0.06 ± 0.04. Daily CO 2 fluxes were positively correlated with incubation chamber temperature, core water content, and percent soil nitrogen. They also had a temperature sensitivity ( Q 10) of 1.3 and 1.9 for the field moisture and drought treatments, respectively. Daily CH 4 emissions were most strongly correlated with percent nitrogen, but neither temperature nor water content was a significant first-order predictor of CH 4 fluxes. The cumulative production of C from CO 2 was over 6 orders of magnitude higher than that from CH 4; cumulative CO 2 was correlated with incubation temperature and moisture treatment, with drought cores producing 52–73 % lower C. Cumulative CH 4 production was unaffected by any treatment. These results suggest that deep active-layer soils may be sensitive to changes in soil moisture under aerobic conditions, a critical factor as discontinuous permafrost thaws in interior Alaska. Furthermore, deep but unfrozen high-latitude soils have been shown to be strongly affected by long-term experimental warming, and these results provide insight into their future dynamics and feedback potential with future climate change.« less
Temperature and moisture effects on greenhouse gas emissions from deep active-layer boreal soils
Bond-Lamberty, Ben; Smith, A. Peyton; Bailey, Vanessa L.
2016-12-21
Rapid climatic changes, rising air temperatures, and increased fires are expected to drive permafrost degradation and alter soil carbon (C) cycling in many high-latitude ecosystems. How these soils will respond to changes in their temperature, moisture, and overlying vegetation is uncertain but critical to understand given the large soil C stocks in these regions. We used a laboratory experiment to examine how temperature and moisture control CO 2 and CH 4 emissions from mineral soils sampled from the bottom of the annual active layer, i.e., directly above permafrost, in an Alaskan boreal forest. Gas emissions from 30 cores, subjected tomore » two temperatures and either field moisture conditions or experimental drought, were tracked over a 100-day incubation; we also measured a variety of physical and chemical characteristics of the cores. Gravimetric water content was 0.31 ± 0.12 (unitless) at the beginning of the incubation; cores at field moisture were unchanged at the end, but drought cores had declined to 0.06 ± 0.04. Daily CO 2 fluxes were positively correlated with incubation chamber temperature, core water content, and percent soil nitrogen. They also had a temperature sensitivity ( Q 10) of 1.3 and 1.9 for the field moisture and drought treatments, respectively. Daily CH 4 emissions were most strongly correlated with percent nitrogen, but neither temperature nor water content was a significant first-order predictor of CH 4 fluxes. The cumulative production of C from CO 2 was over 6 orders of magnitude higher than that from CH 4; cumulative CO 2 was correlated with incubation temperature and moisture treatment, with drought cores producing 52–73 % lower C. Cumulative CH 4 production was unaffected by any treatment. These results suggest that deep active-layer soils may be sensitive to changes in soil moisture under aerobic conditions, a critical factor as discontinuous permafrost thaws in interior Alaska. Furthermore, deep but unfrozen high-latitude soils have been shown to be strongly affected by long-term experimental warming, and these results provide insight into their future dynamics and feedback potential with future climate change.« less
Temperature and moisture effects on greenhouse gas emissions from deep active-layer boreal soils
NASA Astrophysics Data System (ADS)
Bond-Lamberty, Ben; Smith, A. Peyton; Bailey, Vanessa
2016-12-01
Rapid climatic changes, rising air temperatures, and increased fires are expected to drive permafrost degradation and alter soil carbon (C) cycling in many high-latitude ecosystems. How these soils will respond to changes in their temperature, moisture, and overlying vegetation is uncertain but critical to understand given the large soil C stocks in these regions. We used a laboratory experiment to examine how temperature and moisture control CO2 and CH4 emissions from mineral soils sampled from the bottom of the annual active layer, i.e., directly above permafrost, in an Alaskan boreal forest. Gas emissions from 30 cores, subjected to two temperatures and either field moisture conditions or experimental drought, were tracked over a 100-day incubation; we also measured a variety of physical and chemical characteristics of the cores. Gravimetric water content was 0.31 ± 0.12 (unitless) at the beginning of the incubation; cores at field moisture were unchanged at the end, but drought cores had declined to 0.06 ± 0.04. Daily CO2 fluxes were positively correlated with incubation chamber temperature, core water content, and percent soil nitrogen. They also had a temperature sensitivity (Q10) of 1.3 and 1.9 for the field moisture and drought treatments, respectively. Daily CH4 emissions were most strongly correlated with percent nitrogen, but neither temperature nor water content was a significant first-order predictor of CH4 fluxes. The cumulative production of C from CO2 was over 6 orders of magnitude higher than that from CH4; cumulative CO2 was correlated with incubation temperature and moisture treatment, with drought cores producing 52-73 % lower C. Cumulative CH4 production was unaffected by any treatment. These results suggest that deep active-layer soils may be sensitive to changes in soil moisture under aerobic conditions, a critical factor as discontinuous permafrost thaws in interior Alaska. Deep but unfrozen high-latitude soils have been shown to be strongly affected by long-term experimental warming, and these results provide insight into their future dynamics and feedback potential with future climate change.
Buch, Andressa Cristhy; Schmelz, Rüdiger M; Niva, Cintia Carla; Correia, Maria Elizabeth Fernandes; Silva-Filho, Emmanoel Vieira
2017-05-01
Soil provides many ecosystem services that are essential to maintain its quality and healthy development of the flora, fauna and human well-being. Environmental mercury levels may harm the survival and diversity of the soil fauna. In this respect, efforts have been made to establish limit values of mercury (Hg) in soils to terrestrial fauna. Soil organisms such as earthworms and enchytraeids have intimate contact with trace metals in soil by their oral and dermal routes, reflecting the potentially adverse effects of this contaminant. The main goal of this study was to obtain Hg critical concentrations under normal and extreme conditions of moisture in tropical soils to Enchytraeus crypticus to order to assess if climate change may potentiate their acute and chronic toxicity effects. Tropical soils were sampled from of two Forest Conservation Units of the Rio de Janeiro State - Brazil, which has been contaminated by Hg atmospheric depositions. Worms were exposed to three moisture conditions, at 20%, 50% and 80% of water holding capacity, respectively, and in combination with different Hg (HgCl 2 ) concentrations spiked in three types of tropical soil (two natural soils and one artificial soil). The tested concentrations ranged from 0 to 512mg Hg kg -1 dry weight. Results indicate that the Hg toxicity is higher under increased conditions of moisture, significantly affecting survival and reproduction rate. Copyright © 2017 Elsevier Inc. All rights reserved.
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.
[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.
NASA Technical Reports Server (NTRS)
Ballard, Jerrell R., Jr.; Howington, Stacy E.; Cinnella, Pasquale; Smith, James A.
2011-01-01
The temperature and moisture regimes in a forest are key components in the forest ecosystem dynamics. Observations and studies indicate that the internal temperature distribution and moisture content of the tree influence not only growth and development, but onset and cessation of cambial activity [1], resistance to insect predation[2], and even affect the population dynamics of the insects [3]. Moreover, temperature directly affects the uptake and metabolism of population from the soil into the tree tissue [4]. Additional studies show that soil and atmospheric temperatures are significant parameters that limit the growth of trees and impose treeline elevation limitation [5]. Directional thermal infrared radiance effects have long been observed in natural backgrounds [6]. In earlier work, we illustrated the use of physically-based models to simulate directional effects in thermal imaging [7-8]. In this paper, we illustrated the use of physically-based models to simulate directional effects in thermal, and net radiation in a adeciduous forest using our recently developed three-dimensional, macro-scale computational tool that simulates the heat and mass transfer interaction in a soil-root-stem systems (SRSS). The SRSS model includes the coupling of existing heat and mass transport tools to stimulate the diurnal internal and external temperatures, internal fluid flow and moisture distribution, and heat flow in the system.
Evaluation of Long-term Soil Moisture Proxies in the U.S. Great Plains
NASA Astrophysics Data System (ADS)
Yuan, S.; Quiring, S. M.
2016-12-01
Soil moisture plays an important role in land-atmosphere interactions through both surface energy and water balances. However, despite its importance, there are few long-term records of observed soil moisture for investigating long-term spatial and temporal variations of soil moisture. Hence, it is necessary to find suitable approximations of soil moisture observations. 5 drought indices will be compared with simulated and observed soil moisture over the U.S. Great Plains during two time periods (1980 - 2012 and 2003 - 2012). Standardized Precipitation Index (SPI), Standardized Precipitation-Evapotranspiration Index (SPEI), Palmer Z Index (zindex) and Crop Moisture Index (CMI) will be calculated by PRISM data. The soil moisture simulations will be derived from NLDAS. In situ soil moisture will be obtained from North American Soil Moisture Database. The evaluation will focus on three main aspects: trends, variations and persistence. The results will support further research investigating long-term variations in soil moisture-climate interactions.
Mass flow of a volatile organic liquid mixture in soils
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gerstl, Z.; Galin, Ts.; Yaron, B.
1994-05-01
The flow of kerosene, a volatile organic liquid mixture (VOLM), was studied in loam and clay soils and in a medium sand. The kerosene residual capacity and conductivity were determined for all three media at different initial moisture contents and with kerosene of different compositions. The kerosene conductivity of the soil was found to be strongly influenced by the soil texture and initial moisture content as well as by the kerosene composition. The kerosene conductivity of the sand was two orders of magnitude greater than that of the soils and was unaffected by initial moisture contents as high as fieldmore » capacity. The kerosene conductivity of the loam soil was similar in oven dry and air dry soils, but increased significantly in soils at 70% and fun field capacity due to the Yuster effect. In the clay soil the kerosene conductivity of the air dry sod was four times that of the oven dry sod and increased somewhat in the soil at 70% field capacity. No kerosene flow was observed in the oven dry soil at full field capacity. The differences in kerosene conductivity in these soils and the effect of moisture content were attributed to the different pore-sin distributions of the soil& Changes in the composition of the kerosene due to volatilization of the light fractions resulted in increased viscosity of the residual kerosene. This increased viscosity affected the fluid properties of kerosene, which resulted in decreased kerosene conductivity in the sand and the soils. 29 refs., 4 figs., 4 tabs.« less
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.
USDA-ARS?s Scientific Manuscript database
Soil moisture is a key variable in understanding the hydrologic processes and energy fluxes at the land surface. In spite of new technologies for in-situ soil moisture measurements and increased availability of remotely sensed soil moisture data, scaling issues between soil moisture observations and...
NASA Astrophysics Data System (ADS)
Bekele, Dawit N.; Naidu, Ravi; Chadalavada, Sreenivasulu
2014-05-01
A comprehensive field study was conducted at a site contaminated with chlorinated solvents, mainly trichloroethylene (TCE), to investigate the influence of subsurface soil moisture and temperature on vapour intrusion (VI) into built structures. Existing approaches to predict the risk of VI intrusion into buildings assume homogeneous or discrete layers in the vadose zone through which TCE migrates from an underlying source zone. In reality, the subsurface of the majority of contaminated sites will be subject to significant variations in moisture and temperature. Detailed site-specific data were measured contemporaneously to evaluate the impact of spatial and temporal variability of subsurface soil properties on VI exposure assessment. The results revealed that indoor air vapour concentrations would be affected by spatial and temporal variability of subsurface soil moisture and temperature. The monthly monitoring of soil-gas concentrations over a period of one year at a depth of 3 m across the study site demonstrated significant variation in TCE vapour concentrations, which ranged from 480 to 629,308 μg/m3. Soil-gas wells at 1 m depth exhibited high seasonal variability in TCE vapour concentrations with a coefficient of variation 1.02 in comparison with values of 0.88 and 0.74 in 2 m and 3 m wells, respectively. Contour plots of the soil-gas TCE plume during wet and dry seasons showed that the plume moved across the site, hence locations of soil-gas monitoring wells for human risk assessment is a site specific decision. Subsurface soil-gas vapour plume characterisation at the study site demonstrates that assessment for VI is greatly influenced by subsurface soil properties such as temperature and moisture that fluctuate with the seasons of the year.
NASA Astrophysics Data System (ADS)
Carbone, E.; Small, E. E.; Badger, A.; Livneh, B.
2016-12-01
Evapotranspiration (ET) is fundamental to the water, energy and carbon cycles. However, our ability to measure ET and partition the total flux into transpiration and evaporation from soil is limited. This project aims to generate a global, observationally-based soil evaporation dataset (E-SMAP): using SMAP surface soil moisture data in conjunction with models and auxiliary observations to observe or estimate each component of the surface water balance. E-SMAP will enable a better understanding of water balance processes and contribute to forecasts of water resource availability. Here we focus on the flux between the soil surface and root zone layers (qbot), which dictates the proportion of water that is available for soil evaporation. Any water that moves from the surface layer to the root zone contributes to transpiration or groundwater recharge. The magnitude and direction of qbot are driven by gravity and the gradient in matric potential. We use a highly discretized Richards Equation-type model (e.g. Hydrus 1D software) with meteorological forcing from the North American Land Data Assimilation System (NLDAS) to estimate qbot. We verify the simulations using SMAP L4 surface and root zone soil moisture data. These data are well suited for evaluating qbot because they represent the most advanced estimate of the surface to root zone soil moisture gradient at the global scale. Results are compared with similar calculations using NLDAS and in situ soil moisture data. Preliminary calculations show that the greatest amount of variability between qbot determined from NLDAS, in situ and SMAP occurs directly after precipitation events. At these times, uncertainties in qbot calculations significantly affect E-SMAP estimates.
Cosmic ray soil moisture observing systems comos in cap fields at El Reno Oklahoma
USDA-ARS?s Scientific Manuscript database
Soil water content (SWC) partitions rainfall into runoff and infiltration, modulates surface and atmospheric exchanges of water and energy, affects plant growth and crop yields, and impacts chemical and biological activities of soil, among other things. Thus, SWC, especially over large scales, is a...
Factors affecting transport of bacteria and microspheres through biochar-amended soils
USDA-ARS?s Scientific Manuscript database
We have investigated the role of biochar feedstock type (poultry litter extract and pine chips), biochar pyrolysis temperature (350 and 700 oC), biochar application rate (1, 2, and 10%), soil moisture content (saturated and 50% saturation), soil texture (1 and 12 % clay content), and surface propert...
Moisture content measurements of moss (Sphagnum spp.) using commercial sensors
Yoshikawa, K.; Overduin, P.P.; Harden, J.W.
2004-01-01
Sphagnum (spp.) is widely distributed in permafrost regions around the arctic and subarctic. The moisture content of the moss layer affects the thermal insulative capacity and preservation of permafrost. It also controls the growth and collapse history of palsas and other peat mounds, and is relevant, in general terms, to permafrost thaw (thermokarst). In this study, we test and calibrate seven different soil moisture sensors for measuring the moisture content of Sphagnum moss under laboratory conditions. The soil volume to which each probe is sensitive is one of the important parameters influencing moisture measurement, particularly in a heterogeneous medium such as moss. Each sensor has a unique response to changing moisture content levels, solution salinity, moss bulk density and to the orientation (structure) of the Sphagnum relative to the sensor. All of the probes examined here require unique polynomial calibration equations to obtain moisture content from probe output. We provide polynomial equations for dead and live Sphagnum moss (R2 > 0.99. Copyright ?? 2004 John Wiley & Sons, Ltd.
Climate Controls AM Fungal Distributions from Global to Local Scales
NASA Astrophysics Data System (ADS)
Kivlin, S. N.; Hawkes, C.; Muscarella, R.; Treseder, K. K.; Kazenel, M.; Lynn, J.; Rudgers, J.
2016-12-01
Arbuscular mycorrhizal (AM) fungi have key functions in terrestrial biogeochemical processes; thus, determining the relative importance of climate, edaphic factors, and plant community composition on their geographic distributions can improve predictions of their sensitivity to global change. Local adaptation by AM fungi to plant hosts, soil nutrients, and climate suggests that all of these factors may control fungal geographic distributions, but their relative importance is unknown. We created species distribution models for 142 AM fungal taxa at the global scale with data from GenBank. We compared climate variables (BioClim and soil moisture), edaphic variables (phosphorus, carbon, pH, and clay content), and plant variables using model selection on models with (1) all variables, (2) climatic variables only (including soil moisture) and (3) resource-related variables only (all other soil parameters and NPP) using the MaxEnt algorithm evaluated with ENMEval. We also evaluated whether drivers of AM fungal distributions were phylogenetically conserved. To test whether global correlates of AM fungal distributions were reflected at local scales, we then surveyed AM fungi in nine plant hosts along three elevation gradients in the Upper Gunnison Basin, Colorado, USA. At the global scale, the distributions of 55% of AM fungal taxa were affected by both climate and soil resources, whereas 16% were only affected by climate and 29% were only affected by soil resources. Even for AM fungi that were affected by both climate and resources, the effects of climatic variables nearly always outweighed those of resources. Soil moisture and isothermality were the main climatic and NPP and soil carbon the main resource related factors influencing AM fungal distributions. Distributions of closely related AM fungal taxa were similarly affected by climate, but not by resources. Local scale surveys of AM fungi across elevations confirmed that climate was a key driver of AM fungal composition and root colonization, with weaker influences of plant identity and soil nutrients. These two studies across scales suggest prevailing effects of climate on AM fungal distributions. Thus, incorporating climate when forecasting future ranges of AM fungi will enhance predictions of AM fungal abundance and associated ecosystem functions.
The effect of soil type on the bioremediation of petroleum contaminated soils.
Haghollahi, Ali; Fazaelipoor, Mohammad Hassan; Schaffie, Mahin
2016-09-15
In this research the bioremediation of four different types of contaminated soils was monitored as a function of time and moisture content. The soils were categorized as sandy soil containing 100% sand (type I), clay soil containing more than 95% clay (type II), coarse grained soil containing 68% gravel and 32% sand (type III), and coarse grained with high clay content containing 40% gravel, 20% sand, and 40% clay (type IV). The initially clean soils were contaminated with gasoil to the concentration of 100 g/kg, and left on the floor for the evaporation of light hydrocarbons. A full factorial experimental design with soil type (four levels), and moisture content (10 and 20%) as the factors was employed. The soils were inoculated with petroleum degrading microorganisms. Soil samples were taken on days 90, 180, and 270, and the residual total petroleum hydrocarbon (TPH) was extracted using soxhlet apparatus. The moisture content of the soils was kept almost constant during the process by intermittent addition of water. The results showed that the efficiency of bioremediation was affected significantly by the soil type (Pvalue < 0.05). The removal percentage was the highest (70%) for the sandy soil with the initial TPH content of 69.62 g/kg, and the lowest for the clay soil (23.5%) with the initial TPH content of 69.70 g/kg. The effect of moisture content on bioremediation was not statistically significant for the investigated levels. The removal percentage in the clay soil was improved to 57% (within a month) in a separate experiment by more frequent mixing of the soil, indicating low availability of oxygen as a reason for low degradation of hydrocarbons in the clay soil. Copyright © 2016 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Tromp-van Meerveld, H. J.; McDonnell, J. J.
2009-04-01
SummaryHillslopes are fundamental landscape units, yet represent a difficult scale for measurements as they are well-beyond our traditional point-scale techniques. Here we present an assessment of electromagnetic induction (EM) as a potential rapid and non-invasive method to map soil moisture patterns at the hillslope scale. We test the new multi-frequency GEM-300 for spatially distributed soil moisture measurements at the well-instrumented Panola hillslope. EM-based apparent conductivity measurements were linearly related to soil moisture measured with the Aqua-pro capacitance sensor below a threshold conductivity and represented the temporal patterns in soil moisture well. During spring rainfall events that wetted only the surface soil layers the apparent conductivity measurements explained the soil moisture dynamics at depth better than the surface soil moisture dynamics. All four EM frequencies (7.290, 9.090, 11.250, and 14.010 kHz) were highly correlated and linearly related to each other and could be used to predict soil moisture. This limited our ability to use the four different EM frequencies to obtain a soil moisture profile with depth. The apparent conductivity patterns represented the observed spatial soil moisture patterns well when the individually fitted relationships between measured soil moisture and apparent conductivity were used for each measurement point. However, when the same (master) relationship was used for all measurement locations, the soil moisture patterns were smoothed and did not resemble the observed soil moisture patterns very well. In addition the range in calculated soil moisture values was reduced compared to observed soil moisture. Part of the smoothing was likely due to the much larger measurement area of the GEM-300 compared to the soil moisture measurements.
Near-surface turbulence as a missing link in modeling evapotranspiration-soil moisture relationships
NASA Astrophysics Data System (ADS)
Haghighi, Erfan; Kirchner, James W.
2017-07-01
Despite many efforts to develop evapotranspiration (ET) models with improved parametrizations of resistance terms for water vapor transfer into the atmosphere, estimates of ET and its partitioning remain prone to bias. Much of this bias could arise from inadequate representations of physical interactions near nonuniform surfaces from which localized heat and water vapor fluxes emanate. This study aims to provide a mechanistic bridge from land-surface characteristics to vertical transport predictions, and proposes a new physically based ET model that builds on a recently developed bluff-rough bare soil evaporation model incorporating coupled soil moisture-atmospheric controls. The newly developed ET model explicitly accounts for (1) near-surface turbulent interactions affecting soil drying and (2) soil-moisture-dependent stomatal responses to atmospheric evaporative demand that influence leaf (and canopy) transpiration. Model estimates of ET and its partitioning were in good agreement with available field-scale data, and highlight hidden processes not accounted for by commonly used ET schemes. One such process, nonlinear vegetation-induced turbulence (as a function of vegetation stature and cover fraction) significantly influences ET-soil moisture relationships. Our results are particularly important for water resources and land use planning of semiarid sparsely vegetated ecosystems where soil surface interactions are known to play a critical role in land-climate interactions. This study potentially facilitates a mathematically tractable description of the strength (i.e., the slope) of the ET-soil moisture relationship, which is a core component of models that seek to predict land-atmosphere coupling and its feedback to the climate system in a changing climate.
Hydrologic and water quality effects of thinning Loblolly Pine
Johnny M. Grace; R. W. Skaggs; G. M. Chescheir
2006-01-01
Forest operations such as harvesting, thinning, and site preparation can affect the hydrologic behavior of watersheds on poorly drained soils. The influence of these operations conducted on organic soil sites can be more pronounced than on mineral soil sites due to the differences in bulk density and soil moisture relationships that exist between mineral and organic...
Moisture drives surface decomposition in thawing tundra
NASA Astrophysics Data System (ADS)
Hicks Pries, Caitlin E.; Schuur, E. A. G.; Vogel, Jason G.; Natali, Susan M.
2013-07-01
Permafrost thaw can affect decomposition rates by changing environmental conditions and litter quality. As permafrost thaws, soils warm and thermokarst (ground subsidence) features form, causing some areas to become wetter while other areas become drier. We used a common substrate to measure how permafrost thaw affects decomposition rates in the surface soil in a natural permafrost thaw gradient and a warming experiment in Healy, Alaska. Permafrost thaw also changes plant community composition. We decomposed 12 plant litters in a common garden to test how changing plant litter inputs would affect decomposition. We combined species' tissue-specific decomposition rates with species and tissue-level estimates of aboveground net primary productivity to calculate community-weighted decomposition constants at both the thaw gradient and warming experiment. Moisture, specifically growing season precipitation and water table depth, was the most significant driver of decomposition. At the gradient, an increase in growing season precipitation from 200 to 300 mm increased mass loss of the common substrate by 100%. At the warming experiment, a decrease in the depth to the water table from 30 to 15 cm increased mass loss by 100%. At the gradient, community-weighted decomposition was 21% faster in extensive than in minimal thaw, but was similar when moss production was included. Overall, the effect of climate change and permafrost thaw on surface soil decomposition are driven more by precipitation and soil environment than by changes to plant communities. Increasing soil moisture is thereby another mechanism by which permafrost thaw can become a positive feedback to climate change.
NASA Astrophysics Data System (ADS)
Zaady, E.; Yizhaq, H.; Ashkenazy, Y.
2012-04-01
Biological soil crusts produce mucilage sheets of polysaccharides that cover the soil surface. This hydrophobic coating can seal the soil micro-pores and thus cause reduction of water permeability and may influence soil temperature. This study evaluates the impact of crust composition on sub-surface water and temperature over time. We hypothesized that the successional stages of biological soil crusts, affect soil moisture and temperature differently along a rainfall gradient throughout the year. Four experimental sites were established along a rainfall gradient in the western Negev Desert. At each site three treatments; crust removal, pure sand (moving dune) and natural crusted were monitored. Crust successional stage was measured by biophysiological and physical measurements, soil water permeability by field mini-Infiltrometer, soil moisture by neutron scattering probe and temperature by sensors, at different depths. Our main interim conclusions from the ongoing study along the rainfall gradient are: 1. the biogenic crust controls water infiltration into the soil in sand dunes, 2. infiltration was dependent on the composition of the biogenic crust. It was low for higher successional stage crusts composed of lichens and mosses and high with cyanobacterial crust. Thus, infiltration rate controlled by the crust is inverse to the rainfall gradient. Continuous disturbances to the crust increase infiltration rates, 3. despite the different rainfall amounts at the sites, soil moisture content below 50 cm is almost the same. We therefore predict that climate change in areas that are becoming dryer (desertification) will have a positive effect on soil water content and vice versa.
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.
Climate change effects on soil microarthropod abundance and community structure
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kardol, Paul; Reynolds, W. Nicholas; Norby, Richard J
2011-01-01
Long-term ecosystem responses to climate change strongly depend on how the soil subsystem and its inhabitants respond to these perturbations. Using open-top chambers, we studied the response of soil microarthropods to single and combined effects of ambient and elevated atmospheric [CO{sub 2}], ambient and elevated temperatures and changes in precipitation in constructed old-fields in Tennessee, USA. Microarthropods were assessed five years after treatments were initiated and samples were collected in both November and June. Across treatments, mites and collembola were the most dominant microarthropod groups collected. We did not detect any treatment effects on microarthropod abundance. In November, but notmore » in June, microarthropod richness, however, was affected by the climate change treatments. In November, total microarthropod richness was lower in dry than in wet treatments, and in ambient temperature treatments, richness was higher under elevated [CO{sub 2}] than under ambient [CO{sub 2}]. Differential responses of individual taxa to the climate change treatments resulted in shifts in community composition. In general, the precipitation and warming treatments explained most of the variation in community composition. Across treatments, we found that collembola abundance and richness were positively related to soil moisture content, and that negative relationships between collembola abundance and richness and soil temperature could be explained by temperature-related shifts in soil moisture content. Our data demonstrate how simultaneously acting climate change factors can affect the structure of soil microarthropod communities in old-field ecosystems. Overall, changes in soil moisture content, either as direct effect of changes in precipitation or as indirect effect of warming or elevated [CO{sub 2}], had a larger impact on microarthropod communities than did the direct effects of the warming and elevated [CO{sub 2}] treatments. Moisture-induced shifts in soil microarthropod abundance and community composition may have important impacts on ecosystem functions, such as decomposition, under future climatic change.« less
Shu, Xiao; Zhang, KeRong; Zhang, QuanFa; Wang, WeiBo
2017-11-01
With the completion of the Danjiangkou Dam, the impoundment and drainage of dams can significantly alter shorelines, hydrological regime, and sediment and can result in the loss of soil and original riparian vegetation. Revegetation may affect soil properties and have broad important implications both for ecological services and soil recovery. In this work, we investigated the soil properties under different restoration approaches, and before and after submergence in the water level fluctuation zone (WLFZ) of the Danjiangkou Reservoir. Soil physical (bulk density and soil moisture), chemical (pH, soil organic carbon, nitrogen, phosphorus and potassium contents), and heavy metals were determined. This study reported that restoration approaches have impacts on soil moisture, pH, N, soil organic carbon, P, K and heavy metals in the WLFZ of the Danjiangkou Reservoir. Our results indicated that different restoration approaches could increase the soil moisture while decrease soil pH. Higher soil organic carbon in propagule banks transplantation (PBT) and shrubs restoration (SR) indicate that PBT and SR may provide soil organic matter more quickly than trees restoration (TR). SR and TR could significantly improve the soil total P and available P. PBT and SR could improve the soil total K and available K. SR and TR could significantly promote Cu and Zn adsorption, and Pb and Fe release by plant. Submergence could significantly affect the soil pH, NO 3 - -N, NH 4 + -N, total P and available P. Submergence could promote NO 3 - -N and available P adsorption, and NH 4 + -N and total P release by soil. The soil quality index (SQI) values implied that TR and PBT greatly improved soil quality. The present study suggests that PBT and TR could be effective for soil restoration in WLFZ of the Danjiangkou Reservoir. Copyright © 2017 Elsevier Inc. All rights reserved.
Development of a SMAP-Based Drought Monitoring Product
NASA Astrophysics Data System (ADS)
Sadri, S.; Wood, E. F.; Pan, M.; Lettenmaier, D. P.
2016-12-01
Agricultural drought is defined as a deficit in the amount of soil moisture over a prolonged period of time. Soil moisture information over time and space provides critical insight for agricultural management, including both water availability for crops and moisture conditions that affect management practices such as fertilizer, pesticide applications, and their impact as non-point pollution runoff. Since April of 2015, NASA's Soil Moisture Active Passive (SMAP) mission has retrieved soil moisture using L-band passive radiometric measurements at a 8 day repeat orbit with a swath of 1000 km that maps the Earth in 2-3 days depending on locations. Of particular interest to SMAP-based agricultural applications is a monitoring product that assesses the SMAP soil moisture in terms of probability percentiles for dry (drought) or wet (pluvial) conditions. SMAP observations do result in retrievals that are spatially and temporally discontinuous. Additionally, the short SMAP record length provides a statistical challenge in estimating a drought index and thus drought risk evaluations. In this presentation, we describe a SMAP drought index for the CONUS region based on near-surface soil moisture percentiles. Because the length of the SMAP data record is limited, we use a Bayesian conditional probability approach to extend the SMAP record back to 1979 based on simulated soil moisture of the same period from the Variable Infiltration Capacity (VIC) Land Surface Model (LSM), simulated by Princeton University. This is feasible because the VIC top soil layer (10 cm) is highly correlated with the SMAP 36 km passive microwave during 2015-2016, with more than half the CONUS grids having a cross-correlation greater than 0.6, and over 0.9 in many regions. Given the extended SMAP record, we construct an empirical probability distribution of near-surface soil moisture drought index showing severities similar to those used by the U.S. Drought Monitor (from D0-D4), for a specific SMAP observation. The analysis is done for each of the 8,150 SMAP grids covering the CONUS domain. Comparisons between the SMAP drought index and that from the VIC LSM are presented for selected recent drought events. Issues such as seasonality, robustness of the fitting, regions of poor SMAP-VIC correlations, and extensions to other areas will be discussed.
NASA Astrophysics Data System (ADS)
Li, Zhenchao; Yang, Jiaxi; Gao, Xiaoqing; Zheng, Zhiyuan; Yu, Ye; Hou, Xuhong; Wei, Zhigang
2018-02-01
The understanding of surface spectral radiation and reflected radiation characteristics of different surfaces in different climate zones aids in the interpretation of regional surface energy transfers and the development of land surface models. This study analysed surface spectral radiation variations and corresponding surface albedo characteristics at different wavelengths as well as the relationship between 5-cm soil moisture and surface albedo on typical sunny days during the winter wheat growth period. The analysis was conducted using observational Loess Plateau winter wheat data from 2015. The results show that the ratio of atmospheric downward radiation to global radiation on typical sunny days is highest for near-infrared wavelengths, followed by visible wavelengths and ultraviolet wavelengths, with values of 57.3, 38.7 and 4.0%, respectively. The ratio of reflected spectral radiation to global radiation varies based on land surface type. The visible radiation reflected by vegetated surfaces is far less than that reflected by bare ground, with surface albedos of 0.045 and 0.27, respectively. Thus, vegetated surfaces absorb more visible radiation than bare ground. The atmospheric downward spectral radiation to global radiation diurnal variation ratios vary for near-infrared wavelengths versus visible and ultraviolet wavelengths on typical sunny days. The near-infrared wavelengths ratio is higher in the morning and evening and lower at noon. The visible and ultraviolet wavelengths ratios are lower in the morning and evening and higher at noon. Visible and ultraviolet wavelength surface albedo is affected by 5-cm soil moisture, demonstrating a significant negative correlation. Excluding near-infrared wavelengths, correlations between surface albedo and 5-cm soil moisture pass the 99% confidence test at each wavelength. The correlation with 5-cm soil moisture is more significant at shorter wavelengths. However, this study obtained surface spectral radiation characteristics that were affected by land surface vegetation coverage as well as by soil physical properties.
NASA Astrophysics Data System (ADS)
Taylor, Christopher M.; Harris, Philip P.; Gallego-Elvira, Belen; Folwell, Sonja S.
2017-04-01
The soil moisture control on the partition of land surface fluxes between sensible and latent heat is a key aspect of land surface models used within numerical weather prediction and climate models. As soils dry out, evapotranspiration (ET) decreases, and the excess energy is used to warm the atmosphere. Poor simulations of this dynamic process can affect predictions of mean, and in particular, extreme air temperatures, and can introduce substantial biases into projections of climate change at regional scales. The lack of reliable observations of fluxes and root zone soil moisture at spatial scales that atmospheric models use (typically from 1 to several hundred kilometres), coupled with spatial variability in vegetation and soil properties, makes it difficult to evaluate the flux partitioning at the model grid box scale. To overcome this problem, we have developed techniques to use Land Surface Temperature (LST) to evaluate models. As soils dry out, LST rises, so it can be used under certain circumstances as a proxy for the partition between sensible and latent heat. Moreover, long time series of reliable LST observations under clear skies are available globally at resolutions of the order of 1km. Models can exhibit large biases in seasonal mean LST for various reasons, including poor description of aerodynamic coupling, uncertainties in vegetation mapping, and errors in down-welling radiation. Rather than compare long-term average LST values with models, we focus on the dynamics of LST during dry spells, when negligible rain falls, and the soil moisture store is drying out. The rate of warming of the land surface, or, more precisely, its warming rate relative to the atmosphere, emphasises the impact of changes in soil moisture control on the surface energy balance. Here we show the application of this approach to model evaluation, with examples at continental and global scales. We can compare the behaviour of both fully-coupled land-atmosphere models, and land surface models forced by observed meteorology. This approach provides insight into a fundamental process that affects predictions on multiple time scales, and which has an important impact for society.
Parsakho, Aidin; Hosseini, Seyed Ataollah; Jalilvand, Hamid; Lotfalian, Majid
2008-06-01
Effects of moisture, porosity and soil bulk density properties, grubbing time and terrain side slopes on pc 220 komatsu hydraulic excavator productivity were investigated in Miana forests road construction project which located in the northern forest of Iran. Soil moisture and porosity determined by samples were taken from undisturbed soil. The elements of daily works were measured with a digital stop watch and video camera in 14 observations (days). The road length and cross section profiles after each 20 m were selected to estimate earthworks volume. Results showed that the mean production rates for the pc 220 komatsu excavators were 60.13 m3 h(-1) and earthwork 14.76 m h(-1) when the mean depth of excavation or cutting was 4.27 m3 m(-1), respectively. There was no significant effects (p = 0.5288) from the slope classes' treatments on productivity, whereas grubbing time, soil moisture, bulk density and porosity had significantly affected on excavator earthworks volume (p < 0.0001). Clear difference was showed between the earthwork length by slope classes (p = 0.0060). Grubbing time (p = 0.2180), soil moisture (p = 0.1622), bulk density (p = 0.2490) and porosity (p = 0.2159) had no significant effect on the excavator earthworks length.
Ground Albedo Neutron Sensing (GANS) method for measurements of soil moisture in cropped fields
NASA Astrophysics Data System (ADS)
Andres Rivera Villarreyes, Carlos; Baroni, Gabriele; Oswald, Sascha E.
2013-04-01
Measurement of soil moisture at the plot or hill-slope scale is an important link between local vadose zone hydrology and catchment hydrology. However, so far only few methods are on the way to close this gap between point measurements and remote sensing. This study evaluates the applicability of the Ground Albedo Neutron Sensing (GANS) for integral quantification of seasonal soil moisture in the root zone at the scale of a field or small watershed, making use of the crucial role of hydrogen as neutron moderator relative to other landscape materials. GANS measurements were performed at two locations in Germany under different vegetative situations and seasonal conditions. Ground albedo neutrons were measured at (i) a lowland Bornim farmland (Brandenburg) cropped with sunflower in 2011 and winter rye in 2012, and (ii) a mountainous farmland catchment (Schaefertal, Harz Mountains) since middle 2011. At both sites depth profiles of soil moisture were measured at several locations in parallel by frequency domain reflectometry (FDR) for comparison and calibration. Initially, calibration parameters derived from a previous study with corn cover were tested under sunflower and winter rye periods at the same farmland. GANS soil moisture based on these parameters showed a large discrepancy compared to classical soil moisture measurements. Therefore, two new calibration approaches and four different ways of integration the soil moisture profile to an integral value for GANS were evaluated in this study. This included different sets of calibration parameters based on different growing periods of sunflower. New calibration parameters showed a good agreement with FDR network during sunflower period (RMSE = 0.023 m3 m-3), but they underestimated soil moisture in the winter rye period. The GANS approach resulted to be highly affected by temporal changes of biomass and crop types which suggest the need of neutron corrections for long-term observations with crop rotation. Finally, Bornim sunflower parameters were transferred to Schaefertal catchment for further evaluation. This study proves GANS potential to close the measurement gap between point scale and remote sensing scale; however, its calibration needs to be adapted for vegetation in cropped fields.
NASA Astrophysics Data System (ADS)
Nair, A. S.; Indu, J.
2017-12-01
Prediction of soil moisture dynamics is high priority research challenge because of the complex land-atmosphere interaction processes. Soil moisture (SM) plays a decisive role in governing water and energy balance of the terrestrial system. An accurate SM estimate is imperative for hydrological and weather prediction models. Though SM estimates are available from microwave remote sensing and land surface model (LSM) simulations, it is affected by uncertainties from several sources during estimation. Past studies have generally focused on land data assimilation (DA) for improving LSM predictions by assimilating soil moisture from single satellite sensor. This approach is limited by the large time gap between two consequent soil moisture observations due to satellite repeat cycle of more than three days at the equator. To overcome this, in the present study, we have performed DA using ensemble products from the soil moisture operational product system (SMOPS) blended soil moisture retrievals from different satellite sensors into Noah LSM. Before the assimilation period, the Noah LSM is initialized by cycling through seven multiple loops from 2008 to 2010 forcing with Global data assimilation system (GDAS) data over the Indian subcontinent. We assimilated SMOPS into Noah LSM for a period of two years from 2010 to 2011 using Ensemble Kalman Filter within NASA's land information system (LIS) framework. Results show that DA has improved Noah LSM prediction with a high correlation of 0.96 and low root mean square difference of 0.0303 m3/m3 (figure 1a). Further, this study has also investigated the notion of assimilating microwave brightness temperature (Tb) as a proxy for SM estimates owing to the close proximity of Tb and SM. Preliminary sensitivity analysis show a strong need for regional parameterization of radiative transfer models (RTMs) to improve Tb simulation. Towards this goal, we have optimized the forward RTM using swarm optimization technique for direct Tb assimilation. The results indicate an improvement in Tb simulations based on the multi polarization difference index approach with a correlation of 0.81 (figure 1b (e)) and bias of < 5 K with respect to the SMOS Tb.
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.
NASA Astrophysics Data System (ADS)
Shi, Y.; Eissenstat, D. M.; Davis, K. J.; He, Y.
2015-12-01
Forest carbon processes are affected by soil moisture, soil temperature and solar radiation. Most of the current biogeochemical models are 1-D and represent one point in space. Therefore they can neither resolve topographically driven hill-slope soil moisture patterns, nor simulate the nonlinear effects of soil moisture on carbon processes. A spatially-distributed biogeochemistry model, Flux-PIHM-BGC, has been developed by coupling the Biome-BGC (BBGC) model with a coupled physically-based land surface hydrologic model, Flux-PIHM. Flux-PIHM incorporates a land-surface scheme (adapted from the Noah land surface model) into the Penn State Integrated Hydrologic Model (PIHM). 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. Flux-PIHM-BGC model was tested at the Susquehanna/Shale Hills critical zone observatory (SSHCZO). The abundant observations at the SSHCZO, including eddy covariance fluxes, soil moisture, groundwater level, sap flux, stream discharge, litterfall, leaf area index, aboveground carbon stock, and soil carbon efflux, provided an ideal test bed for the coupled model. Model results show that when uniform solar radiation is used, vegetation carbon and soil carbon are positively correlated with soil moisture in space, which agrees with the observations within the watershed. When topographically-driven solar radiation is used, however, the wetter valley floor becomes radiation limited, and produces less vegetation and soil carbon than the drier hillslope due to the assumption that canopy height is uniform in the watershed. This contradicts with the observations, and suggests that a tree height model with dynamic allocation model are needed to reproduce the spatial variation of carbon processes within a watershed.
Estimation of Physical Parameters of a Multilayered Multi-Scale Vegetated Surface
NASA Astrophysics Data System (ADS)
Hosni, I.; Bennaceur Farah, L.; Naceur, M. S.; Farah, I. R.
2016-06-01
Soil moisture is important to enable the growth of vegetation in the way that it also conditions the development of plant population. Additionally, its assessment is important in hydrology and agronomy, and is a warning parameter for desertification. Furthermore, the soil moisture content affects exchanges with the atmosphere via the energy balance at the soil surface; it is significant due to its impact on soil evaporation and transpiration. Therefore, it conditions the energy transfer between Earth and atmosphere. Many remote sensing methods were tested. For the soil moisture; the first methods relied on the optical domain (short wavelengths). Obviously, due to atmospheric effects and the presence of clouds and vegetation cover, this approach is doomed to fail in most cases. Therefore, the presence of vegetation canopy complicates the retrieval of soil moisture because the canopy contains moisture of its own. This paper presents a synergistic methodology of SAR and optical remote sensing data, and it's for simulation of statistical parameters of soil from C-band radar measurements. Vegetation coverage, which can be easily estimated from optical data, was combined in the backscattering model. The total backscattering was divided into the amount attributed to areas covered with vegetation and that attributed to areas of bare soil. Backscattering coefficients were simulated using the established backscattering model. A two-dimensional multiscale SPM model has been employed to investigate the problem of electromagnetic scattering from an underlying soil. The water cloud model (WCM) is used to account for the effect of vegetation water content on radar backscatter data, whereof to eliminate the impact of vegetation layer and isolate the contributions of vegetation scattering and absorption from the total backscattering coefficient.
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.
Reconstructions of Soil Moisture for the Upper Colorado River Basin Using Tree-Ring Chronologies
NASA Astrophysics Data System (ADS)
Tootle, G.; Anderson, S.; Grissino-Mayer, H.
2012-12-01
Soil moisture is an important factor in the global hydrologic cycle, but existing reconstructions of historic soil moisture are limited. Tree-ring chronologies (TRCs) were used to reconstruct annual soil moisture in the Upper Colorado River Basin (UCRB). Gridded soil moisture data were spatially regionalized using principal components analysis and k-nearest neighbor techniques. Moisture sensitive tree-ring chronologies in and adjacent to the UCRB were correlated with regional soil moisture and tested for temporal stability. TRCs that were positively correlated and stable for the calibration period were retained. Stepwise linear regression was applied to identify the best predictor combinations for each soil moisture region. The regressions explained 42-78% of the variability in soil moisture data. We performed reconstructions for individual soil moisture grid cells to enhance understanding of the disparity in reconstructive skill across the regions. Reconstructions that used chronologies based on ponderosa pines (Pinus ponderosa) and pinyon pines (Pinus edulis) explained increased variance in the datasets. Reconstructed soil moisture was standardized and compared with standardized reconstructed streamflow and snow water equivalent from the same region. Soil moisture reconstructions were highly correlated with streamflow and snow water equivalent reconstructions, indicating reconstructions of soil moisture in the UCRB using TRCs successfully represent hydrologic trends, including the identification of periods of prolonged drought.
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.
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.
NASA Astrophysics Data System (ADS)
Flores, A. N.; Entekhabi, D.; Bras, R. L.
2007-12-01
Soil hydraulic and thermal properties (SHTPs) affect both the rate of moisture redistribution in the soil column and the volumetric soil water capacity. Adequately constraining these properties through field and lab analysis to parameterize spatially-distributed hydrology models is often prohibitively expensive. Because SHTPs vary significantly at small spatial scales individual soil samples are also only reliably indicative of local conditions, and these properties remain a significant source of uncertainty in soil moisture and temperature estimation. In ensemble-based soil moisture data assimilation, uncertainty in the model-produced prior estimate due to associated uncertainty in SHTPs must be taken into account to avoid under-dispersive ensembles. To treat SHTP uncertainty for purposes of supplying inputs to a distributed watershed model we use the restricted pairing (RP) algorithm, an extension of Latin Hypercube (LH) sampling. The RP algorithm generates an arbitrary number of SHTP combinations by sampling the appropriate marginal distributions of the individual soil properties using the LH approach, while imposing a target rank correlation among the properties. A previously-published meta- database of 1309 soils representing 12 textural classes is used to fit appropriate marginal distributions to the properties and compute the target rank correlation structure, conditioned on soil texture. Given categorical soil textures, our implementation of the RP algorithm generates an arbitrarily-sized ensemble of realizations of the SHTPs required as input to the TIN-based Realtime Integrated Basin Simulator with vegetation dynamics (tRIBS+VEGGIE) distributed parameter ecohydrology model. Soil moisture ensembles simulated with RP- generated SHTPs exhibit less variance than ensembles simulated with SHTPs generated by a scheme that neglects correlation among properties. Neglecting correlation among SHTPs can lead to physically unrealistic combinations of parameters that exhibit implausible hydrologic behavior when input to the tRIBS+VEGGIE model.
NASA Astrophysics Data System (ADS)
Zhang, Y. J.; Guo, S. L.; Zhao, M.; Du, L. L.; Li, R. J.; Jiang, J. S.; Wang, R.; Li, N. N.
2015-06-01
Temperature sensitivity of soil organic carbon (SOC) mineralization (i.e., Q10) determines how strong the feedback from global warming may be on the atmospheric CO2 concentration; thus, understanding the factors influencing the interannual variation in Q10 is important for accurately estimating local soil carbon cycle. In situ SOC mineralization rate was measured using an automated CO2 flux system (Li-8100) in long-term bare fallow soil in the Loess Plateau (35°12' N, 107°40' E) in Changwu, Shaanxi, China from 2008 to 2013. The results showed that the annual cumulative SOC mineralization ranged from 226 to 298 g C m-2 yr-1, with a mean of 253 g C m-2 yr-1 and a coefficient of variation (CV) of 13%, annual Q10 ranged from 1.48 to 1.94, with a mean of 1.70 and a CV of 10%, and annual soil moisture content ranged from 38.6 to 50.7% soil water-filled pore space (WFPS), with a mean of 43.8% WFPS and a CV of 11%, which were mainly affected by the frequency and distribution of precipitation. Annual Q10 showed a quadratic correlation with annual mean soil moisture content. In conclusion, understanding of the relationships between interannual variation in Q10, soil moisture, and precipitation are important to accurately estimate the local carbon cycle, especially under the changing climate.
How Much Water Trees Access and How It Determines Forest Response to Drought
NASA Astrophysics Data System (ADS)
Berdanier, A. B.; Clark, J. S.
2015-12-01
Forests are transformed by drought as water availability drops below levels where trees of different sizes and species can maintain productivity and survive. Physiological studies have provided detailed understanding of how species differences affect drought vulnerability but they offer almost no insights about the amount of water different trees can access beyond general statements about rooting depth. While canopy architecture provides strong evidence for light availability aboveground, belowground moisture availability remains essentially unknown. For example, do larger trees always have greater access to soil moisture? In temperate mixed forests, the ability to access a large soil moisture pool could minimize damage during drought events and facilitate post-drought recovery, potentially at the expense of neighboring trees. We show that the pool of accessible soil moisture can be estimated for trees with data on whole-plant transpiration and that this data can be used to predict water availability for forest stands. We estimate soil water availability with a Bayesian state-space model based on a simple water balance, where cumulative depressions in water use below potential transpiration indicate soil resource depletion. We compare trees of different sizes and species, extend these findings to the entire stand, and connect them to our recent research showing that tree survival after drought depends on post-drought growth recovery and local moisture availability. These results can be used to predict competitive abilities for soil water, understand ecohydrological variation within stands, and identify trees that are at risk of damage from future drought events.
Huang, Yu-Hsuan; Hung, Chih-Yu; Lin, I-Rhy; Kume, Tomonori; Menyailo, Oleg V; Cheng, Chih-Hsin
2017-11-15
Soil respiration contributes to a large quantity of carbon emissions in the forest ecosystem. In this study, the soil respiration rates at three Taiwanese forest plantations (two lowland and one mid-elevation) were investigated. We aimed to determine how soil respiration varies between lowland and mid-elevation forest plantations and identify the relative importance of biotic and abiotic factors affecting soil respiration. The results showed that the temporal patterns of soil respiration rates were mainly influenced by soil temperature and soil water content, and a combined soil temperature and soil water content model explained 54-80% of the variation. However, these two factors affected soil respiration differently. Soil temperature positively contributed to soil respiration, but a bidirectional relationship between soil respiration and soil water content was revealed. Higher soil moisture content resulted in higher soil respiration rates at the lowland plantations but led to adverse effects at the mid-elevation plantation. The annual soil respiration rates were estimated as 14.3-20.0 Mg C ha -1 year -1 at the lowland plantations and 7.0-12.2 Mg C ha -1 year -1 at the mid-elevation plantation. When assembled with the findings of previous studies, the annual soil respiration rates increased with the mean annual temperature and litterfall but decreased with elevation and the mean annual precipitation. A conceptual model of the biotic and abiotic factors affecting the spatial and temporal patterns of the soil respiration rate was developed. Three determinant factors were proposed: (i) elevation, (ii) stand characteristics, and (iii) soil temperature and soil moisture. The results indicated that changes in temperature and precipitation significantly affect soil respiration. Because of the high variability of soil respiration, more studies and data syntheses are required to accurately predict soil respiration in Taiwanese forests.
Experimental investigation of the origin of fynbos plant community structure after fire.
Silvertown, Jonathan; Araya, Yoseph N; Linder, H Peter; Gowing, David J
2012-11-01
Species in plant communities segregate along fine-scale hydrological gradients. Although this phenomenon is not unique to fynbos, this community regenerates after fire and therefore provides an opportunity to study the ecological genesis of hydrological niche segregation. Following wildfires at two field sites where we had previously mapped the vegetation and monitored the hydrology, seeds were moved experimentally in >2500 intact soil cores up and down soil-moisture gradients to test the hypothesis that hydrological niche segregation is established during the seedling phase of the life cycle. Seedling numbers and growth were then monitored and they were identified using DNA bar-coding, the first use of this technology for an experiment of this kind. At the site where niche segregation among Restionaceae had previously been found, the size of seedlings was significantly greater, the wetter the location into which they were moved, regardless of the soil moisture status of their location of origin, or of the species. Seedling weight was also significantly greater in a competition treatment where the roots of other species were excluded. No such effects were detected at the control site where niche segregation among Restionaceae was previously found to be absent. The finding that seedling growth on hydrological gradients in the field is affected by soil moisture status and by root competition shows that hydrological niche segregation could potentially originate in the seedling stage. The methodology, applied at a larger scale and followed-through for a longer period, could be used to determine whether species are differently affected by soil moisture.
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
NASA Technical Reports Server (NTRS)
Girotto, Manuela; Reichle, Rolf H.; De Lannoy, Gabrielle J. M.; Rodell, Matthew
2017-01-01
Observations from recent soil moisture missions (e.g. SMOS) have been used in innovative data assimilation studies to provide global high spatial (i.e. 40 km) and temporal resolution (i.e. 3-days) soil moisture profile estimates from microwave brightness temperature observations. In contrast with microwave-based satellite missions that are only sensitive to near-surface soil moisture (0 - 5 cm), the Gravity Recovery and Climate Experiment (GRACE) mission provides accurate measurements of the entire vertically integrated terrestrial water storage column but, it is characterized by low spatial (i.e. 150,000 km2) and temporal (i.e. monthly) resolutions. Data assimilation studies have shown that GRACE-TWS primarily affects (in absolute terms) deeper moisture storages (i.e., groundwater). This work hypothesizes that unprecedented soil water profile accuracy can be obtained through the joint assimilation of GRACE terrestrial water storage and SMOS brightness temperature observations. A particular challenge of the joint assimilation is the use of the two different types of measurements that are relevant for hydrologic processes representing different temporal and spatial scales. The performance of the joint assimilation strongly depends on the chosen assimilation methods, measurement and model error spatial structures. The optimization of the assimilation technique constitutes a fundamental step toward a multi-variate multi-resolution integrative assimilation system aiming to improve our understanding of the global terrestrial water cycle.
NASA Astrophysics Data System (ADS)
Girotto, M.; Reichle, R. H.; De Lannoy, G.; Rodell, M.
2017-12-01
Observations from recent soil moisture missions (e.g. SMOS) have been used in innovative data assimilation studies to provide global high spatial (i.e. 40 km) and temporal resolution (i.e. 3-days) soil moisture profile estimates from microwave brightness temperature observations. In contrast with microwave-based satellite missions that are only sensitive to near-surface soil moisture (0-5 cm), the Gravity Recovery and Climate Experiment (GRACE) mission provides accurate measurements of the entire vertically integrated terrestrial water storage column but, it is characterized by low spatial (i.e. 150,000 km2) and temporal (i.e. monthly) resolutions. Data assimilation studies have shown that GRACE-TWS primarily affects (in absolute terms) deeper moisture storages (i.e., groundwater). This work hypothesizes that unprecedented soil water profile accuracy can be obtained through the joint assimilation of GRACE terrestrial water storage and SMOS brightness temperature observations. A particular challenge of the joint assimilation is the use of the two different types of measurements that are relevant for hydrologic processes representing different temporal and spatial scales. The performance of the joint assimilation strongly depends on the chosen assimilation methods, measurement and model error spatial structures. The optimization of the assimilation technique constitutes a fundamental step toward a multi-variate multi-resolution integrative assimilation system aiming to improve our understanding of the global terrestrial water cycle.
NASA Astrophysics Data System (ADS)
Montzka, C.; Rötzer, K.; Bogena, H. R.; Vereecken, H.
2017-12-01
Improving the coarse spatial resolution of global soil moisture products from SMOS, SMAP and ASCAT is currently an up-to-date topic. Soil texture heterogeneity is known to be one of the main sources of soil moisture spatial variability. A method has been developed that predicts the soil moisture standard deviation as a function of the mean soil moisture based on soil texture information. It is a closed-form expression using stochastic analysis of 1D unsaturated gravitational flow in an infinitely long vertical profile based on the Mualem-van Genuchten model and first-order Taylor expansions. With the recent development of high resolution maps of basic soil properties such as soil texture and bulk density, relevant information to estimate soil moisture variability within a satellite product grid cell is available. Here, we predict for each SMOS, SMAP and ASCAT grid cell the sub-grid soil moisture variability based on the SoilGrids1km data set. We provide a look-up table that indicates the soil moisture standard deviation for any given soil moisture mean. The resulting data set provides important information for downscaling coarse soil moisture observations of the SMOS, SMAP and ASCAT missions. Downscaling SMAP data by a field capacity proxy indicates adequate accuracy of the sub-grid soil moisture patterns.
Polymer tensiometers in a saline environment.
NASA Astrophysics Data System (ADS)
van der Ploeg, Martine; Gooren, H. P. A.; Bakker, G.; Russell, W.; Hoogendam, C. W.; Huiskes, C.; Shouse, P.; de Rooij, G. H.
2010-05-01
It is estimated that 20% of all cultivated land and nearly half of the irrigated land is salt-affected, which pose major economic and environmental problems. Salinity may be the result of two processes; dryland and irrigation salinity. Dryland salinity is caused by a rise in the groundwater table, which occurs as a result of the replacement of deep-rooted, perennial native vegetation by shallow-rooted annual species meant for production. Irrigation salinity may occur as a result of poor water quality, poor drainage, or inefficient use of water. Consequently, new strategies to enhance crop yield stability on saline soils represent a major research priority (Botella et al. 2005). At the same time, native vegetation is capable of thriving under saline and/or dry conditions. The plant physiology of such vegetation has been investigated thoroughly, but the relation with in situ soil properties (soil moisture and salinity) may be more difficult to unravel as soil moisture sensors are less sensitive in dry soil, and the signal of most soil moisture content sensors is strongly attenuated by soil salinity. Recently, polymer tensiometer were developed that are able to measure matric potentials (closely related to a soil's moisture status) in dry soils. Polymer tensiometers consist of a solid ceramic, a stainless steel cup and a pressure transducer. The ceramic consist of a support layer and a membrane with 2 nm pore-size to prevent polymer leakage. Between the ceramic membrane and the pressure transducer a tiny chamber is located, which contains the polymer solution. The polymer's osmotic potential strongly reduces the total water potential inside the polymer tensiometer, which causes build-up of osmotic pressure. Polymer tensiometers would thus be an ideal instrument to measure in dry soil, if the polymer inside the tensiometer is not affected by the salts in the soil solution. We will address some key issues regarding the use of POTs in saline environments by showing results from a field experiment conducted in a very saline soil. This research was funded by the Dutch Technology Foundation (STW).
NASA Astrophysics Data System (ADS)
Bian, Zhengfu; Lei, Shaogang; Inyang, Hilary I.; Chang, Luqun; Zhang, Richen; Zhou, Chengjun; He, Xiao
2009-03-01
Mining affects the environment in different ways depending on the physical context in which the mining occurs. In mining areas with an arid environment, mining affects plants’ growth by changing the amount of available water. This paper discusses the effects of mining on two important determinants of plant growth—soil moisture and groundwater table (GWT)—which were investigated using an integrated approach involving a field sampling investigation with remote sensing (RS) and ground-penetrating radar (GPR). To calculate and map the distribution of soil moisture for a target area, we initially analyzed four models for regression analysis between soil moisture and apparent thermal inertia and finally selected a linear model for modeling the soil moisture at a depth 10 cm; the relative error of the modeled soil moisture was about 6.3% and correlation coefficient 0.7794. A comparison of mined and unmined areas based on the results of limited field sampling tests or RS monitoring of Landsat 5-thermatic mapping (TM) data indicated that soil moisture did not undergo remarkable changes following mining. This result indicates that mining does not have an effect on soil moisture in the Shendong coal mining area. The coverage of vegetation in 2005 was compared with that in 1995 by means of the normalized difference vegetation index (NDVI) deduced from TM data, and the results showed that the coverage of vegetation in Shendong coal mining area has improved greatly since 1995 because of policy input RMB¥0.4 per ton coal production by Shendong Coal Mining Company. The factor most affected by coal mining was GWT, which dropped from a depth of 35.41 m before mining to a depth of 43.38 m after mining at the Bulianta Coal Mine based on water well measurements. Ground-penetrating radar at frequencies of 25 and 50 MHz revealed that the deepest GWT was at about 43.4 m. There was a weak water linkage between the unsaturated zone and groundwater, and the decline of water table primarily resulted from the well pumping for mining safety rather than the movement of cracking strata. This result is in agreement with the measurements of the water wells. The roots of nine typical plants in the study area were investigated. Populus was found to have the deepest root system with a depth of about 26 m. Based on an assessment of plant growth demands and the effect of mining on environmental factors, we concluded that mining will have less of an effect on plant growth at those sites where the primary GWT depth before mining was deep enough to be unavailable to plants. If the primary GWT was available for plant growth before mining, especially to those plants with deeper roots, mining will have a significant effect on the growth of plants and the mechanism of this effect will include the loss of water to roots and damage to the root system.
NASA Astrophysics Data System (ADS)
Rosier, C. L.; Van Stan, J. T., II; Trammell, T. L.
2017-12-01
Urbanization alters environmental conditions such as temperature, moisture, carbon (C) and nitrogen (N) deposition affecting critical soil processes (e.g., C storage). Urban soils experience elevated N deposition (e.g., transportation, industry) and decreased soil moisture via urban heat island that can subsequently alter soil microbial community structure and activity. However, there is a critical gap in understanding how increased temperatures and pollutant deposition influences soil microbial community structure and soil C/N cycling in urban forests. Furthermore, canopy structural differences between individual tree species is a potentially important mechanism facilitating the deposition of pollutants to the soil. The overarching goal of this study is to investigate the influence of urbanization and tree species structural differences on the bacterial and fungal community and C and N content of soils experiencing a gradient of urbanization pressures (i.e., forest edge to interior; 150-m). Soil cores (1-m depth) were collected near the stem (< 0.5 meter) of two tree species with contrasting canopy and bark structure (Fagus grandifolia, vs. Liriodendron tulipifera), and evaluated for soil microbial structure via metagenomic analysis and soil C/N content. We hypothesize that soil moisture constraints coupled with increases in recalcitrant C will decrease gram negative bacteria (i.e., dependent on labile C) while increasing saprophytic fungal community abundance (i.e., specialist consuming recalcitrant C) within both surface and subsurface soils experiencing the greatest urban pressure (i.e., forest edge). We further expect trees located on the edge of forest fragments will maintain greater surface soil (< 20 cm) C concentrations due to decreased soil moisture constraining microbial activity (e.g., slower decay), and increased capture of recalcitrant C stocks from industrial/vehicle emission sources (e.g., black C). Our initial results support our hypotheses that urbanization alters soil microbial community composition via reduced soil moisture and carbon storage potential via deposition gradients. Further analyses will answer important questions regarding how individual tree species alters urban soil C storage, N retention, and microbial dynamics.
NASA Astrophysics Data System (ADS)
Schaefer, Carlos; Thomazini, André; Michel, Roberto; Francelino, Márcio; Pereira, Antônio; Schünemann, Adriano; Mendonça, Eduardo Sá
2017-04-01
Current climate change is greatly affecting terrestrial ecosystems of Maritime Antarctica, especially due the variations in soil temperature and moisture content. The vegetation species distribution in Maritime Antarctica is highly heterogeneous on the landscape, being governed mainly by water regime and soil characteristics. Hence, the objective of this study was to evaluate soil temperature and moisture based on long-term in situ measurements from two well-developed vegetation communities in Coppermine Peninsula, Robert Island, Maritime Antarctica. The moss site (S1) is located in a marine terrace, highly influenced by ice/snow/permafrost melting (20 m a.s.l) not affected by permafrost. This site represents the most extensive moss carpet in Coppermine Peninsula, mainly constituted by Sanionia uncinata (Hedw.) Loeske, forming a dense carpet of 3-7 cm thickness. The moss/lichen site (S2) is located in an elevated area on basaltic ridge (29 m a.s.l.). The site has great influence of permafrost bellow the A horizon of the soil, at 50 cm depth. Vegetation species constitution is highly variable, with a significant occurrence of Polytrichastrum alpinum G.L. Smith. Musiccolas lichens populations of Psoroma cinnamomeum Malme, Ochrolechia frigida (Sw.). The monitoring systems consist of soil temperature probes (Campbell L107E thermocouple, accuracy of ± 0.2°C) and soil moisture probes (CS656 water content reflectometer, accuracy of ± 2.5%), placed in the active layer at 0-10 cm depths. Three probes were inserted at each site in triplicates, spaced at 2 m from each other. All probes were connected to a Campbell Scientific CR 1000 data logger, recording data at every 1 hour interval. We calculated the thawing days (TD), freezing days (FD); thawing degree days (TDD) and freezing degree days (FDD); all according to Guglielmin et al. (2008). This system recorded data of soil temperature and moisture from February 2014 to February 2016. A predominance of freezing conditions was observed to occur in S1 with only 1 thaw day in the studied period (23 thawed degree days, -1400 freeze degree days), whilst thawed days occur in January, February and March in S2 (118 thawed degree days, -1107 freeze degree days). Almeida et al (2014) attributed the thermal buffering effect under mosses primarily to higher moisture onsite, but recognized the possible contribution of a longer duration of the snowpack. Soil moisture presented less variation compared to values of soil temperature along the monitored period, hourly records show average soil moisture of 0.18 m3 m-3 (0.52 max, 0.09 min) and 0.11 m3 m-3 (0.38 max, 0.04 min) at S1 and S2, respectively. S1 presented a more pronounced buffering effect due to its position in the landscape where thawing of surrounding active layer continuously supply water, providing conditions for a thicker vegetation cover, On the other hand, the moss/lichen site is located in the middle of the slope, where drainage is facilitated.
NASA Astrophysics Data System (ADS)
Senanayake, I. P.; Yeo, I. Y.; Tangdamrongsub, N.; Willgoose, G. R.; Hancock, G. R.; Wells, T.; Fang, B.; Lakshmi, V.
2017-12-01
Long-term soil moisture datasets at high spatial resolution are important in agricultural, hydrological, and climatic applications. The soil moisture estimates can be achieved using satellite remote sensing observations. However, the satellite soil moisture data are typically available at coarse spatial resolutions ( several tens of km), therefore require further downscaling. Different satellite soil moisture products have to be conjointly employed in developing a consistent time-series of high resolution soil moisture, while the discrepancies amongst different satellite retrievals need to be resolved. This study aims to downscale three different satellite soil moisture products, the Soil Moisture and Ocean Salinity (SMOS, 25 km), the Soil Moisture Active Passive (SMAP, 36 km) and the SMAP-Enhanced (9 km), and to conduct an inter-comparison of the downscaled results. The downscaling approach is developed based on the relationship between the diurnal temperature difference and the daily mean soil moisture content. The approach is applied to two sub-catchments (Krui and Merriwa River) of the Goulburn River catchment in the Upper Hunter region (NSW, Australia) to estimate soil moisture at 1 km resolution for 2015. The three coarse spatial resolution soil moisture products and their downscaled results will be validated with the in-situ observations obtained from the Scaling and Assimilation of Soil Moisture and Streamflow (SASMAS) network. The spatial and temporal patterns of the downscaled results will also be analysed. This study will provide the necessary insights for data selection and bias corrections to maintain the consistency of a long-term high resolution soil moisture dataset. The results will assist in developing a time-series of high resolution soil moisture data over the south-eastern Australia.
USDA-ARS?s Scientific Manuscript database
Stringent environmental regulations are being developed to control the emission of soil fumigants to reduce air pollution. Water application is a low-cost strategy for fumigant emission control and applicable for a wide range of commodity groups, especially those with low profit margins. Although it...
NASA Astrophysics Data System (ADS)
Du, C.; Yu, J.; Sun, F.; Liu, X.
2015-12-01
To reveal how water and vapor transfer in vadose zone affect evapotranspiration in Gobi desert and riparian in hyper arid region is important for understanding eco-hydrological process. Field studies and numerical simulations were imported to evaluate the water and vapor movement processes under non isothermal and lower water content conditions. The soil profiles (12 layers) in Gobi desert and riparian sites of Ejina were installed with sensors to monitor soil moisture and temperature for 1 year. The meteorological conditions and water table were measured by micro weather stations and mini-Divers respectively in the two sites. Soil properties, including particles composition, moisture, bulk density, water retention curve, and saturated hydraulic conductivity of two site soil profiles, was measured. The observations showed that soil temperatures for the two sites displayed large diurnal and seasonal fluctuations. Temperature gradients with depth resulted in a downward in summer and upward in winter and became driving force for thermal vapor movement. Soil moistures in Gobi desert site were very low and varied slowly with time. While the soil moistures in riparian site were complicated due to root distribution but water potentials remained uniform with time. The hydrus-1D was employed to simulate evapotranspiration processes. The simulation results showed the significant difference of evaporation rate in the Gobi desert and riparian sites.
NASA Technical Reports Server (NTRS)
Liu, Yi; van Dijk, Albert I.J.M.; Owe, Manfred
2007-01-01
Spatiotemporal patterns in soil moisture and vegetation water content across mainland Australia were investigated from 1998 through 2005, using TRMMITMI passive microwave observations. The Empirical Orthogonal Function technique was used to extract dominant spatial and temporal patterns in retrieved estimates of moisture content for the top 1-cm of soil (theta) and vegetation moisture content (via optical depth tau). The dominant temporal theta and tau patterns were strongly correlated to El Nino/Southern Oscillation (ENSO) in spring (3 = 0.90), and to a progressively lesser extent autumn, summer and winter. The Indian Ocean Dipole (IOD) index also explained part of the variation in spring 8 and z. Cluster analysis suggested that the regions most affected by ENS0 are mainly located in eastern Australia. The results suggest that the drought conditions experienced in eastern Australia since 2000 an clearly expressed in these satellite observations have a strong connection with ENSO patterns.
James Reardon; Roger Hungerford; Kevin Ryan
2007-01-01
The smouldering combustion of peat and muck soil plays an important role in the creation and maintenance of wetland communities. This experimental study was conducted to improve our understanding of how moisture and mineral content constrain smouldering in organic soil. Laboratory burning was conducted with root mat and muck soil samples from pocosin and pond pine...
Soil moisture and fungi affect seed survival in California grassland annual plants.
Mordecai, Erin A
2012-01-01
Survival of seeds in the seed bank is important for the population dynamics of many plant species, yet the environmental factors that control seed survival at a landscape level remain poorly understood. These factors may include soil moisture, vegetation cover, soil type, and soil pathogens. Because many soil fungi respond to moisture and host species, fungi may mediate environmental drivers of seed survival. Here, I measure patterns of seed survival in California annual grassland plants across 15 species in three experiments. First, I surveyed seed survival for eight species at 18 grasslands and coastal sage scrub sites ranging across coastal and inland Santa Barbara County, California. Species differed in seed survival, and soil moisture and geographic location had the strongest influence on survival. Grasslands had higher survival than coastal sage scrub sites for some species. Second, I used a fungicide addition and exotic grass thatch removal experiment in the field to tease apart the relative impact of fungi, thatch, and their interaction in an invaded grassland. Seed survival was lower in the winter (wet season) than in the summer (dry season), but fungicide improved winter survival. Seed survival varied between species but did not depend on thatch. Third, I manipulated water and fungicide in the laboratory to directly examine the relationship between water, fungi, and survival. Seed survival declined from dry to single watered to continuously watered treatments. Fungicide slightly improved seed survival when seeds were watered once but not continually. Together, these experiments demonstrate an important role of soil moisture, potentially mediated by fungal pathogens, in driving seed survival.
NASA Astrophysics Data System (ADS)
Ding, Jingyi; Zhao, Wenwu; Daryanto, Stefani; Wang, Lixin; Fan, Hao; Feng, Qiang; Wang, Yaping
2017-05-01
Desert riparian forests are the main restored vegetation community in Heihe River basin. They provide critical habitats and a variety of ecosystem services in this arid environment. Since desert riparian forests are also sensitive to disturbance, examining the spatial distribution and temporal variation of these forests and their influencing factors is important to determine the limiting factors of vegetation recovery after long-term restoration. In this study, field experiment and remote sensing data were used to determine the spatial distribution and temporal variation of desert riparian forests and their relationship with the environmental factors. We classified five types of vegetation communities at different distances from the river channel. Community coverage and diversity formed a bimodal pattern, peaking at the distances of 1000 and 3000 m from the river channel. In general, the temporal normalized difference vegetation index (NDVI) trend from 2000 to 2014 was positive at different distances from the river channel, except for the region closest to the river bank (i.e. within 500 m from the river channel), which had been undergoing degradation since 2011. The spatial distribution of desert riparian forests was mainly influenced by the spatial heterogeneity of soil properties (e.g. soil moisture, bulk density and soil particle composition). Meanwhile, while the temporal variation of vegetation was affected by both the spatial heterogeneity of soil properties (e.g. soil moisture and soil particle composition) and to a lesser extent, the temporal variation of water availability (e.g. annual average and variability of groundwater, soil moisture and runoff). Since surface (0-30 cm) and deep (100-200 cm) soil moisture, bulk density and the annual average of soil moisture at 100 cm obtained from the remote sensing data were regarded as major determining factors of community distribution and temporal variation, conservation measures that protect the soil structure and prevent soil moisture depletion (e.g. artificial soil cover and water conveyance channels) were suggested to better protect desert riparian forests under climate change and intensive human disturbance.
NASA Technical Reports Server (NTRS)
Kim, E. J.; Walker, J. P.; Panciera, R.; Kalma, J. D.
2006-01-01
Spatially-distributed soil moisture observations have applications spanning a wide range of spatial resolutions from the very local needs of individual farmers to the progressively larger areas of interest to weather forecasters, water resource managers, and global climate modelers. To date, the most promising approach for space-based remote sensing of soil moisture makes use of passive microwave emission radiometers at L-band frequencies (1-2 GHz). Several soil moisture-sensing satellites have been proposed in recent years, with the European Space Agency's Soil Moisture Ocean Salinity (SMOS) mission scheduled to be launched first in a couple years. While such a microwave-based approach has the advantage of essentially allweather operation, satellite size limits spatial resolution to 10's of km. Whether used at this native resolution or in conjunction with some type of downscaling technique to generate soil moisture estimates on a finer-scale grid, the effects of subpixel spatial variability play a critical role. The soil moisture variability is typically affected by factors such as vegetation, topography, surface roughness, and soil texture. Understanding and these factors is the key to achieving accurate soil moisture retrievals at any scale. Indeed, the ability to compensate for these factors ultimately limits the achievable spatial resolution and/or accuracy of the retrieval. Over the last 20 years, a series of airborne campaigns in the USA have supported the development of algorithms for spaceborne soil moisture retrieval. The most important observations involved imagery from passive microwave radiometers. The early campaigns proved that the retrieval worked for larger and larger footprints, up to satellite-scale footprints. These provided the solid basis for proposing the satellite missions. More recent campaigns have explored other aspects such as retrieval performance through greater amounts of vegetation. All of these campaigns featured extensive ground truth collection over a range of grid spacings, to provide a basis for examining the effects of subpixel variability. However, the native footprint size of the airborne L-band radiometers was always a few hundred meters. During the recently completed (November, 2005) National Airborne Field Experiment (NAFE) campaign in Australia, a compact L-band radiometer was deployed on a small aircraft. This new combination permitted routine observations at native resolutions as high as 60 meters, substantially finer than in previous airborne soil moisture campaigns, as well as satellite footprint areal coverage. The radiometer, the Polarimetric L-band Microwave Radiometer (PLMR) performed extremely well and operations included extensive calibration-related observations. Thus, along with the extensive fine-scale ground truth, the NAFE dataset includes all the ingredients for the first scaling studies involving very-high-native resolution soil moisture observations and the effects of vegetation, roughness, etc. A brief overview of the NAFE will be presented, then examples of the airborne observations with resolutions from 60 m to 1 km will be shown, and early results from scaling studies will be discussed.
A Combined Soil Moisture Product of the Tibetan Plateau using Different Sensors Simultaneously
NASA Astrophysics Data System (ADS)
Zeng, Y.; Dente, L.; Su, B.; Wang, L.
2012-12-01
It is always challenging to find a single satellite-derived soil moisture product that has complete coverage of the Tibetan Plateau for a long time period and is suitable for climate change studies at sub-continental scale. Meanwhile, having a number of independent satellite-derived soil moisture data sets does not mean that it is straightforward to create long-term consistent time series, due to the differences among the data sets related to the different retrieval approaches. Therefore, this study is focused on the development and validation of a simple Bayesian based method to merge/blend different satellite-derived soil moisture data. The merging method was firstly tested over the Maqu region (north-eastern fringe of the Tibetan Plateau), where in situ soil moisture data were collected, for the period from May 2008 to December 2010. The in situ data provided by the 20 monitoring stations in the Maqu region were compared to the AMSR-E soil moisture products by VUA-NASA and the ASCAT soil moisture products by TU Wien, in order to determine bias and standard deviation. It was found that the bias between the satellite and the in situ data varies with seasons. The satellite-derived products were first corrected for the bias and then merged. This is generally caused by notable differences in the represented depth, spatial extent and so on. The systematic bias is affected by the spatial variability and the temporal stability (Dente et al. 2012). The dependence of the bias on season was investigated and identified as the monsoon season only (May-September), in winter only (December - February), and in the period between the monsoon season and winter (March-April, October-November, called the transition season) (Dente et al. 2012, Su et al. 2011). After the date merging procedure, the standard deviations between the satellite and the in situ data reduced from 0.0839 to 0.0622 for ASCAT data, and from 0.0682 to 0.0593 for AMSR-E data. The developed merging method is therefore suitable to provide a more accurate soil moisture product than the AMSR-E and ASCAT products. As the merging method was shown to be promising over the Maqu region, it will be extended to the entire Tibetan Plateau. Then, the combined soil moisture product will be validated over the monitored sites located in Ngari and Naqu regions. References: Dente, L.; Vekerdy, Z.; Wen, J.; Su, Z., (2012) Maqu network for validation of satellite-derived soil moisture products. International Journal of Applied Earth Observation and Geoinformation, 17, 55-65. Su, Z., Wen, J., Dente, L., van der Velde, R. and ... [et al.] (2011) The Tibetan plateau observatory of plateau scale soil moisture and soil temperature, Tibet - Obs, for quantifying uncertainties in coarse resolution satellite and model products. In: Hydrology and earth system sciences (HESS): open access, 15 (2011)7 pp. 2303-2016.
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.
Predicting the response of soil organic matter microbial decomposition to moisture
NASA Astrophysics Data System (ADS)
Chenu, Claire; Garnier, Patricia; Monga, Olivier; Moyano, Fernando; Pot, Valérie; Nunan, Naoise; Coucheney, Elsa; Otten, Wilfred
2014-05-01
Next to temperature, soil moisture is a main driver of soil C and N transformations in soils, because it affects microbial activity and survival. The moisture sensitivity of soil organic matter decay may be a source of uncertainty of similar magnitude to that of the temperature sensitivity and receives much less attention. The basic concepts and mechanisms relating soil water to microorganisms were identified early (i.e. in steady state conditions : direct effects on microbial physiology, diffusion substrates, nutrients, extracellular enzymes, diffusion of oxygen, movement of microorganisms). However, accounting for how moisture controls soil microbial activity remains essentially empirical and poorly accounts for soil characteristics. Soil microorganisms live in a complex 3-D framework of mineral and organic particles defining pores of various sizes, connections with adjacent pores, and with pore walls of contrasted nature, which result in a variety of microhabitats. The water regime to which microorganisms are exposed can be predicted to depend the size and connectivity of pores in which they are located. Furthermore, the spatial distribution of microorganisms as well as that of organic matter is very heterogeneous, determining the diffusion distances between substrates and decomposers. A new generation of pore scale models of C dynamics in soil may challenge the difficulty of modelling such a complex system. These models are based on an explicit representation of soil structure (i.e. soil particles and voids), microorganisms and organic matter localisation. We tested here the ability of such a model to account for changes in microbial respiration with soil moisture. In the model MOSAIC II, soil pore space is described using a sphere network coming from a geometrical modelling algorithm. MicroCT tomography images were used to implement this representation of soil structure. A biological sub-model describes the hydrolysis of insoluble SOM into dissolved organic matter, its assimilation, respiration and microbial mortality. A recent improvement of the model was the description of the diffusion of soluble organic matter. We tested the model using the results from an experiment where a simple substrate (fructose) was decomposed by bacteria within a simple media (sand). Separate incubations in microcosms were carried out using five different bacterial communities at two different moisture conditions corresponding to water potentials of -0.01 and -0.1 bars. We calibrated the biological parameters using the experimental data obtained at high water content and we tested the model without any parameters change at low water content. Both the experiments and simulations showed a decrease in mineralisation with a decrease of water content, of which pattern depended on the bacterial species and its physiological characteristics. The model was able to correctly simulate the decrease of connectivity between substrate and microorganism due the decrease of water content. The potential and required developments of such models in describing how heterotrophic respiration is affected by micro-scale distribution and processes in soils and in testing scenarios regarding water regimes in a changing climate is discussed.
NASA Astrophysics Data System (ADS)
Shrivastava, Sourabh; Kar, Sarat C.; Sharma, Anu Rani
2017-07-01
Variation of soil moisture during active and weak phases of summer monsoon JJAS (June, July, August, and September) is very important for sustenance of the crop and subsequent crop yield. As in situ observations of soil moisture are few or not available, researchers use data derived from remote sensing satellites or global reanalysis. This study documents the intercomparison of soil moisture from remotely sensed and reanalyses during dry spells within monsoon seasons in central India and central Myanmar. Soil moisture data from the European Space Agency (ESA)—Climate Change Initiative (CCI) has been treated as observed data and was compared against soil moisture data from the ECMWF reanalysis-Interim (ERA-I) and the climate forecast system reanalysis (CFSR) for the period of 2002-2011. The ESA soil moisture correlates rather well with observed gridded rainfall. The ESA data indicates that soil moisture increases over India from west to east and from north to south during monsoon season. The ERA-I overestimates the soil moisture over India, while the CFSR soil moisture agrees well with the remotely sensed observation (ESA). Over Myanmar, both the reanalysis overestimate soil moisture values and the ERA-I soil moisture does not show much variability from year to year. Day-to-day variations of soil moisture in central India and central Myanmar during weak monsoon conditions indicate that, because of the rainfall deficiency, the observed (ESA) and the CFSR soil moisture values are reduced up to 0.1 m3/m3 compared to climatological values of more than 0.35 m3/m3. This reduction is not seen in the ERA-I data. Therefore, soil moisture from the CFSR is closer to the ESA observed soil moisture than that from the ERA-I during weak phases of monsoon in the study region.
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...
Role of model structure on the response of soil biogeochemistry to hydro-climatic fluctuations
NASA Astrophysics Data System (ADS)
Manzoni, S.; Porporato, A.
2005-05-01
Soil carbon and nutrient cycles are strongly affected by hydro-climatic variability, which interacts with the internal ecosystem structure. Here we test the implications of biogeochemical model structure on such dynamics by extending an existing model by the authors and coworkers. When forced by hydro-climatic fluctuations, the different model structures induce specific preferential nutrient paths among the soil pools, which in turn affect nutrient distribution and availability to microbes and plants. In particular, if it is assumed that microbes can directly assimilate organic nitrogen, plants tend to be inferior competitors for nutrients even in well-watered conditions, while if a certain amount of organic nitrogen is assumed to be mineralized without being first incorporated into microbial cells, vegetation can be advantaged over a wide range of soil moisture values. We also investigate the intensification of competition for nutrients (e.g., nitrogen) between plant and soil microbial communities under extreme hydrologic conditions, such as droughts and intense storms. Frequent rainfall events may determine ideal soil moisture conditions for plant uptake, enhancing nitrogen leaching while lowering oxygen concentration and inhibiting microbial activity. During droughts, the soil water potential often drops to the point of hampering the plant nutrient uptake while still remaining high enough for microbial decomposition and nitrogen immobilization. The interplay of microbe and vegetation water stress is investigated in depth as it controls the ability of one community (e.g., plants or soil microbes) to establish competitive advantage on the other. The long-term effects of these dynamics of competition and nutrient allocation are explored under steady-state and stochastic soil moisture conditions to analyze the feedbacks between soil organic matter and vegetation dynamics.
On the potential of a multi-temporal AMSR-E data analysis for soil wetness monitoring
NASA Astrophysics Data System (ADS)
Lacava, T.; Coviello, I.; Calice, G.; Mazzeo, G.; Pergola, N.; Tramutoli, V.
2009-12-01
Soil moisture is a critical element for both global water and energy budget. The use of satellite remote sensing data for a characterizations of soil moisture fields at different spatial and temporal scales has more and more increased during last years, thanks also to the new generation of microwave sensors (both active and passive) orbiting around the Earth. Among microwave radiometers which could be used for soil moisture retrieval, the Advanced Microwave Scanning Radiometer on Earth Observing System (AMSR-E), is the one that, for its spectral characteristics, should give more reliable results. The possibility of collect information in five observational bands in the range 6.9 - 89 GHz (with dual polarization), make it currently, waiting for the next ESA Soil Moisture and Ocean Salinity Mission (SMOS - scheduled for September 2009) and the NASA Soil Moisture Active Passive Mission (SMAP - scheduled for 2013), the best radiometer for soil moisture retrieval. Unfortunately, after its launch (AMSR-E is flying aboard EOS-AQUA satellite since 2002) diffuse C-band Radio-Frequency Interferences (RFI) were discovered contaminating AMSR-E radiances over many areas in the world. For this reason, often X-band (less RFI affected) based soil moisture retrieval algorithms, instead of the original based on C-band, have been preferred. As a consequence, the sensitivity of such measurements is decreased, because of the lower penetrating capability of the X band wavelengths than C-band, as well as for their greater noisiness, due to their high sensitivity to the presence of vegetation in the sensor field of view. In order to face all these problems, in this work a general methodology for multi-temporal satellite data analysis (Robust Satellite Techniques, RST) will be used. RST approach, already successfully applied in the framework of hydro-meteorological risk mitigation, should help us in managing AMSR-E data for several purposes. In this paper, in particular, we have looked into the possible improvement, both in terms of quality and reliability, of AMSR-E C-band soil moisture retrieval which, a differential approach like RST, may produce. To reach this aim, a multi-temporal analysis of long-term historical series of AMSR-E C-band data has been performed. Preliminary results of such an analysis will be shown in this work and discussed also by a comparison with the standard AMSR-E soil moisture products, daily provided by NASA. In detail, achievements obtained investigating several flooding events happened in the past over different areas of the world will be presented.
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.
Deposition parameterizations for the Industrial Source Complex (ISC3) model
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wesely, Marvin L.; Doskey, Paul V.; Shannon, J. D.
2002-06-01
Improved algorithms have been developed to simulate the dry and wet deposition of hazardous air pollutants (HAPs) with the Industrial Source Complex version 3 (ISC3) model system. The dry deposition velocities (concentrations divided by downward flux at a specified height) of the gaseous HAPs are modeled with algorithms adapted from existing dry deposition modules. The dry deposition velocities are described in a conventional resistance scheme, for which micrometeorological formulas are applied to describe the aerodynamic resistances above the surface. Pathways to uptake at the ground and in vegetative canopies are depicted with several resistances that are affected by variations inmore » air temperature, humidity, solar irradiance, and soil moisture. The role of soil moisture variations in affecting the uptake of gases through vegetative plant leaf stomata is assessed with the relative available soil moisture, which is estimated with a rudimentary budget of soil moisture content. Some of the procedures and equations are simplified to be commensurate with the type and extent of information on atmospheric and surface conditions available to the ISC3 model system user. For example, standardized land use types and seasonal categories provide sets of resistances to uptake by various components of the surface. To describe the dry deposition of the large number of gaseous organic HAPS, a new technique based on laboratory study results and theoretical considerations has been developed providing a means of evaluating the role of lipid solubility in uptake by the waxy outer cuticle of vegetative plant leaves.« less
NASA Astrophysics Data System (ADS)
Wilton, E.; Flanagan, L. B.
2014-12-01
Soil respiration rate is affected by seasonal changes in temperature and moisture, but is this a direct effect on soil metabolism or an indirect effect caused by changes in microbial biomass, bacterial community composition and substrate availability? In order to address this question, we compared continuous measurements of soil and plant CO2 exchange made with an automatic chamber system to analyses conducted on replicate soil samples collected on four dates during June-August. Microbial biomass was estimated from substrate-induced respiration rate, bacterial community composition was determined by 16S rRNA amplicon pyrosequencing, and β-1,4-N-acetylglucosaminidase (NAGase) and phenol oxidase enzyme activities were assayed fluorometrically or by absorbance measurements, respectively. Soil microbial biomass declined from June to August in strong correlation with a progressive decline in soil moisture during this time period. Soil bacterial species richness and alpha diversity showed no significant seasonal change. However, bacterial community composition showed a progressive shift over time as measured by Bray-Curtis dissimilarity. In particular, the change in community composition was associated with increasing relative abundance in the alpha and delta classes, and declining abundance of the beta and gamma classes of the Proteobacteria phylum during June-August. NAGase showed a progressive seasonal decline in potential activity that was correlated with microbial biomass and seasonal changes in soil moisture. In contrast, phenol oxidase showed highest potential activity in mid-July near the time of peak soil respiration and ecosystem photosynthesis, which may represent a time of high input of carbon exudates into the soil from plant roots. This input of exudates may stimulate the activity of phenol oxidase, a lignolytic enzyme involved in the breakdown of soil organic matter. These analyses indicated that seasonal change in soil respiration is a complex interaction between temporal changes in soil environmental factors and biological changes in the plant and microbial community that affect soil respiratory metabolism.
Evaluation of the validated soil moisture product from the SMAP radiometer
USDA-ARS?s Scientific Manuscript database
In this study, we used a multilinear regression approach to retrieve surface soil moisture from NASA’s Soil Moisture Active Passive (SMAP) satellite data to create a global dataset of surface soil moisture which is consistent with ESA’s Soil Moisture and Ocean Salinity (SMOS) satellite retrieved sur...
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.
Evaluation of SMAP Level 2 Soil Moisture Algorithms Using SMOS Data
NASA Technical Reports Server (NTRS)
Bindlish, Rajat; Jackson, Thomas J.; Zhao, Tianjie; Cosh, Michael; Chan, Steven; O'Neill, Peggy; Njoku, Eni; Colliander, Andreas; Kerr, Yann; Shi, J. C.
2011-01-01
The objectives of the SMAP (Soil Moisture Active Passive) mission are global measurements of soil moisture and land freeze/thaw state at 10 km and 3 km resolution, respectively. SMAP will provide soil moisture with a spatial resolution of 10 km with a 3-day revisit time at an accuracy of 0.04 m3/m3 [1]. In this paper we contribute to the development of the Level 2 soil moisture algorithm that is based on passive microwave observations by exploiting Soil Moisture Ocean Salinity (SMOS) satellite observations and products. SMOS brightness temperatures provide a global real-world, rather than simulated, test input for the SMAP radiometer-only soil moisture algorithm. Output of the potential SMAP algorithms will be compared to both in situ measurements and SMOS soil moisture products. The investigation will result in enhanced SMAP pre-launch algorithms for soil moisture.
Schwerbrock, R; Leuschner, C
2016-07-01
(1) Most ferns are restricted to moist and shady habitats, but it is not known whether soil moisture or atmospheric water status are decisive limiting factors, or if both are equally important. (2) Using the rare temperate woodland fern Polystichum braunii, we conducted a three-factorial climate chamber experiment (soil moisture (SM) × air humidity (RH) × air temperature (T)) to test the hypotheses that: (i) atmospheric water status (RH) exerts a similarly large influence on the fern's biology as soil moisture, and (ii) both a reduction in RH and an increase in air temperature reduce vigour and growth. (3) Nine of 11 morphological, physiological and growth-related traits were significantly influenced by an increase in RH from 65% to 95%, leading to higher leaf conductance, increased above- and belowground productivity, higher fertility, more epidermal trichomes and fewer leaf deformities under high air humidity. In contrast, soil moisture variation (from 66% to 70% in the moist to ca. 42% in the dry treatment) influenced only one trait (specific leaf area), and temperature variation (15 °C versus 19 °C during daytime) only three traits (leaf conductance, root/shoot ratio, specific leaf area); RH was the only factor affecting productivity. (4) This study is the first experimental proof for a soil moisture-independent air humidity effect on the growth of terrestrial woodland ferns. P. braunii appears to be an air humidity hygrophyte that, whithin the range of realistic environmental conditions set in this study, suffers more from a reduction in RH than in soil moisture. A climate warming-related increase in summer temperatures, however, seems not to directly threaten this endangered species. © 2016 German Botanical Society and The Royal Botanical Society of the Netherlands.
Acclimation and soil moisture constrain sugar maple root respiration in experimentally warmed soil.
Jarvi, Mickey P; Burton, Andrew J
2013-09-01
The response of root respiration to warmer soil can affect ecosystem carbon (C) allocation and the strength of positive feedbacks between climatic warming and soil CO2 efflux. This study sought to determine whether fine-root (<1 mm) respiration in a sugar maple (Acer saccharum Marsh.)-dominated northern hardwood forest would adjust to experimentally warmed soil, reducing C return to the atmosphere at the ecosystem scale to levels lower than that would be expected using an exponential temperature response function. Infrared heating lamps were used to warm the soil (+4 to +5 °C) in a mature sugar maple forest in a fully factorial design, including water additions used to offset the effects of warming-induced dry soil. Fine-root-specific respiration rates, root biomass, root nitrogen (N) concentration, soil temperature and soil moisture were measured from 2009 to 2011, with experimental treatments conducted from late 2010 to 2011. Partial acclimation of fine-root respiration to soil warming occurred, with soil moisture deficit further constraining specific respiration rates in heated plots. Fine-root biomass and N concentration remained unchanged. Over the 2011 growing season, ecosystem root respiration was not significantly greater in warmed soil. This result would not be predicted by models that allow respiration to increase exponentially with temperature and do not directly reduce root respiration in drier soil.
Migration of Paraburkholderia terrae BS001 Along Old Fungal Hyphae in Soil at Various pH Levels.
Yang, Pu; Oliveira da Rocha Calixto, Renata; van Elsas, Jan Dirk
2018-01-10
The movement of bacterial cells along with fungal hyphae in soil (the mycosphere) has been reported in several previous studies. However, how local soil conditions affect bacterial migration direction in the mycosphere has not been extensively studied. Here, we investigated the influence of two soil parameters, pH and soil moisture content, on the migration, and survival, of Paraburkholderia terrae BS001 in the mycosphere of Lyophyllum sp. strain Karsten in microcosms containing a loamy sand soil. The data showed that bacterial movement along the hyphal networks took place in both the "forward" and the "backward" directions. Low soil pH strongly restricted bacterial survival, as well as dispersal in both directions, in the mycosphere. The backward movement was weakly correlated with the amount of fungal tissue formed in the old mycelial network. The initial soil moisture content, set at 12 versus 17% (corresponding to 42 and 60% of the soil water holding capacity), also significantly affected the bacterial dispersal along the fungal hyphae. Overall, the presence of fungal hyphae was found to increase the soil pH (under conditions of acidity), which possibly exerted protective effects on the bacterial cells. Finally, we provide a refined model that describes the bacterial migration patterns with fungal hyphae based on the new findings in this study.
NASA Astrophysics Data System (ADS)
Haohao, Wu; Xingkai, Xu; Cuntao, Duan; TuanSheng, Li; Weiguo, Cheng
2017-07-01
Packed soil-core incubation experiments were done to study the effects of carbon (glucose, 6.4 g C m-2) and nitrogen (NH4Cl and KNO3, 4.5 g N m-2) addition on nitrous oxide (N2O) and carbon dioxide (CO2) fluxes during thawing of frozen soils under two forest stands (broadleaf and Korean pine mixed forest and white birch forest) with two moisture levels (55 and 80% water-filled pore space). With increasing soil moisture, the magnitude and longevity of the flush N2O flux from forest soils was enhanced during the early period of thawing, which was accompanied by great NO3--N consumption. Without N addition, the glucose-induced cumulative CO2 fluxes ranged from 9.61 to 13.49 g CO2-C m-2, which was larger than the dose of carbon added as glucose. The single addition of glucose increased microbial biomass carbon but slightly affected soil dissolved organic carbon pool. Thus, the extra carbon released upon addition of glucose can result from the decomposition of soil native organic carbon. The glucose-induced N2O and CO2 fluxes were both significantly correlated to the glucose-induced total N and dissolved organic carbon pools and influenced singly and interactively by soil moisture and KNO3 addition. The interactive effects of glucose and nitrogen inputs on N2O and CO2 fluxes from forest soils after frost depended on N sources, soil moisture, and vegetation types.
NASA Technical Reports Server (NTRS)
Colliander, Andreas; Cosh, Michael H.; Misra, Sidharth; Jackson, Thomas J.; Crow, Wade T.; Chan, Steven; Bindlish, Rajat; Chae, Chun; Holifield Collins, Chandra; Yueh, Simon H.
2017-01-01
The NASA SMAP (Soil Moisture Active Passive) mission conducted the SMAP Validation Experiment 2015 (SMAPVEX15) in order to support the calibration and validation activities of SMAP soil moisture data products. The main goals of the experiment were to address issues regarding the spatial disaggregation methodologies for improvement of soil moisture products and validation of the in situ measurement upscaling techniques. To support these objectives high-resolution soil moisture maps were acquired with the airborne PALS (Passive Active L-band Sensor) instrument over an area in southeast Arizona that includes the Walnut Gulch Experimental Watershed (WGEW), and intensive ground sampling was carried out to augment the permanent in situ instrumentation. The objective of the paper was to establish the correspondence and relationship between the highly heterogeneous spatial distribution of soil moisture on the ground and the coarse resolution radiometer-based soil moisture retrievals of SMAP. The high-resolution mapping conducted with PALS provided the required connection between the in situ measurements and SMAP retrievals. The in situ measurements were used to validate the PALS soil moisture acquired at 1-km resolution. Based on the information from a dense network of rain gauges in the study area, the in situ soil moisture measurements did not capture all the precipitation events accurately. That is, the PALS and SMAP soil moisture estimates responded to precipitation events detected by rain gauges, which were in some cases not detected by the in situ soil moisture sensors. It was also concluded that the spatial distribution of the soil moisture resulted from the relatively small spatial extents of the typical convective storms in this region was not completely captured with the in situ stations. After removing those cases (approximately10 of the observations) the following metrics were obtained: RMSD (root mean square difference) of0.016m3m3 and correlation of 0.83. The PALS soil moisture was also compared to SMAP and in situ soil moisture at the 36-km scale, which is the SMAP grid size for the standard product. PALS and SMAP soil moistures were found to be very similar owing to the close match of the brightness temperature measurements and the use of a common soil moisture retrieval algorithm. Spatial heterogeneity, which was identified using the high-resolution PALS soil moisture and the intensive ground sampling, also contributed to differences between the soil moisture estimates. In general, discrepancies found between the L-band soil moisture estimates and the 5-cm depth in situ measurements require methodologies to mitigate the impact on their interpretations in soil moisture validation and algorithm development. Specifically, the metrics computed for the SMAP radiometer-based soil moisture product over WGEW will include errors resulting from rainfall, particularly during the monsoon season when the spatial distribution of soil moisture is especially heterogeneous.
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.
Impact of SMOS soil moisture data assimilation on NCEP-GFS forecasts
NASA Astrophysics Data System (ADS)
Zhan, X.; Zheng, W.; Meng, J.; Dong, J.; Ek, M.
2012-04-01
Soil moisture is one of the few critical land surface state variables that have long memory to impact the exchanges of water, energy and carbon between the land surface and atmosphere. Accurate information about soil moisture status is thus required for numerical weather, seasonal climate and hydrological forecast as well as for agricultural production forecasts, water management and many other water related economic or social activities. Since the successful launch of ESA's soil moisture ocean salinity (SMOS) mission in November 2009, about 2 years of soil moisture retrievals has been collected. SMOS is believed to be the currently best satellite sensors for soil moisture remote sensing. Therefore, it becomes interesting to examine how the collected SMOS soil moisture data are compared with other satellite-sensed soil moisture retrievals (such as NASA's Advanced Microwave Scanning Radiometer -AMSR-E and EUMETSAT's Advanced Scatterometer - ASCAT)), in situ soil moisture measurements, and how these data sets impact numerical weather prediction models such as the Global Forecast System of NOAA-NCEP. This study implements the Ensemble Kalman filter in GFS to assimilate the AMSR-E, ASCAT and SMOS soil moisture observations after a quantitative assessment of their error rate based on in situ measurements from ground networks around contiguous United States. in situ soil moisture measurements from ground networks (such as USDA Soil Climate Analysis network - SCAN and NOAA's U.S. Climate Reference Network -USCRN) are used to evaluate the GFS soil moisture simulations (analysis). The benefits and uncertainties of assimilating the satellite data products in GFS are examined by comparing the GFS forecasts of surface temperature and rainfall with and without the assimilations. From these examinations, the advantages of SMOS soil moisture data products over other satellite soil moisture data sets will be evaluated. The next step toward operationally assimilating soil moisture and other land observations into GFS will also be discussed.
NASA Astrophysics Data System (ADS)
Ciabatta, Luca; Brocca, Luca; Ponziani, Francesco; Berni, Nicola; Stelluti, Marco; Moramarco, Tommaso
2014-05-01
The Umbria Region, located in Central Italy, is one of the most landslide risk prone area in Italy, almost yearly affected by landslides events at different spatial scales. For early warning procedures aimed at the assessment of the hydrogeological risk, the rainfall thresholds represent the main tool for the Italian Civil Protection System. As shown in previous studies, soil moisture plays a key-role in landslides triggering. In fact, acting on the pore water pressure, soil moisture influences the rainfall amount needed for activating a landslide. In this work, an operational physically-based early warning system, named PRESSCA, that takes into account soil moisture for the definition of rainfall thresholds is presented. Specifically, the soil moisture conditions are evaluated in PRESSCA by using a distributed soil water balance model that is recently coupled with near real-time satellite soil moisture product obtained from ASCAT (Advanced SCATterometer) and from in-situ monitoring data. The integration of three different sources of soil moisture information allows to estimate the most accurate possible soil moisture condition. Then, both observed and forecasted rainfall data are compared with the soil moisture-based thresholds in order to obtain risk indicators over a grid of ~ 5 km. These indicators are then used for the daily hydrogeological risk evaluation and management by the Civil Protection regional service, through the sharing/delivering of near real-time landslide risk scenarios (also through an open source web platform: www.cfumbria.it). On the 11th-12th November, 2013, Umbria Region was hit by an exceptional rainfall event with up to 430mm/72hours that resulted in significant economic damages, but fortunately no casualties among the population. In this study, the results during the rainfall event of PRESSCA system are described, by underlining the model capability to reproduce, two days in advance, landslide risk scenarios in good spatial and temporal agreement with the occurred actual conditions. High-resolution risk scenarios (100mx100m), obtained by coupling PRESSCA forecasts with susceptibility and vulnerability layers, are also produced. The results show good relationship between the PRESSCA forecast and the reported landslides to the Civil Protection Service during the rainfall event, confirming the system robustness. The good forecasts of PRESSCA system have surely contributed to start well in advance the Civil Protection operations (alerting local authorities and population).
NASA Astrophysics Data System (ADS)
Singh, Gurjeet; Panda, Rabindra K.; Mohanty, Binayak P.; Jana, Raghavendra B.
2016-05-01
Strategic ground-based sampling of soil moisture across multiple scales is necessary to validate remotely sensed quantities such as NASA's Soil Moisture Active Passive (SMAP) product. In the present study, in-situ soil moisture data were collected at two nested scale extents (0.5 km and 3 km) to understand the trend of soil moisture variability across these scales. This ground-based soil moisture sampling was conducted in the 500 km2 Rana watershed situated in eastern India. The study area is characterized as sub-humid, sub-tropical climate with average annual rainfall of about 1456 mm. Three 3x3 km square grids were sampled intensively once a day at 49 locations each, at a spacing of 0.5 km. These intensive sampling locations were selected on the basis of different topography, soil properties and vegetation characteristics. In addition, measurements were also made at 9 locations around each intensive sampling grid at 3 km spacing to cover a 9x9 km square grid. Intensive fine scale soil moisture sampling as well as coarser scale samplings were made using both impedance probes and gravimetric analyses in the study watershed. The ground-based soil moisture samplings were conducted during the day, concurrent with the SMAP descending overpass. Analysis of soil moisture spatial variability in terms of areal mean soil moisture and the statistics of higher-order moments, i.e., the standard deviation, and the coefficient of variation are presented. Results showed that the standard deviation and coefficient of variation of measured soil moisture decreased with extent scale by increasing mean soil moisture.
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.
NASA Astrophysics Data System (ADS)
Fu, X.; Dai, X.; Wang, H.
2015-12-01
Knowledge of the fine root dynamics of different life forms in forest ecosystems is critical to understanding how the overall belowground carbon cycling is affected by climate change. However, our current knowledge regarding how endogenous or exogenous factors regulate the root dynamics of understory vegetation is limited. We selected a suite of study sites representing different habitats with gradients of soil moisture and solar radiation (shading or no shading). We assessed the fine root production phenology, the total fine root production, and the turnover among six understory shrub species in a subtropical climate, and examined the responses of the fine root dynamics to gradients in the soil moisture and solar radiation. The shrubs included three evergreen species, Loropetalum chinense, Vaccinium bracteatum, and Adinandra millettii, and three deciduous species, Serissa serissoides, Rubus corchorifolius, and Lespedeza davidii. We observed that variations in the annual fine root production and turnover among species were significant in the deciduous group but not in the evergreen group. Notably, V. bracteatum and S. serissoides presented the greatest responses in terms of root phenology to gradients in the soil moisture and shading: high-moisture habitat led to a decrease and shade led to an increase in fine root production during spring. Species with smaller fine roots of the 1st+2nd-order diameter presented more sensitive responses in terms of fine root phenology to a soil moisture gradient. Species with a higher fine root nitrogen-to -carbon ratio exhibited more sensitive responses in terms of fine root annual production to shading. Soil moisture and shading did not change the annual fine root production as much as the turnover rate. The fine root dynamics of some understory shrubs varied significantly with soil moisture and solar radiation status and may be different from tree species. Our results emphasize the need to study the understory fine root dynamics in the achievement of a complete understanding of the overall belowground carbon cycling in a forest ecosystem, particularly ecosystems in which the understory fine root highly contributes to the belowground biomass.
Using satellite image data to estimate soil moisture
NASA Astrophysics Data System (ADS)
Chuang, Chi-Hung; Yu, Hwa-Lung
2017-04-01
Soil moisture is considered as an important parameter in various study fields, such as hydrology, phenology, and agriculture. In hydrology, soil moisture is an significant parameter to decide how much rainfall that will infiltrate into permeable layer and become groundwater resource. Although soil moisture is a critical role in many environmental studies, so far the measurement of soil moisture is using ground instrument such as electromagnetic soil moisture sensor. Use of ground instrumentation can directly obtain the information, but the instrument needs maintenance and consume manpower to operation. If we need wide range region information, ground instrumentation probably is not suitable. To measure wide region soil moisture information, we need other method to achieve this purpose. Satellite remote sensing techniques can obtain satellite image on Earth, this can be a way to solve the spatial restriction on instrument measurement. In this study, we used MODIS data to retrieve daily soil moisture pattern estimation, i.e., crop water stress index (cwsi), over the year of 2015. The estimations are compared with the observations at the soil moisture stations from Taiwan Bureau of soil and water conservation. Results show that the satellite remote sensing data can be helpful to the soil moisture estimation. Further analysis can be required to obtain the optimal parameters for soil moisture estimation in Taiwan.
Using Remotely Sensed Soil Moisture to Estimate Fire Risk in Tropical Peatlands
NASA Astrophysics Data System (ADS)
Dadap, N.; Cobb, A.; Hoyt, A.; Harvey, C. F.; Konings, A. G.
2017-12-01
Tropical peatlands in Equatorial Asia have become more vulnerable to fire due to deforestation and peatland drainage over the last 30 years. In these regions, water table depth has been shown to play an important role in mediating fire risk as it serves as a proxy for peat moisture content. However, water table depth observations are sparse and expensive. Soil moisture could provide a more direct indicator of fire risk than water table depth. In this study, we use new soil moisture retrievals from the Soil Moisture Active Passive (SMAP) satellite to demonstrate that - contrary to popular wisdom - remotely sensed soil moisture observations are possible over most Southeast Asian peatlands. Soil moisture estimation in this region was previously thought to be impossible over tropical peatlands because of dense vegetation cover. We show that vegetation density is sufficiently low across most Equatorial Asian peatlands to allow soil moisture estimation, and hypothesize that deforestation and other anthropogenic changes in land cover have combined to reduce overall vegetation density sufficient to allow soil moisture estimation. We further combine burned area estimates from the Global Fire Emissions Database and SMAP soil moisture retrievals to show that soil moisture provides a strong signal for fire risk in peatlands, with fires occurring at a much greater rate over drier soils. We will also develop an explicit fire risk model incorporating soil moisture with additional climatic, land cover, and anthropogenic predictor variables.
NASA Astrophysics Data System (ADS)
Khodayar, S.; Sehlinger, A.; Feldmann, H.; Kottmeier, C.
2015-12-01
The impact of soil initialization is investigated through perturbation simulations with the regional climate model COSMO-CLM. The focus of the investigation is to assess the sensitivity of simulated extreme periods, dry and wet, to soil moisture initialization in different climatic regions over Europe and to establish the necessary spin up time within the framework of decadal predictions for these regions. Sensitivity experiments consisted of a reference simulation from 1968 to 1999 and 5 simulations from 1972 to 1983. The Effective Drought Index (EDI) is used to select and quantify drought status in the reference run to establish the simulation time period for the sensitivity experiments. Different soil initialization procedures are investigated. The sensitivity of the decadal predictions to soil moisture initial conditions is investigated through the analysis of water cycle components' (WCC) variability. In an episodic time scale the local effects of soil moisture on the boundary-layer and the propagated effects on the large-scale dynamics are analysed. The results show: (a) COSMO-CLM reproduces the observed features of the drought index. (b) Soil moisture initialization exerts a relevant impact on WCC, e.g., precipitation distribution and intensity. (c) Regional characteristics strongly impact the response of the WCC. Precipitation and evapotranspiration deviations are larger for humid regions. (d) The initial soil conditions (wet/dry), the regional characteristics (humid/dry) and the annual period (wet/dry) play a key role in the time that soil needs to restore quasi-equilibrium and the impact on the atmospheric conditions. Humid areas, and for all regions, a humid initialization, exhibit shorter spin up times, also soil reacts more sensitive when initialised during dry periods. (e) The initial soil perturbation may markedly modify atmospheric pressure field, wind circulation systems and atmospheric water vapour distribution affecting atmospheric stability conditions, thus modifying precipitation intensity and distribution even several years after the initialization.
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)
Hunt, E. D.; Otkin, J.; Zhong, Y.
2017-12-01
Flash drought, characterized by the rapid onset of abnormally warm and dry weather conditions that leads to the rapid depletion of soil moisture and rapid deteriorations in vegetation health. Flash recovery, on the other hand, is characterized by a period(s) of intense precipitation where drought conditions are quickly eradicated and may be replaced by saturated soils and flooding. Both flash drought and flash recovery are closely tied to the rapid depletion or recharge of root zone soil moisture; therefore, soil moisture observations are very useful for monitoring their evolution. However, in-situ soil moisture observations tend to be concentrated over small regions and thus other methods are needed to provide a spatially continuous depiction of soil moisture conditions. One option is to use top soil moisture retrievals from the Soil Moisture Active Passive (SMAP) sensor. SMAP provides routine coverage of surface soil moisture (0-5 cm) over most of the globe, including the timespan (2015) and region of interest (Texas) that are the focus of our study. This region had an unusual sequence of flash recovery-flash drought-flash recovery during an six-month period during 2015 that provides a valuable case study of rapid transitions between extreme soil moisture conditions. During this project, SMAP soil moisture retrievals are being used in combination with in-situ soil moisture observations and assimilated into the Land Information System (LIS) to provide information about soil moisture content. LIS also provides greenness vegetation fraction data over large regions. The relationship between soil moisture and vegetation conditions and the response of the vegetation to the rapidly changing conditions are also assessed using the satellite thermal infrared based Evaporative Stress Index (ESI) that depicts anomalies in evapotranspiration, along with other vegetation datasets (leaf area index, greenness fraction) derived using MODIS observations. Preliminary results with the Noah land surface model (inside of LIS) shows that it broadly captured the soil moisture evolution during the 2015 sequence but tended to underestimate the magnitude of soil moisture anomalies. The ESI also showed negative anomalies during the drought. These and other results will be presented at the annual meeting.
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.
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.
Moisture-strength-constructability guidelines for subgrade foundation soils found in Indiana.
DOT National Transportation Integrated Search
2016-09-01
Soil moisture is an important indicator of constructability in the field. Construction activities become difficult when the soil moisture content is excessive, especially in fine-grained soils. Change orders caused by excessive soil moisture during c...
Gee, Hugo K.W.; King, Sammy L.; Keim, Richard F.
2015-01-01
We used tree-ring analysis to examine radial growth response of a common, moderately flood-tolerant species (Fraxinus pennsylvanica Marshall) to hydrologic and climatic variability for > 40 years before and after hydrologic modifications affecting two forest stands in the Mississippi River Alluvial Valley (USA): a stand without levees below dams and a stand within a ring levee. At the stand without levees below dams, spring flood stages decreased and overall growth increased after dam construction, which we attribute to a reduction in flood stress. At the stand within a ring levee, growth responded to the elimination of overbank flooding by shifting from being positively correlated with river stage to not being correlated with river stage. In general, growth in swales was positively correlated with river stage and Palmer Drought Severity Index (an index of soil moisture) for longer periods than flats. Growth decreased after levee construction, but swales were less impacted than flats likely because of differences in elevation and soils provide higher soil moisture. Results of this study indicate that broad-scale hydrologic processes differ in their effects on the flood regime, and the effects on growth of moderately flood-tolerant species such as F. pennsylvanica can be mediated by local-scale factors such as topographic position, which affects soil moisture.
NASA Astrophysics Data System (ADS)
Zhang, Sibo; Calvet, Jean-Christophe; Darrozes, José; Roussel, Nicolas; Frappart, Frédéric; Bouhours, Gilles
2018-03-01
This work assesses the estimation of surface volumetric soil moisture (VSM) using the global navigation satellite system interferometric reflectometry (GNSS-IR) technique. Year-round observations were acquired from a grassland site in southwestern France using an antenna consecutively placed at two contrasting heights above the ground surface (3.3 and 29.4 m). The VSM retrievals are compared with two independent reference datasets: in situ observations of soil moisture, and numerical simulations of soil moisture and vegetation biomass from the ISBA (Interactions between Soil, Biosphere and Atmosphere) land surface model. Scaled VSM estimates can be retrieved throughout the year removing vegetation effects by the separation of growth and senescence periods and by the filtering of the GNSS-IR observations that are most affected by vegetation. Antenna height has no significant impact on the quality of VSM estimates. Comparisons between the VSM GNSS-IR retrievals and the in situ VSM observations at a depth of 5 cm show good agreement (R2 = 0.86 and RMSE = 0.04 m3 m-3). It is shown that the signal is sensitive to the grass litter water content and that this effect triggers differences between VSM retrievals and in situ VSM observations at depths of 1 and 5 cm, especially during light rainfall events.
Vasileiadis, Sotirios; Coppolecchia, Damiano; Puglisi, Edoardo; Balloi, Annalisa; Mapelli, Francesca; Hamon, Rebecca E; Daffonchio, Daniele; Trevisan, Marco
2012-11-01
Ammonia oxidation has been intensively studied for its sensitivity to environmental shifts and stresses. However, acute stress effects on the occurrence and composition of ammonia oxidizing bacteria (AOB) and archaea (AOA) based on expression of related molecular markers in complex soil environments have been to an extent overlooked, particularly concerning transient but commonly occurring environmental changes like soil moisture shifts. The present study investigates the responses of AOB and AOA to moisture shifts and high Zn soil content. AmoA gene copies and transcripts of AOB and AOA along with potential nitrification activity were measured in a soil microcosm approach for investigating the referred environmental shifts. Moisture change from 87 to 50 % of the water holding capacity caused a ~99 % reduction of AOB but not of AOA amoA transcripts that did not change significantly. Increasing applied zinc concentrations resulted in a reduction of potential nitrification rates and negatively affected studied gene expressions of both AOB and AOA, with AOB being more responsive. Both 16 S rRNA and amoA transcripts of AOB had an inverse relation to the applied zinc, indicating a gradual loss in total cell activity. Our results suggest the existence of pronounced differences between AOB and AOA concerning ammonia oxidation activity.
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.
Chen, Jie; Xu, Qing; Gao, De Qiang; Ma, Ying Bin; Zhang, Bei Bei; Hao, Yu Guang
2017-07-18
Understanding the soil-profile temporal and spatial distribution of rainwater in arid and semiarid regions provides a scientific basis for the restoration and maintenance of degraded desert ecosystems in the West Ordos Desert of Inner Mongolia, China. In this study, the deuterium isotope (δD) value of rainwater, soil water, and groundwater were examined in the West Ordos Desert. The contribution of precipitation to soil water in each layer of the soil profile was calculated with two-end linear mixed model. In addition, the temporal and spatial distribution of δD of soil water in the soil profile was analyzed under different-intensity precipitation. The results showed that small rainfall events (0-10 mm) affected the soil moisture and the δD value of soil water in surface soil (0-10 cm). About 30.3% to 87.9% of rainwater was kept in surface soil for nine days following the rainfall event. Medium rainfall events (10-20 mm) influenced the soil moisture and the δD value of soil water at soil depth of 0-40 cm. About 28.2% to 80.8% of rainwater was kept in soil layer of 0-40 cm for nine days following the medium rainfall event. Large (20-30 mm) and extremely large (>30 mm) rainfall events considerably influenced the soil moisture and δD value of soil water in each of the soil layers, except for the 100-150 cm layer. The δD value of soil water was between those δD values of rainwater and groundwater, which suggested that precipitation and groundwater were the sources of soil water in the West Ordos Desert. Under the same intensity rainfall, the δD value of surface soil water (0-10 cm) was directly affected by δD of rainwater. With increasing soil depth, the variation of soil water δD decreased, and the soil water of 100-150 cm kept stable. With increasing intensity of precipitation, the influence of precipitation on soil water δD lasted for a longer duration and occurred at a deeper soil depth.
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.
Wang, Shuai; Fu, Bojie; Gao, Guangyao; Zhou, Ji; Jiao, Lei; Liu, Jianbo
2015-12-01
Soil moisture pulses are a prerequisite for other land surface pulses at various spatiotemporal scales in arid and semi-arid areas. The temporal dynamics and profile variability of soil moisture in relation to land cover combinations were studied along five slopes transect on the Loess Plateau during the rainy season of 2011. Within the 3 months of the growing season coupled with the rainy season, all of the soil moisture was replenished in the area, proving that a type stability exists between different land cover soil moisture levels. Land cover combinations disturbed the trend determined by topography and increased soil moisture variability in space and time. The stability of soil moisture resulting from the dynamic processes could produce stable patterns on the slopes. The relationships between the mean soil moisture and vertical standard deviation (SD) and coefficient of variation (CV) were more complex, largely due to the fact that different land cover types had distinctive vertical patterns of soil moisture. The spatial SD of each layer had a positive correlation and the spatial CV exhibited a negative correlation with the increase in mean soil moisture. The soil moisture stability implies that sampling comparisons in this area can be conducted at different times to accurately compare different land use types.
Wang, Zheng Ning; Wang, Xin Ping; Liu, Bo
2016-03-01
Rainfall partitioning by desert shrub canopy modifies the redistribution of incident rainfall under the canopy, and may affect the distribution pattern of soil moisture around the plant. This study examined the distribution of rainfall and the response of soil moisture beneath the canopy of two dominant desert shrubs, Caragana korshinskii and Artemisia ordosica, in the revegetation area at the southeastern edge of the Tengger Desert. The results showed that throughfall and stemflow ave-ragely occupied 74.4%, 11.3% and 61.8%, 5.5% of the gross precipitation for C. korshinskii and A. ordosica, respectively. The mean coefficients of variation (CV) of throughfall were 0.25 and 0.30, respectively. C. korshinski were more efficient than A. ordosica on stemflow generation. The depth of soil wetting front around the stem area was greater than other areas under shrub canopy for C. korshinski, and it was only significantly greater under bigger rain events for A. ordosica. The shrub canopy could cause the unevenness of soil wetting front under the canopy in consequence of rainfall redistribution induced by xerophytic shrub.
NASA Astrophysics Data System (ADS)
Onojeghuo, A. R.; Balzter, H.; Monks, P. S.
2015-12-01
West Africa is a region with six different climatic zones including a rich savannah affected by biomass burning annually, the Niger delta oil producing region with major gas flaring sites and a long coastline. Research on atmospheric pollution using remotely sensed data over West Africa has mostly been conducted at regional scale or for individual countries, with little emphasis on the dynamics of climatic zones and the diversity of land cover types. This study analyses annual seasonal dynamics of emissions of two ozone precursors stratified by climatic zone: nitrogen dioxide (NO2) from OMI and carbon monoxide (CO) from TES. The different sources of these pollutants and their seasonality are explicitly considered. Results indicate that the highest annual wet season NO2 column concentrations were in the semi-arid zone (1.33 x 1015 molecules cm-2) after prolonged periods of low soil moisture while the highest dry season were observed in the wet sub-humid zone (2.62 x 1015 molecules cm-2) where the savannah fires occur annually. The highest annual CO concentrations (> 3.1 x 1018 molecules cm-2) were from the Niger Delta, located in the humid zone. There were indications of atmospheric transport of CO from the southern hemisphere in the west season. Climate change induced soil moisture variability was most prominent in the dry sub-humid and semi-arid climatic zones (±0.015m3m-3) . The causal effects of soil moisture variability on NO2 emissions and their seasonal cycles were tested using the Granger causality test. Causal effects of inter-zonal exchanges/transport of NO2 and CO emissions respectively were inferred using Directed Acyclic Graphs. The results indicate that NO2, CO and their seasonal ratios are strongly affected by changes in soil moisture.
Temperature Effects on Biomass and Regeneration of Vegetation in a Geothermal Area
Nishar, Abdul; Bader, Martin K.-F.; O’Gorman, Eoin J.; Deng, Jieyu; Breen, Barbara; Leuzinger, Sebastian
2017-01-01
Understanding the effects of increasing temperature is central in explaining the effects of climate change on vegetation. Here, we investigate how warming affects vegetation regeneration and root biomass and if there is an interactive effect of warming with other environmental variables. We also examine if geothermal warming effects on vegetation regeneration and root biomass can be used in climate change experiments. Monitoring plots were arranged in a grid across the study area to cover a range of soil temperatures. The plots were cleared of vegetation and root-free ingrowth cores were installed to assess above and below-ground regeneration rates. Temperature sensors were buried in the plots for continued soil temperature monitoring. Soil moisture, pH, and soil chemistry of the plots were also recorded. Data were analyzed using least absolute shrinkage and selection operator and linear regression to identify the environmental variable with the greatest influence on vegetation regeneration and root biomass. There was lower root biomass and slower vegetation regeneration in high temperature plots. Soil temperature was positively correlated with soil moisture and negatively correlated with soil pH. Iron and sulfate were present in the soil in the highest quantities compared to other measured soil chemicals and had a strong positive relationship with soil temperature. Our findings suggest that soil temperature had a major impact on root biomass and vegetation regeneration. In geothermal fields, vegetation establishment and growth can be restricted by low soil moisture, low soil pH, and an imbalance in soil chemistry. The correlation between soil moisture, pH, chemistry, and plant regeneration was chiefly driven by soil temperature. Soil temperature was negatively correlated to the distance from the geothermal features. Apart from characterizing plant regeneration on geothermal soils, this study further demonstrates a novel approach to global warming experiments, which could be particularly useful in low heat flow geothermal systems that more realistically mimic soil warming. PMID:28326088
Temperature Effects on Biomass and Regeneration of Vegetation in a Geothermal Area.
Nishar, Abdul; Bader, Martin K-F; O'Gorman, Eoin J; Deng, Jieyu; Breen, Barbara; Leuzinger, Sebastian
2017-01-01
Understanding the effects of increasing temperature is central in explaining the effects of climate change on vegetation. Here, we investigate how warming affects vegetation regeneration and root biomass and if there is an interactive effect of warming with other environmental variables. We also examine if geothermal warming effects on vegetation regeneration and root biomass can be used in climate change experiments. Monitoring plots were arranged in a grid across the study area to cover a range of soil temperatures. The plots were cleared of vegetation and root-free ingrowth cores were installed to assess above and below-ground regeneration rates. Temperature sensors were buried in the plots for continued soil temperature monitoring. Soil moisture, pH, and soil chemistry of the plots were also recorded. Data were analyzed using least absolute shrinkage and selection operator and linear regression to identify the environmental variable with the greatest influence on vegetation regeneration and root biomass. There was lower root biomass and slower vegetation regeneration in high temperature plots. Soil temperature was positively correlated with soil moisture and negatively correlated with soil pH. Iron and sulfate were present in the soil in the highest quantities compared to other measured soil chemicals and had a strong positive relationship with soil temperature. Our findings suggest that soil temperature had a major impact on root biomass and vegetation regeneration. In geothermal fields, vegetation establishment and growth can be restricted by low soil moisture, low soil pH, and an imbalance in soil chemistry. The correlation between soil moisture, pH, chemistry, and plant regeneration was chiefly driven by soil temperature. Soil temperature was negatively correlated to the distance from the geothermal features. Apart from characterizing plant regeneration on geothermal soils, this study further demonstrates a novel approach to global warming experiments, which could be particularly useful in low heat flow geothermal systems that more realistically mimic soil warming.
Global Soil Moisture from the Aquarius/SAC-D Satellite: Description and Initial Assessment
NASA Technical Reports Server (NTRS)
Bindlish, Rajat; Jackson, Thomas; Cosh, Michael; Zhao, Tianjie; O'Neil, Peggy
2015-01-01
Aquarius satellite observations over land offer a new resource for measuring soil moisture from space. Although Aquarius was designed for ocean salinity mapping, our objective in this investigation is to exploit the large amount of land observations that Aquarius acquires and extend the mission scope to include the retrieval of surface soil moisture. The soil moisture retrieval algorithm development focused on using only the radiometer data because of the extensive heritage of passive microwave retrieval of soil moisture. The single channel algorithm (SCA) was implemented using the Aquarius observations to estimate surface soil moisture. Aquarius radiometer observations from three beams (after bias/gain modification) along with the National Centers for Environmental Prediction model forecast surface temperatures were then used to retrieve soil moisture. Ancillary data inputs required for using the SCA are vegetation water content, land surface temperature, and several soil and vegetation parameters based on land cover classes. The resulting global spatial patterns of soil moisture were consistent with the precipitation climatology and with soil moisture from other satellite missions (Advanced Microwave Scanning Radiometer for the Earth Observing System and Soil Moisture Ocean Salinity). Initial assessments were performed using in situ observations from the U.S. Department of Agriculture Little Washita and Little River watershed soil moisture networks. Results showed good performance by the algorithm for these land surface conditions for the period of August 2011-June 2013 (rmse = 0.031 m(exp 3)/m(exp 3), Bias = -0.007 m(exp 3)/m(exp 3), and R = 0.855). This radiometer-only soil moisture product will serve as a baseline for continuing research on both active and combined passive-active soil moisture algorithms. The products are routinely available through the National Aeronautics and Space Administration data archive at the National Snow and Ice Data Center.
NASA Astrophysics Data System (ADS)
Davis, M. L.; Konkel, J.; Welker, J. M.; Schaeffer, S. M.
2017-12-01
Soil moisture and soil temperature are critical to plant community distribution and soil carbon cycle processes in High Arctic tundra. As environmental drivers of soil biochemical processes, the predictability of soil moisture and soil temperature by vegetation zone in High Arctic landscapes has significant implications for the use of satellite imagery and vegetation distribution maps to estimate of soil gas flux rates. During the 2017 growing season, we monitored soil moisture and soil temperature weekly at 48 sites in dry tundra, moist tundra, and wet grassland vegetation zones in a High Arctic lake basin. Soil temperature in all three communities reflected fluctuations in air temperature throughout the season. Mean soil temperature was highest in the dry tundra community at 10.5±0.6ºC, however, did not differ between moist tundra and wet grassland communities (2.7±0.6 and 3.1±0.5ºC, respectively). Mean volumetric soil moisture differed significantly among all three plant communities with the lowest and highest soil moisture measured in the dry tundra and wet grassland (30±1.2 and 65±2.7%), respectively. For all three communities, soil moisture was highest during the early season snow melt. Soil moisture in wet grassland remained high with no significant change throughout the season, while significant drying occurred in dry tundra. The most significant change in soil moisture was measured in moist tundra, ranging from 61 to 35%. Our results show different gradients in soil moisture variability within each plant community where: 1) soil moisture was lowest in dry tundra with little change, 2) highest in wet grassland with negligible change, and 3) variable in moist tundra which slowly dried but remained moist. Consistently high soil moisture in wet grassland restricts this plant community to areas with no significant drying during summer. The moist tundra occupies the intermediary areas between wet grassland and dry tundra and experiences the widest range of soil moisture variability. As climate projections predict wetter summers in the High Arctic, expansion of areas with seasonally inundated soils and increased soil moisture variability could result in an expansion of wet grassland and moist tundra communities with a commensurate decrease in dry tundra area.
Response of spectral vegetation indices to soil moisture in grasslands and shrublands
Zhang, Li; Ji, Lei; Wylie, Bruce K.
2011-01-01
The relationships between satellite-derived vegetation indices (VIs) and soil moisture are complicated because of the time lag of the vegetation response to soil moisture. In this study, we used a distributed lag regression model to evaluate the lag responses of VIs to soil moisture for grasslands and shrublands at Soil Climate Analysis Network sites in the central and western United States. We examined the relationships between Moderate Resolution Imaging Spectroradiometer (MODIS)-derived VIs and soil moisture measurements. The Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) showed significant lag responses to soil moisture. The lag length varies from 8 to 56 days for NDVI and from 16 to 56 days for NDWI. However, the lag response of NDVI and NDWI to soil moisture varied among the sites. Our study suggests that the lag effect needs to be taken into consideration when the VIs are used to estimate soil moisture.
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)
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.
Bitterlich, Michael; Sandmann, Martin; Graefe, Jan
2018-01-01
Arbuscular mycorrhizal fungi (AMF) proliferate in soil pores, on the surface of soil particles and affect soil structure. Although modifications in substrate moisture retention depend on structure and could influence plant water extraction, mycorrhizal impacts on water retention and hydraulic conductivity were rarely quantified. Hence, we asked whether inoculation with AMF affects substrate water retention, water transport properties and at which drought intensity those factors become limiting for plant transpiration. Solanum lycopersicum plants were set up in the glasshouse, inoculated or not with Funneliformis mosseae , and grown for 35 days under ample water supply. After mycorrhizal establishment, we harvested three sets of plants, one before (36 days after inoculation) and the second (day 42) and third (day 47) within a sequential drying episode. Sampling cores were introduced into pots before planting. After harvest, moisture retention and substrate conductivity properties were assessed and water retention and hydraulic conductivity models were fitted. A root water uptake model was adopted in order to identify the critical substrate moisture that induces soil derived transpiration limitation. Neither substrate porosity nor saturated water contents were affected by inoculation, but both declined after substrates dried. Drying also caused a decline in pot water capacity and hydraulic conductivity. Plant available water contents under wet (pF 1.8-4.2) and dry (pF 2.5-4.2) conditions increased in mycorrhizal substrates and were conserved after drying. Substrate hydraulic conductivity was higher in mycorrhizal pots before and during drought exposure. After withholding water from pots, higher substrate drying rates and lower substrate water potentials were found in mycorrhizal substrates. Mycorrhiza neither affected leaf area nor root weight or length. Consistently with higher substrate drying rates, AMF restored the plant hydraulic status, and increased plant transpiration when soil moisture declined. The water potential at the root surface and the resistance to water flow in the rhizosphere were restored in mycorrhizal pots although the bulk substrate dried more. Finally, substrates colonized by AMF can be more desiccated before substrate water flux quantitatively limits transpiration. This is most pronounced under high transpiration demands and complies with a difference of over 1,000 hPa in substrate water potential.
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.
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.
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.
Within-field variability of plant and soil parameters
NASA Technical Reports Server (NTRS)
Ulaby, F. T. (Principal Investigator); Brisco, B.; Dobson, C.
1981-01-01
The variability of ground truth data collected for vegetation experiments was investigated. Two fields of wheat and one field of corn were sampled on two different dates. The variability of crop and soil parameters within a field, between two fields of the same type, and within a field over time were compared statistically. The number of samples from each test site required in order to be able to determine with confidence the mean and standard deviations for a given variable was determined. Eight samples were found to be adequate for plant height determinations, while twenty samples were required for plant moisture and soil moisture characterization. Eighteen samples were necessary for detecting within field variability over time and for between field variability for the same crop. The necessary sample sites vary according to the physiological growth stage of the crop and recent weather events that affect the moisture and/or height characteristics of the field in question.
NASA Astrophysics Data System (ADS)
Qian, F.; Lee, D. B.; Bodek, S.; Roberts, S.; Topping, T. T.; Robele, Y.; Koditschek, D. E.; Jerolmack, D. J.
2017-12-01
Understanding the parameters that control the spatial variation in aeolian soil erodibility is crucial to the development of sediment transport models. Currently, in-situ measurements of erodibility are time consuming and lack robustness. In an attempt to remedy this issue, we perform field and laboratory tests to determine the suitability of a novel mechanical shear strength method to assess soil erodibility. These tests can be performed quickly ( 1 minute) by a semi-autonomous robot using its direct-drive leg, while environmental controls such as soil moisture and grain size are simultaneously characterized. The robot was deployed at White Sands National Monument to delineate and understand erodibility gradients at two different scales: (1) from dry dune crest to moist interdune (distance 10s m), where we determined that shear strength increases by a factor of three with increasing soil moisture; and (2) from barren barchan dunes to vegetated and crusted parabolics downwind (distance 5 km), where we found that shear strength was enhanced by a factor of two relative to loose sand. Interestingly, shear strength varied little from carbonate-crusted dune surfaces to bio-crust covered interdunes in the downwind parabolic region, indicating that varied surface crusts contribute similarly to erosion resistance. To isolate the control of soil moisture on erodibility, we performed laboratory experiments in a sandbox. These results verify that the observed increase in soil erodibility from barchan crest to interdune at White Sands is dominated by soil moisture, and the variation in parabolic dune and barchan interdune areas results from a combination of soil moisture, bio-activity, and crust development. This study highlights that spatial variation of soil erodibility in arid environments is large enough to significantly affect sediment transport, and that probing soil erodibility with a robot has the potential to improve our understanding of this multifaceted problem.
NASA Astrophysics Data System (ADS)
Gupta, M.; Bolten, J. D.; Lakshmi, V.
2016-12-01
Water scarcity is one of the main factors limiting agricultural development. Numerical models integrated with remote sensing datasets are increasingly being used operationally as inputs for crop water balance models and agricultural forecasting due to increasing availability of high temporal and spatial resolution datasets. However, the model accuracy in simulating soil water content is affected by the accuracy of the soil hydraulic parameters used in the model, which are used in the governing equations. However, soil databases are known to have a high uncertainty across scales. Also, for agricultural sites, the in-situ measurements of soil moisture are currently limited to discrete measurements at specific locations, and such point-based measurements do not represent the spatial distribution at a larger scale accurately, as soil moisture is highly variable both spatially and temporally. The present study utilizes effective soil hydraulic parameters obtained using a 1-km downscaled microwave remote sensing soil moisture product based on the NASA Advanced Microwave Scanning Radiometer (AMSR-E) using the genetic algorithm inverse method within the Catchment Land Surface Model (CLSM). Secondly, to provide realistic irrigation estimates for agricultural sites, an irrigation scheme within the land surface model is triggered when the root-zone soil moisture deficit reaches the threshold, 50% with respect to the maximum available water capacity obtained from the effective soil hydraulic parameters. An additional important criterion utilized is the estimation of crop water consumption based on dynamic root growth and uptake in root zone layer. Model performance is evaluated using MODIS land surface temperature (LST) product. The soil moisture estimates for the root zone are also validated with the in situ field data, for three sites (2- irrigated and 1- rainfed) located at the University of Nebraska Agricultural Research and Development Center near Mead, NE and monitored by three AmeriFlux installations (Verma et al., 2005).
NASA Astrophysics Data System (ADS)
Usowicz, J. B.; Marczewski, W.; Usowicz, B.; Lukowski, M. I.; Lipiec, J.; Slominski, J.
2012-04-01
Soil moisture, together with soil and vegetation characteristics, plays an important role in exchange of water and energy between the land surface and the atmospheric boundary layer. Accurate knowledge of current and future spatial and temporal variation in soil moisture is not well known, nor easy to measure or predict. Knowledge of soil moisture in surface and root zone soil moisture is critical for achieving sustainable land and water management. The importance of SM is so high that this ECV is recommended by GCOS (Global Climate Observing System) to any attempts of evaluating of effects the climate change, and therefore it is one of the goals for observing the Earth by the ESA SMOS Mission (Soil Moisture and Ocean Salinity), globally. SMOS provides its observations by means of the interferometric radiometry method (1.4 GHz) from the orbit. In parallel, ten ground based stations are kept by IA PAN, in area of the Eastern Wall in Poland, in order to validate SMOS data and for other ground based agrophysical purposes. Soil moisture measurements obtained from ground and satellite measurements from SMOS were compared using Bland-Altman method of agreement, concordance correlation coefficient (CCC) and total deviation index (TDI). Observed similar changes in soil moisture, but the values obtained from satellite measurements were lower. Minor differences between the compared data are at higher moisture contents of soil and they grow with decreasing soil moisture. Soil moisture trends are maintained in the individual stations. Such distributions of soil moisture were mainly related to soil type. * The work was financially supported in part by the ESA Programme for European Cooperating States (PECS), No.98084 "SWEX-R, Soil Water and Energy Exchange/Research", AO3275.
NASA Astrophysics Data System (ADS)
Gusman, M.; Nazki, A.; Putra, R. R.
2018-04-01
One of the parameters in slope stability analysis is the shear strength of the soil. Changes in soil shear strength characteristics lead to a decrease in safety factors on the slopes. This study aims to see the effect of increased moisture content on soil mechanical parameters. The case study study was conducted on the slopes of Sitinjau Lauik Kota Padang. The research method was done by laboratory analysis and simple liniear regression analysis and multiple. Based on the test soil results show that the increase in soil water content causes a decrease in cohesion values and internal shear angle. The relationship of moisture content to cohesion is described in equation Y = 55.713-0,6X with R2 = 0.842. While the relationship of water content to shear angle in soil is described in the equation Y = 38.878-0.258X with R2 = 0.915. From several simulations of soil water level improvement, calculation of safety factor (SF) of slope. The calculation results show that the increase of groundwater content is very significant affect the safety factor (SF) slope. SF slope values are in safe condition when moisture content is 50% and when it reaches maximum water content 73.74% slope safety factor value potentially for landslide.
A multiyear study of soil moisture patterns across agricultural and forested landscapes
NASA Astrophysics Data System (ADS)
Georgakakos, C. B.; Hofmeister, K.; O'Connor, C.; Buchanan, B.; Walter, T.
2017-12-01
This work compares varying spatial and temporal soil moisture patterns in wet and dry years between forested and agricultural landscapes. This data set spans 6 years (2012-2017) of snow-free soil moisture measurements across multiple watersheds and land covers in New York State's Finger Lakes region. Due to the relatively long sampling period, we have captured fluctuations in soil moisture dynamics across wetter, dryer, and average precipitation years. We can therefore analyze response of land cover types to precipitation under varying climatic and hydrologic conditions. Across the study period, mean soil moisture in forest soils was significantly drier than in agricultural soils, and exhibited a smaller range of moisture conditions. In the drought year of 2016, soil moisture at all sites was significantly drier compared to the other years. When comparing the effects of land cover and year on soil moisture, we found that land cover had a more significant influence. Understanding the difference in landscape soil moisture dynamics between forested and agricultural land will help predict watershed responses to changing precipitation patterns in the future.
USDA-ARS?s Scientific Manuscript database
NASA Soil Moisture Active Passive (SMAP) satellite mission was launched on January 31, 2015 to provide global mapping of high-resolution soil moisture and freeze thaw state every 2-3 days using an L-band (active) radar and an L-band (passive) radiometer. The radiometer-only soil moisture product (L2...
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.
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.
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...
NASA Astrophysics Data System (ADS)
Boisserie, M.; Cocke, S.; O'Brien, J. J.
2009-12-01
Although the amount of water contained in the soil seems insignificant when compared to the total amount of water on a global-scale, soil moisture is widely recognized as a crucial variable for climate studies. It plays a key role in regulating the interaction between the atmosphere and the land-surface by controlling the repartition between the surface latent and sensible heat fluxes. In addition, the persistence of soil moisture anomalies provides one of the most important components of memory for the climate system. Several studies have shown that, during the boreal summer in mid-latitudes, the soil moisture role in controlling the continental precipitation variability may be more important than that of the sea surface temperature (Koster et al. 2000, Hong and Kalnay 2000, Koster et al. 2000, Kumar and Hoerling 1995, Trenberth et al. 1998, Shukla 1998). Although all of the above studies have demonstrated the strong sensitivity of seasonal forecasts to the soil moisture initial conditions, they relied on extreme or idealized soil moisture levels. The question of whether realistic soil moisture initial conditions lead to improved seasonal predictions has not been adequately addressed. Progress in addressing this question has been hampered by the lack of long-term reliable observation-based global soil moisture data sets. Since precipitation strongly affects the soil moisture characteristics at the surface and in depth, an alternative to this issue is to assimilate precipitation. Because precipitation is a diagnostic variable, most of the current reanalyses do not directly assimilate it into their models (M. Bosilovitch, 2008). In this study, an effective technique that directly assimilates the precipitation is used. We examine two experiments. In the first experiment, the model is initialized by directly assimilating a global, 3-hourly, 1.0° precipitation dataset, provided by Sheffield et al. (2006), in a continuous assimilation period of a couple of months. For this, we use a technique named the Precipitation Assimilation Reanalysis (PAR) described in Nunes and Cocke (2004). This technique consists of modifying the vertical profile of humidity as a function of the observed and predicted model rain rates. In the second experiment, the model is initialized without precipitation assimilation. For each experiment, ten sets of seasonal forecasts of the coupled land-atmosphere Florida State University/Center for Ocean and Atmosphere Predictions Studies (FSU/COAPS) model were generated, starting from the boreal summer of each year between 1986 and 1995. For each forecast, ten ensembles are produced by starting the forecast from the 1st and the 15th of each month from April to August. The results of these experiments show, first, that the PAR technique greatly improves the temporal and spatial variability of out model soil moisture estimate. Second, using these realistic soil moisture initial conditions, we found a significant increase in the air temperature seasonal forecasting skills. However, not significant increase has been found in the precipitation seasonal forecasting skills. The results of this study are involved in the GLACE-2 international multi-model experiment.
NASA Astrophysics Data System (ADS)
Saidaliyeva, Zarina; Davenport, Ian; Nobakht, Mohamad; White, Kevin; Shahgedanova, Maria
2017-04-01
Kazakhstan is a major producer of grain. Large scale grain production dominates in the north, making Kazakhstan one of the largest exporters of grain in the world. Agricultural production accounts for 9% of the national GDP, providing 25% of national employment. The south relies on grain production from household farms for subsistence, and has low resilience, so is vulnerable to reductions in output. Yields in the south depend on snowmelt and glacier runoff. The major limit to production is water supply, which is affected by glacier retreat and frequent droughts. Climate change is likely to impact all climate drivers negatively, leading to a decrease in crop yield, which will impact Kazakhstan and countries dependent on importing its produce. This work makes initial steps in modelling the impact of climate change on crop yield, by identifying the links between snowfall, soil moisture and agricultural productivity. Several remotely-sensed data sources are being used. The availability of snowmelt water over the period 2010-2014 is estimated by extracting the annual maximum snow water equivalent (SWE) from the Globsnow dataset, which assimilates satellite microwave observations with field observations to produce a spatial map. Soil moisture over the period 2010-2016 is provided by the ESA Soil Moisture and Ocean Salinity (SMOS) mission. Vegetation density is approximated by the Normalised Difference Vegetation Index (NDVI) produced from NASA's MODIS instruments. Statistical information on crop yields is provided by the Ministry of National Economy of the Republic of Kazakhstan Committee on Statistics. Demonstrating the link between snowmelt yield and agricultural productivity depends on showing the impact of snow mass during winter on remotely-sensed soil moisture, the link between soil moisture and vegetation density, and finally the link between vegetation density and crop yield. Soil moisture maps were extracted from SMOS observations, and resampled onto a 40km x 40km grid, and analysed to produce monthly averages. The monthly maximum snow water equivalent estimates for March were resampled onto the same grid, to approximate the total snow contributing to snowmelt. The MODIS MOD13A2 1km 16-day NDVI product was resampled onto the same 40km grid, and aggregated into 32-day averages. Annual crop yield is available in terms of kg of yield per hectare for each region in Kazakhstan between 2004 and 2015. To show the connection between the snowmelt and soil moisture, the cells within the snow and soil moisture grids were compared to calculate correlation. Data were aggregated per region. Regions in northern Kazakhstan showed the strongest correlations, because more of the soil water supply is derived from snowmelt than rain, and the southern regions showed poor correlation because of the greater influence of rainfall and irrigation. Correlations between soil moisture and vegetation density, and crop yield are ongoing, and results will be presented. It is envisaged that this research will assist the Kazakh farming community, providing real-time soil moisture data from SMOS.
SMAP Radiometer Captures Views of Global Soil Moisture
2015-05-06
These maps of global soil moisture were created using data from the radiometer instrument on NASA Soil Moisture Active Passive SMAP observatory. Evident are regions of increased soil moisture and flooding during April, 2015.
NASA Astrophysics Data System (ADS)
Cumming, William Frank Preston
Fine scale studies are rarely performed to address landscape level responses to microclimatic variability. Is it the timing, distribution, and magnitude of soil temperature and moisture that affects what species emerge each season and, in turn, their resilience to fluctuations in microclimate. For this dissertation research, I evaluated the response of vegetation change to microclimatic variability within two communities over a three year period (2009-2012) utilizing 25 meter transects at two locations along the Front Range of Colorado near Boulder, CO and Golden, CO respectively. To assess microclimatic variability, spatial and temporal autocorrelation analyses were performed with soil temperature and moisture. Species cover was assessed along several line transects and correlated with microclimatic variability. Spatial and temporal autocorrelograms are useful tools in identifying the degree of dependency of soil temperature and moisture on the distance and time between pairs of measurements. With this analysis I found that a meter spatial resolution and two-hour measurements are sufficient to capture the fine scale variability in soil properties throughout the year. By comparing this to in situ measurements of soil properties and species percent cover I found that there are several plant functional types and/or species origin in particular that are more sensitive to variations in temperature and moisture than others. When all seasons, locations, correlations, and regional climate are looked at, it is the month of March that stands out in terms of significance. Additionally, of all of the vegetation types represented at these two sites C4, C3, native, non-native, and forb species seem to be the most sensitive to fluctuations in soil temperature, moisture, and regional climate in the spring season. The steady decline in percent species cover the study period and subsequent decrease in percent species cover and size at both locations may indicate that certain are unable to respond to continually higher temperatures and lower moisture availability that is inevitable with future climatic variability.
Value of Available Global Soil Moisture Products for Agricultural Monitoring
NASA Astrophysics Data System (ADS)
Mladenova, Iliana; Bolten, John; Crow, Wade; de Jeu, Richard
2016-04-01
The first operationally derived and publicly distributed global soil moil moisture product was initiated with the launch of the Advanced Scanning Microwave Mission on the NASA's Earth Observing System Aqua satellite (AMSR-E). AMSR-E failed in late 2011, but its legacy is continued by AMSR2, launched in 2012 on the JAXA Global Change Observation Mission-Water (GCOM-W) mission. AMSR is a multi-frequency dual-polarization instrument, where the lowest two frequencies (C- and X-band) were used for soil moisture retrieval. Theoretical research and small-/field-scale airborne campaigns, however, have demonstrated that soil moisture would be best monitored using L-band-based observations. This consequently led to the development and launch of the first L-band-based mission-the ESA's Soil Moisture Ocean Salinity (SMOS) mission (2009). In early 2015 NASA launched the second L-band-based mission, the Soil Moisture Active Passive (SMAP). These satellite-based soil moisture products have been demonstrated to be invaluable sources of information for mapping water stress areas, crop monitoring and yield forecasting. Thus, a number of agricultural agencies routinely utilize and rely on global soil moisture products for improving their decision making activities, determining global crop production and crop prices, identifying food restricted areas, etc. The basic premise of applying soil moisture observations for vegetation monitoring is that the change in soil moisture conditions will precede the change in vegetation status, suggesting that soil moisture can be used as an early indicator of expected crop condition change. Here this relationship was evaluated across multiple microwave frequencies by examining the lag rank cross-correlation coefficient between the soil moisture observations and the Normalized Difference Vegetation Index (NDVI). A main goal of our analysis is to evaluate and inter-compare the value of the different soil moisture products derived using L-band (SMOS) versus C-/X-band (AMSR2) observations. The soil moisture products analyzed here were derived using the Land Parameter Retrieval Model.
NASA Technical Reports Server (NTRS)
Arya, L. M.; Phinney, D. E. (Principal Investigator)
1980-01-01
Soil moisture data acquired to support the development of algorithms for estimating surface soil moisture from remotely sensed backscattering of microwaves from ground surfaces are presented. Aspects of field uniformity and variability of gravimetric soil moisture measurements are discussed. Moisture distribution patterns are illustrated by frequency distributions and contour plots. Standard deviations and coefficients of variation relative to degree of wetness and agronomic features of the fields are examined. Influence of sampling depth on observed moisture content an variability are indicated. For the various sets of measurements, soil moisture values that appear as outliers are flagged. The distribution and legal descriptions of the test fields are included along with examinations of soil types, agronomic features, and sampling plan. Bulk density data for experimental fields are appended, should analyses involving volumetric moisture content be of interest to the users of data in this report.
NASA Technical Reports Server (NTRS)
Laymon, Charles A.; Crosson, William L.; Limaye, Ashutosh; Manu, Andrew; Archer, Frank
2005-01-01
We compare soil moisture retrieved with an inverse algorithm with observations of mean moisture in the 0-6 cm soil layer. A significant discrepancy is noted between the retrieved and observed moisture. Using emitting depth functions as weighting functions to convert the observed mean moisture to observed effective moisture removes nearly one-half of the discrepancy noted. This result has important implications in remote sensing validation studies.
NASA Astrophysics Data System (ADS)
Ju, Tingting; Li, Xiaolan; Zhang, Hongsheng; Cai, Xuhui; Song, Yu
2018-06-01
Using the observational data of dust concentrations and meteorological parameters from 2011 to 2015, the effects of soil moisture and air humidity on dust emission were studied at long (monthly) and short (several days or hours) time scales over the Horqin Sandy Land area, Inner Mongolia of China. The results show that the monthly mean dust concentrations and dust fluxes within the near-surface layer had no obvious relationship with the monthly mean soil moisture content but had a slightly negative correlation with monthly mean air relative humidity from 2011 to 2015. The daily mean soil moisture exhibited a significantly negative correlation with the daily mean dust concentrations and dust fluxes, as soil moisture changed obviously. However, such negative correlation between soil moisture and dust emission disappeared on dust blowing days. Additionally, the effect of soil moisture on an important parameter for dust emission, the threshold friction velocity (u∗t), was investigated during several saltation-bombardment and/or aggregation-disintegration dust emission (SADE) events. Under dry soil conditions, the values of u∗t were not influenced by soil moisture content; however, when the soil moisture content was high, the values of u∗t increased with increasing soil moisture content.
Relation Between the Rainfall and Soil Moisture During Different Phases of Indian Monsoon
NASA Astrophysics Data System (ADS)
Varikoden, Hamza; Revadekar, J. V.
2018-03-01
Soil moisture is a key parameter in the prediction of southwest monsoon rainfall, hydrological modelling, and many other environmental studies. The studies on relationship between the soil moisture and rainfall in the Indian subcontinent are very limited; hence, the present study focuses the association between rainfall and soil moisture during different monsoon seasons. The soil moisture data used for this study are the ESA (European Space Agency) merged product derived from four passive and two active microwave sensors spanning over the period 1979-2013. The rainfall data used are India Meteorological Department gridded daily data. Both of these data sets are having a spatial resolution of 0.25° latitude-longitude grid. The study revealed that the soil moisture is higher during the southwest monsoon period similar to rainfall and during the pre-monsoon period, the soil moisture is lower. The annual cycle of both the soil moisture and rainfall has the similitude of monomodal variation with a peak during the month of August. The interannual variability of soil moisture and rainfall shows that they are linearly related with each other, even though they are not matched exactly for individual years. The study of extremes also exhibits the surplus amount of soil moisture during wet monsoon years and also the regions of surplus soil moisture are well coherent with the areas of high rainfall.
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...
MISTRALE: Soil moisture mapping service based on a UAV-embedded GNSS-Reflectometry sensor
NASA Astrophysics Data System (ADS)
Van de Vyvere, Laura; Desenfans, Olivier
2016-04-01
Around 70 percent of worldwide freshwater is used by agriculture. To be able to feed an additional 2 billion people by 2030, water demand is expected to increase tremendously in the next decades. Farmers are challenged to produce "more crop per drop". In order to optimize water resource management, it is crucial to improve soil moisture situation awareness, which implies both a better temporal and spatial resolution. To this end, the objective of the MISTRALE project (Monitoring soIl moiSture and waTeR-flooded Areas for agricuLture and Environment) is to provide UAV-based soil moisture maps that could complement satellite-based and field measurements. In addition to helping farmers make more efficient decisions about where and when to irrigate, MISTRALE moisture maps are an invaluable tool for risk management and damage evaluation, as they provide highly relevant information for wetland and flood-prone area monitoring. In order to measure soil water content, a prototype of a new sensor, called GNSS-Reflectometry (GNSS-R), is being developed in MISTRALE. This approach consists in comparing the direct signal, i.e. the signal travelling directly from satellite to receiver (in this case, embedded in the UAV), with its ground-reflected equivalent. Since soil dielectric properties vary with moisture content, the reflected signal's peak power is affected by soil moisture, unlike the direct one. In order to mitigate the effect of soil surface roughness on measurements, both left-hand and right-hand circular polarization reflected signals have to be recorded and processed. When it comes to soil moisture, using GNSS signals instead of traditional visible/NIR imagery has many advantages: it is operational under cloud cover, during the night, and also under vegetation (bushes, grass, trees). In addition, compared to microwaves, GNSS signal (which lies in L-band, between 1.4 and 1.8 GHz) is less influenced by variation on thermal background. GNSS frequencies are then ideal candidates for soil moisture observation. In the context of the MISTRALE project, both GPS and GALILEO signals will be used. Thanks to a higher number of available satellites and to the GALILEO signals characteristics, the sensor's measurements accuracy will be improved. The GNSS-R sensor will be embedded on Boreal, a fixed-wing UAV weighing less than 20 kg and allowing about 5 kg payload. Boreal is able to fly continuously for 10 hours and has a range of 1000 km. Due to the low elevation (100-150m) of UAV flights, high spatial resolution can be achieved. Test flights have already been performed in Pech Rouge and Camargue areas, France. During these campaigns, soil moisture maps were computed using GNSS-R data. These were successfully correlated with in-situ measurements, considered as ground truth, demonstrating the feasibility of the MISTRALE concept. The MISTRALE project is co-funded by GSA (European GNSS Agency) under H2020 program framework for research and innovation.
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.
Methods of measuring soil moisture in the field
Johnson, A.I.
1962-01-01
For centuries, the amount of moisture in the soil has been of interest in agriculture. The subject of soil moisture is also of great importance to the hydrologist, forester, and soils engineer. Much equipment and many methods have been developed to measure soil moisture under field conditions. This report discusses and evaluates the various methods for measurement of soil moisture and describes the equipment needed for each method. The advantages and disadvantages of each method are discussed and an extensive list of references is provided for those desiring to study the subject in more detail. The gravimetric method is concluded to be the most satisfactory method for most problems requiring onetime moisture-content data. The radioactive method is normally best for obtaining repeated measurements of soil moisture in place. It is concluded that all methods have some limitations and that the ideal method for measurement of soil moisture under field conditions has yet to be perfected.
NASA Astrophysics Data System (ADS)
Wu, Mousong; Sholze, Marko
2017-04-01
We investigated the importance of soil moisture data on assimilation of a terrestrial biosphere model (BETHY) for a long time period from 2010 to 2015. Totally, 101 parameters related to carbon turnover, soil respiration, as well as soil texture were selected for optimization within a carbon cycle data assimilation system (CCDAS). Soil moisture data from Soil Moisture and Ocean Salinity (SMOS) product was derived for 10 sites representing different plant function types (PFTs) as well as different climate zones. Uncertainty of SMOS soil moisture data was also estimated using triple collocation analysis (TCA) method by comparing with ASCAT dataset and BETHY forward simulation results. Assimilation of soil moisture to the system improved soil moisture as well as net primary productivity(NPP) and net ecosystem productivity (NEP) when compared with soil moisture derived from in-situ measurements and fluxnet datasets. Parameter uncertainties were largely reduced relatively to prior values. Using SMOS soil moisture data for assimilation of a terrestrial biosphere model proved to be an efficient approach in reducing uncertainty in ecosystem fluxes simulation. It could be further used in regional an global assimilation work to constrain carbon dioxide concentration simulation by combining with other sources of measurements.
Soil Moisture under Different Vegetation cover in response to Precipitation
NASA Astrophysics Data System (ADS)
Liang, Z.; Zhang, J.; Guo, B.; Ma, J.; Wu, Y.
2016-12-01
The response study of soil moisture to different precipitation and landcover is significant in the field of Hydropedology. The influence of precipitation to soil moisture is obvious in addition to individual stable aquifer. With data of Hillsborough County, Florida, USA, the alluvial wetland forest and ungrazed Bahia grass that under wet and dry periods were chosen as the research objects, respectively. HYDRUS-3D numerical simulation method was used to simulate soil moisture dynamics in the root zone (10-50 cm) of those vegetation. The soil moisture response to precipitation was analyzed. The results showed that the simulation results of alluvial wetland forest by HYDRUS-3D were better than that of the Bahia grass, and for the same vegetation, the simulation results of soil moisture under dry period were better. Precipitation was more in June, 2003, the soil moisture change of alluvial wetland forest in 10-30 cm soil layer and Bahia grass in 10 cm soil layer were consistent with the precipitation change conspicuously. The alluvial wetland forest soil moisture declined faster than Bahia grass under dry period, which demonstrated that Bahia grass had strong ability to hold water. Key words: alluvial wetland forest; Bahia grass; soil moisture; HYDRUS-3D; precipitation
USDA-ARS?s Scientific Manuscript database
This paper evaluates the retrieval of soil moisture in the top 5-cm layer at 3-km spatial resolution using L-band dual-copolarized Soil Moisture Active Passive (SMAP) synthetic aperture radar (SAR) data that mapped the globe every three days from mid-April to early July, 2015. Surface soil moisture ...
NASA Astrophysics Data System (ADS)
Dick, Jonathan; Tetzlaff, Doerthe; Bradford, John; Soulsby, Chris
2018-04-01
As the relationship between vegetation and soil moisture is complex and reciprocal, there is a need to understand how spatial patterns in soil moisture influence the distribution of vegetation, and how the structure of vegetation canopies and root networks regulates the partitioning of precipitation. Spatial patterns of soil moisture are often difficult to visualise as usually, soil moisture is measured at point scales, and often difficult to extrapolate. Here, we address the difficulties in collecting large amounts of spatial soil moisture data through a study combining plot- and transect-scale electrical resistivity tomography (ERT) surveys to estimate soil moisture in a 3.2 km2 upland catchment in the Scottish Highlands. The aim was to assess the spatio-temporal variability in soil moisture under Scots pine forest (Pinus sylvestris) and heather moorland shrubs (Calluna vulgaris); the two dominant vegetation types in the Scottish Highlands. The study focussed on one year of fortnightly ERT surveys. The surveyed resistivity data was inverted and Archie's law was used to calculate volumetric soil moisture by estimating parameters and comparing against field measured data. Results showed that spatial soil moisture patterns were more heterogeneous in the forest site, as were patterns of wetting and drying, which can be linked to vegetation distribution and canopy structure. The heather site showed a less heterogeneous response to wetting and drying, reflecting the more uniform vegetation cover of the shrubs. Comparing soil moisture temporal variability during growing and non-growing seasons revealed further contrasts: under the heather there was little change in soil moisture during the growing season. Greatest changes in the forest were in areas where the trees were concentrated reflecting water uptake and canopy partitioning. Such differences have implications for climate and land use changes; increased forest cover can lead to greater spatial variability, greater growing season temporal variability, and reduced levels of soil moisture, whilst projected decreasing summer precipitation may alter the feedbacks between soil moisture and vegetation water use and increase growing season soil moisture deficits.
Drive by Soil Moisture Measurement: A Citizen Science Project
NASA Astrophysics Data System (ADS)
Senanayake, I. P.; Willgoose, G. R.; Yeo, I. Y.; Hancock, G. R.
2017-12-01
Two of the common attributes of soil moisture are that at any given time it varies quite markedly from point to point, and that there is a significant deterministic pattern that underlies this spatial variation and which is typically 50% of the spatial variability. The spatial variation makes it difficult to determine the time varying catchment average soil moisture using field measurements because any individual measurement is unlikely to be equal to the average for the catchment. The traditional solution to this is to make many measurements (e.g. with soil moisture probes) spread over the catchment, which is very costly and manpower intensive, particularly if we need a time series of soil moisture variation across a catchment. An alternative approach, explored in this poster is to use the deterministic spatial pattern of soil moisture to calibrate one site (e.g. a permanent soil moisture probe at a weather station) to the spatial pattern of soil moisture over the study area. The challenge is then to determine the spatial pattern of soil moisture. This poster will present results from a proof of concept project, where data was collected by a number of undergraduate engineering students, to estimate the spatial pattern. The approach was to drive along a series of roads in a catchment and collect soil moisture measurements at the roadside using field portable soil moisture probes. This drive was repeated a number of times over the semester, and the time variation and spatial persistence of the soil moisture pattern were examined. Provided that the students could return to exactly the same location on each collection day there was a strong persistent pattern in the soil moisture, even while the average soil moisture varied temporally as a result of preceding rainfall. The poster will present results and analysis of the student data, and compare these results with several field sites where we have spatially distributed permanently installed soil moisture probes. The poster will also outline an experimental design, based on our experience, that will underpin a proposed citizen science project involving community environment and farming groups, and high school students.
Fest, Benedikt; Wardlaw, Tim; Livesley, Stephen J; Duff, Thomas J; Arndt, Stefan K
2015-11-01
Disturbance associated with severe wildfires (WF) and WF simulating harvest operations can potentially alter soil methane (CH4 ) oxidation in well-aerated forest soils due to the effect on soil properties linked to diffusivity, methanotrophic activity or changes in methanotrophic bacterial community structure. However, changes in soil CH4 flux related to such disturbances are still rarely studied even though WF frequency is predicted to increase as a consequence of global climate change. We measured in-situ soil-atmosphere CH4 exchange along a wet sclerophyll eucalypt forest regeneration chronosequence in Tasmania, Australia, where the time since the last severe fire or harvesting disturbance ranged from 9 to >200 years. On all sampling occasions, mean CH4 uptake increased from most recently disturbed sites (9 year) to sites at stand 'maturity' (44 and 76 years). In stands >76 years since disturbance, we observed a decrease in soil CH4 uptake. A similar age dependency of potential CH4 oxidation for three soil layers (0.0-0.05, 0.05-0.10, 0.10-0.15 m) could be observed on incubated soils under controlled laboratory conditions. The differences in soil CH4 uptake between forest stands of different age were predominantly driven by differences in soil moisture status, which affected the diffusion of atmospheric CH4 into the soil. The observed soil moisture pattern was likely driven by changes in interception or evapotranspiration with forest age, which have been well described for similar eucalypt forest systems in south-eastern Australia. Our results imply that there is a large amount of variability in CH4 uptake at a landscape scale that can be attributed to stand age and soil moisture differences. An increase in severe WF frequency in response to climate change could potentially increase overall forest soil CH4 sinks. © 2015 John Wiley & Sons Ltd.
Ground-Water Levels and Soil Characteristics in a Forested Typic Glossaqualf
Peter L. Lorio
1977-01-01
The presence of impermeable layers can affect the development of a soil and its water regime. In a forested Typic Glossaqualf in southwest Louisiana, moisture, density, and piezometer measurements revealed an impermeable layer of soil between about 1.8 and 2.8 m below the surface. A high proportion of very fine sand and development of platy structure appeared related...
Inter-Comparison of SMAP, SMOS and GCOM-W Soil Moisture Products
NASA Astrophysics Data System (ADS)
Bindlish, R.; Jackson, T. J.; Chan, S.; Burgin, M. S.; Colliander, A.; Cosh, M. H.
2016-12-01
The Soil Moisture Active Passive (SMAP) mission was launched on Jan 31, 2015. The goal of the SMAP mission is to produce soil moisture with accuracy better than 0.04 m3/m3 with a revisit frequency of 2-3 days. The validated standard SMAP passive soil moisture product (L2SMP) with a spatial resolution of 36 km was released in May 2016. Soil moisture observations from in situ sensors are typically used to validate the satellite estimates. But, in situ observations provide ground truth for limited amount of landcover and climatic conditions. Although each mission will have its own issues, observations by other satellite instruments can be play a role in the calibration and validation of SMAP. SMAP, SMOS and GCOM-W missions share some commonnalities because they are currently providing operational brightness temperature and soil moisture products. SMAP and SMOS operate at L-band but GCOM-W uses X-band observations for soil moisture estimation. All these missions use different ancillary data sources, parameterization and algorithm to retrieve soil moisture. Therefore, it is important to validate and to compare the consistency of these products. Soil moisture products from the different missions will be compared with the in situ observations. SMAP soil moisture products will be inter-compared at global scales with SMOS and GCOM-W soil moisture products. The major contribution of satellite product inter-comparison is that it allows the assessment of the quality of the products over wider geographical and climate domains. Rigorous assessment will lead to a more reliable and accurate soil moisture product from all the missions.
Kivlin, Stephanie N; Hawkes, Christine V
2016-12-01
Tropical ecosystems remain poorly understood and this is particularly true for belowground soil fungi. Soil fungi may respond to plant identity when, for example, plants differentially allocate resources belowground. However, spatial and temporal heterogeneity in factors such as plant inputs, moisture, or nutrients can also affect fungal communities and obscure our ability to detect plant effects in single time point studies or within diverse forests. To address this, we sampled replicated monocultures of four tree species and secondary forest controls sampled in the drier and wetter seasons over 2 years. Fungal community composition was primarily related to vegetation type and spatial heterogeneity in the effects of vegetation type, with increasing divergence partly reflecting greater differences in soil pH and soil moisture. Across wetter versus drier dates, fungi were 7% less diverse, but up to four-fold more abundant. The combined effects of tree species and seasonality suggest that predicted losses of tropical tree diversity and intensification of drought have the potential to cascade belowground to affect both diversity and abundance of tropical soil fungi. © 2016 Society for Applied Microbiology and John Wiley & Sons Ltd.
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.
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.
Thomé, Antônio; Cecchin, Iziquiel; Reginatto, Cleomar; Colla, Luciane M; Reddy, Krishna R
2017-04-01
This study investigates the retention of biodiesel in residual clayey soil during biostimulation by nutrients (nitrogen, phosphorus, and potassium) under conditions of rainfall infiltration. Several column tests were conducted in a laboratory under different void ratios (1.14, 1.24, and 1.34), varying moisture contents (15, 25, and 35%), and in both the presence and absence of biostimulation. The volume of biodiesel (which was equivalent to the volume of voids in the soil) was placed atop the soil and allowed to percolate for a period of 15 days. The soil was subjected to different rainfall infiltration conditions (0.30 or 60 mm). The greatest reductions in residual contaminants occurred after 60 mm of rain simulation, at values of up to 74% less than in samples with the same conditions but no precipitation. However, the residual contamination decay rate was greater with 0-30 mm (0.29 g/mm) of precipitation than with 30-60 mm (0.075 g/mm). Statistical assessment revealed that increased moisture and the presence of nutrients were the factors with the most powerful effect on contaminant retention in the soil. The residual contaminant level was 21 g/kg at a moisture content of 15% and no precipitation, decreasing to 12 g/kg at 35% moisture and no precipitation. Accordingly, it is possible to conclude that biostimulation and rainfall infiltration conditions can decrease the retention of contaminants in soil and allow a greater leaching or spreading of the contamination. All of these phenomena are worthy of careful examination for the in situ bioremediation of organic contamination. • The higher moisture in the soil, due to a high initial moisture content and/or infiltration of rainfall, can reduce contaminant retention, • The use of biostimulation through the addition of nutrients to accelerate the biodegradation of toxic organic contaminants may induce inadvertent undesirable interactions between the soil and the contaminant. • When adopting biostimulation for bioremediation, the effects of rainfall should be addressed; ideally, it should be prevented from entering the affected site, in order to avoid increased contaminant leaching and potential spreading.
NASA Astrophysics Data System (ADS)
Demand, D.; Blume, T.; Weiler, M.
2017-12-01
Preferential flow in macropores significantly affects the distributions of water and solutes in soil and many studies showed its relevance worldwide. Although some models include this process as a second pore domain, little is known about the spatial patterns and temporal dynamics. For example, while flow in the matrix is usually modeled and parameterized based on soil texture, an influence of texture on non-capillary flow for a given land-use class is poorly understood. To investigate the temporal and spatial dynamics on preferential flow we used a four-year soil moisture dataset from the mesoscale Attert catchment (288 km²) in Luxembourg. This dataset contains time series from 126 soil profiles in different textures and two land-use classes (forest, grassland). The soil moisture probes were installed in 10, 30 and 50 cm depth and measured in a 5-minute temporal resolution. Events were defined by a soil moisture increase higher than the instrument noise after a precipitation sum of more than 1 mm. Precipitation was measured next to the profiles so that each location could be associated to its unique precipitation characteristics. For every event and profile the soil moisture reaction was classified in sequential (ordered by depth) and non-sequential response. A non-sequential soil moisture reaction was used as an indicator of preferential flow. For sequential flow, the velocity was determined by the first reaction between two vertically adjacent sensors. The sensor reaction and wetting front velocity was analyzed in the context of precipitation characteristics and initial soil water content. Grassland sites showed a lower proportion of non-sequential flow than forest sites. For forest, non-sequential response is dependent on texture, rainfall intensity and initial water content. This is less distinct for the grassland sites. Furthermore, sequential reactions show higher flow velocities at sites, which also have high percentage of non-sequential response. In contrast, grassland sites show a more homogenous wetting front independent of soil texture. Compared against common modelling approaches of soil water flow, measured velocities show clear evidence of preferential flow, especially for forest soils. The analysis also shows that vegetation can alter the soil properties above the textural properties alone.
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.
NASA Astrophysics Data System (ADS)
Martini, Edoardo; Wollschläger, Ute; Kögler, Simon; Behrens, Thorsten; Dietrich, Peter; Reinstorf, Frido; Schmidt, Karsten; Weiler, Markus; Werban, Ulrike; Zacharias, Steffen
2016-04-01
Characterizing the spatial patterns of soil moisture is critical for hydrological and meteorological models, as soil moisture is a key variable that controls matter and energy fluxes and soil-vegetation-atmosphere exchange processes. Deriving detailed process understanding at the hillslope scale is not trivial, because of the temporal variability of local soil moisture dynamics. Nevertheless, it remains a challenge to provide adequate information on the temporal variability of soil moisture and its controlling factors. Recent advances in wireless sensor technology allow monitoring of soil moisture dynamics with high temporal resolution at varying scales. In addition, mobile geophysical methods such as electromagnetic induction (EMI) have been widely used for mapping soil water content at the field scale with high spatial resolution, as being related to soil apparent electrical conductivity (ECa). The objective of this study was to characterize the spatial and temporal pattern of soil moisture at the hillslope scale and to infer the controlling hydrological processes, integrating well established and innovative sensing techniques, as well as new statistical methods. We combined soil hydrological and pedological expertise with geophysical measurements and methods from digital soil mapping for designing a wireless soil moisture monitoring network. For a hillslope site within the Schäfertal catchment (Central Germany), soil water dynamics were observed during 14 months, and soil ECa was mapped on seven occasions whithin this period of time using an EM38-DD device. Using the Spearman rank correlation coefficient, we described the temporal persistence of a dry and a wet characteristic state of soil moisture as well as the switching mechanisms, inferring the local properties that control the observed spatial patterns and the hydrological processes driving the transitions. Based on this, we evaluated the use of EMI for mapping the spatial pattern of soil moisture under different hydrologic conditions and the factors controlling the temporal variability of the ECa-soil moisture relationship. The approach provided valuable insight into the time-varying contribution of local and nonlocal factors to the characteristic spatial patterns of soil moisture and the transition mechanisms. The spatial organization of soil moisture was controlled by different processes in different soil horizons, and the topsoil's moisture did not mirror processes that take place within the soil profile. Results show that, for the Schäfertal hillslope site which is presumed to be representative for non-intensively managed soils with moderate clay content, local soil properties (e.g., soil texture and porosity) are the major control on the spatial pattern of ECa. In contrast, the ECa-soil moisture relationship is small and varies over time indicating that ECa is not a good proxy for soil moisture estimation at the investigated site.Occasionally observed stronger correlations between ECa and soil moisture may be explained by background dependencies of ECa to other state variables such as pore water electrical conductivity. The results will help to improve conceptual understanding for hydrological model studies at similar or smaller scales, and to transfer observation concepts and process understanding to larger or less instrumented sites, as well as to constrain the use of EMI-based ECa data for hydrological applications.
Spatial structure and scaling of macropores in hydrological process at small catchment scale
NASA Astrophysics Data System (ADS)
Silasari, Rasmiaditya; Broer, Martine; Blöschl, Günter
2013-04-01
During rainfall events, the formation of overland flow can occur under the circumstances of saturation excess and/or infiltration excess. These conditions are affected by the soil moisture state which represents the soil water content in micropores and macropores. Macropores act as pathway for the preferential flows and have been widely studied locally. However, very little is known about their spatial structure and conductivity of macropores and other flow characteristic at the catchment scale. This study will analyze these characteristics to better understand its importance in hydrological processes. The research will be conducted in Petzenkirchen Hydrological Open Air Laboratory (HOAL), a 64 ha catchment located 100 km west of Vienna. The land use is divided between arable land (87%), pasture (5%), forest (6%) and paved surfaces (2%). Video cameras will be installed on an agricultural field to monitor the overland flow pattern during rainfall events. A wireless soil moisture network is also installed within the monitored area. These field data will be combined to analyze the soil moisture state and the responding surface runoff occurrence. The variability of the macropores spatial structure of the observed area (field scale) then will be assessed based on the topography and soil data. Soil characteristics will be supported with laboratory experiments on soil matrix flow to obtain proper definitions of the spatial structure of macropores and its variability. A coupled physically based distributed model of surface and subsurface flow will be used to simulate the variability of macropores spatial structure and its effect on the flow behaviour. This model will be validated by simulating the observed rainfall events. Upscaling from field scale to catchment scale will be done to understand the effect of macropores variability on larger scales by applying spatial stochastic methods. The first phase in this study is the installation and monitoring configuration of video cameras and soil moisture monitoring equipment to obtain the initial data of overland flow occurrence and soil moisture state relationships.
The effects of salinity in the soil water balance: A Budyko's approach
NASA Astrophysics Data System (ADS)
Perri, S.; Viola, F.; Molini, A.
2017-12-01
Soil degradation and water scarcity pose important constraints on productivity and development of arid and semi-arid countries. Among the main causes of loss of soil fertility, aridification and soil salinization are deeply connected threats enhanced by climate change. Assessing water availability is fundamental for a large number of applications especially in arid regions. An approach often adopted to estimate the long-term rainfall partitioning into evapotranspiration and runoff is the Budyko's curve. However, the classical Budyko framework might not be able to properly reproduce the water balance in salt affected basins, especially under elevated soil salinization conditions. Salinity is a limiting factor for plant transpiration (as well as growth) affecting both short and long term soil moisture dynamics and ultimately the hydrologic balance. Soluble salts cause a reduction of soil water potential similar to the one arising from droughts, although plant adaptations to soil salinity show extremely different traits and can vary from species to species. In a similar context, the salt-tolerance plants are expected to control the amount of soil moisture lost to transpiration in saline soils, also because salinity reduces evaporation. We propose a simple framework to include the effects of salinization on the surface energy and water balance within a simple Budyko approach. By introducing the effects of salinity in the stochastic water balance we are able to include the influence of vegetation type (i.e. in terms of salt-tolerance) on evapotranspiration-runoff partitioning under different climatic conditions. The water balance components are thus compared to data obtained from arid salt-affected regions.
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.
NASA Astrophysics Data System (ADS)
Mettrop, I.; Cammeraat, L. H.; Verbeeten, E.
2009-04-01
Termites are important ecosystem-engineers in subtropical and tropical regions. The effect of termite activity affecting soil infiltration is well documented in the Sahelian region. Most studies find increased infiltration rates on surfaces that are affected by termite activity in comparison to crusted areas showing non-termite presence. Crusted agricultural fields in the Sanmatenga region in Burkina Faso with clear termite activity were compared to control fields without visual ground dwelling termite activity. Fine scale rainfall simulations were carried out on crusted termite affected and control sites. Furthermore soil moisture change, bulk density, soil organic matter as well as general soil characteristics were studied. The top soils in the study area were strongly crusted (structural crust) after the summer rainfall and harvest of millet. They have a loamy sand texture underlain by a shallow sandy loam Bt horizon. The initial soil moisture conditions were significantly higher on the termite plots when compared to control sites. It was found that the amount of runoff produced on the termite plots was significantly higher, and also the volumetric soil moisture content after the experiments was significantly lower if compared to the control plots. Bulk density showed no difference whereas soil organic matter was significantly higher under termite affected areas, in comparison to the control plots. Lab tests showed no significant difference in hydrophobic behavior of the topsoil and crust material. Micro and macro-structural properties of the topsoil did not differ significantly between the termite sites and the control sites. The texture of the top 5 cm of the soil was also found to be not significantly different. The infiltration results are contradictory to the general literature, which reports increased infiltration rates after prolonged termite activity although mostly under different initial conditions. The number of nest entrances was clearly higher in the termite areas, but apparently did not significantly affect infiltration. The increased soil organic matter contents in the termite affected areas however, are as expected from literature, but did not improve soil aggregation which would be expected given the importance of organic matter in soil aggregation in this type of soils. One of the explanations for the reduced infiltration rates might be that termites bring clay from the finer textured subsoil to the surface to build casts over the organic material on the surface (mainly millet stems). It is speculated that the excavated clay material could be involved in crust formation, only present is in the upper 0.5 cm of the soil crust, which is enough to block pores in the crust surface, hampering infiltration. The topsoil aggregates are slaking under the summer rainfall and the increase in fine textured material, excavated by the termites, could be incorporated into the crust and reduce infiltration. Furthermore this specific effect might also be related to the type of termite involved, as impacts from ecosystem engineers on their environment is highly dependent on the specific species involved.
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.
Method for evaluating moisture tensions of soils using spectral data
NASA Technical Reports Server (NTRS)
Peterson, John B. (Inventor)
1982-01-01
A method is disclosed which permits evaluation of soil moisture utilizing remote sensing. Spectral measurements at a plurality of different wavelengths are taken with respect to sample soils and the bidirectional reflectance factor (BRF) measurements produced are submitted to regression analysis for development therefrom of predictable equations calculated for orderly relationships. Soil of unknown reflective and unknown soil moisture tension is thereafter analyzed for bidirectional reflectance and the resulting data utilized to determine the soil moisture tension of the soil as well as providing a prediction as to the bidirectional reflectance of the soil at other moisture tensions.
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.
NASA Astrophysics Data System (ADS)
Giraldo, Mario A.; Bosch, David; Madden, Marguerite; Usery, Lynn; Kvien, Craig
2008-08-01
SummaryThis research addressed the temporal and spatial variation of soil moisture (SM) in a heterogeneous landscape. The research objective was to investigate soil moisture variation in eight homogeneous 30 by 30 m plots, similar to the pixel size of a Landsat Thematic Mapper (TM) or Enhanced Thematic Mapper plus (ETM+) image. The plots were adjacent to eight stations of an in situ soil moisture network operated by the United States Department of Agriculture-Agriculture Research Service USDA-ARS in Tifton, GA. We also studied five adjacent agricultural fields to examine the effect of different landuses/land covers (LULC) (grass, orchard, peanuts, cotton and bare soil) on the temporal and spatial variation of soil moisture. Soil moisture field data were collected on eight occasions throughout 2005 and January 2006 to establish comparisons within and among eight homogeneous plots. Consistently throughout time, analysis of variance (ANOVA) showed high variation in the soil moisture behavior among the plots and high homogeneity in the soil moisture behavior within them. A precipitation analysis for the eight sampling dates throughout the year 2005 showed similar rainfall conditions for the eight study plots. Therefore, soil moisture variation among locations was explained by in situ local conditions. Temporal stability geostatistical analysis showed that soil moisture has high temporal stability within the small plots and that a single point reading can be used to monitor soil moisture status for the plot within a maximum 3% volume/volume (v/v) soil moisture variation. Similarly, t-statistic analysis showed that soil moisture status in the upper soil layer changes within 24 h. We found statistical differences in the soil moisture between the different LULC in the agricultural fields as well as statistical differences between these fields and the adjacent 30 by 30 m plots. From this analysis, it was demonstrated that spatial proximity is not enough to produce similar soil moisture, since t-test's among adjacent plots with different LULCs showed significant differences. These results confirm that a remote sensing approach that considers homogeneous LULC landscape fragments can be used to identify landscape units of similar soil moisture behavior under heterogeneous landscapes. In addition, the in situ USDA-ARS network will serve better in remote sensing studies in which sensors with fine spatial resolution are evaluated. This study is a first step towards identifying landscape units that can be monitored using the single point reading of the USDA-ARS stations network.
Giraldo, M.A.; Bosch, D.; Madden, M.; Usery, L.; Kvien, Craig
2008-01-01
This research addressed the temporal and spatial variation of soil moisture (SM) in a heterogeneous landscape. The research objective was to investigate soil moisture variation in eight homogeneous 30 by 30 m plots, similar to the pixel size of a Landsat Thematic Mapper (TM) or Enhanced Thematic Mapper plus (ETM+) image. The plots were adjacent to eight stations of an in situ soil moisture network operated by the United States Department of Agriculture-Agriculture Research Service USDA-ARS in Tifton, GA. We also studied five adjacent agricultural fields to examine the effect of different landuses/land covers (LULC) (grass, orchard, peanuts, cotton and bare soil) on the temporal and spatial variation of soil moisture. Soil moisture field data were collected on eight occasions throughout 2005 and January 2006 to establish comparisons within and among eight homogeneous plots. Consistently throughout time, analysis of variance (ANOVA) showed high variation in the soil moisture behavior among the plots and high homogeneity in the soil moisture behavior within them. A precipitation analysis for the eight sampling dates throughout the year 2005 showed similar rainfall conditions for the eight study plots. Therefore, soil moisture variation among locations was explained by in situ local conditions. Temporal stability geostatistical analysis showed that soil moisture has high temporal stability within the small plots and that a single point reading can be used to monitor soil moisture status for the plot within a maximum 3% volume/volume (v/v) soil moisture variation. Similarly, t-statistic analysis showed that soil moisture status in the upper soil layer changes within 24 h. We found statistical differences in the soil moisture between the different LULC in the agricultural fields as well as statistical differences between these fields and the adjacent 30 by 30 m plots. From this analysis, it was demonstrated that spatial proximity is not enough to produce similar soil moisture, since t-test's among adjacent plots with different LULCs showed significant differences. These results confirm that a remote sensing approach that considers homogeneous LULC landscape fragments can be used to identify landscape units of similar soil moisture behavior under heterogeneous landscapes. In addition, the in situ USDA-ARS network will serve better in remote sensing studies in which sensors with fine spatial resolution are evaluated. This study is a first step towards identifying landscape units that can be monitored using the single point reading of the USDA-ARS stations network. ?? 2008 Elsevier B.V.
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.
Soil moisture and vegetation patterns in northern California forests
James R. Griffin
1967-01-01
Twenty-nine soil-vegetation plots were studied in a broad transect across the southern Cascade Range. Variations in soil moisture patterns during the growing season and in soil moisture tension values are discussed. Plot soil moisture values for 40- and 80-cm. depths in August and September are integrated into a soil drought index. Vegetation patterns are described in...
Human Effects and Soil Surface CO2 fluxes in Tropical Urban Green Areas, Singapore
NASA Astrophysics Data System (ADS)
Ng, Bernard; Gandois, Laure; Kai, Fuu Ming; Chua, Amy; Cobb, Alex; Harvey, Charles; Hutyra, Lucy
2013-04-01
Urban green spaces are appreciated for their amenity value, with increasing interest in the ecosystem services they could provide (e.g. climate amelioration and increasingly as possible sites for carbon sequestration). In Singapore, turfgrass occupies approximately 20% of the total land area and is readily found on both planned and residual spaces. This project aims at understanding carbon fluxes in tropical urban green areas, including controls of soil environmental factors and the effect of urban management techniques. Given the large pool of potentially labile carbon, management regimes are recognised to have an influence on soil environmental factors (temperature and moisture), this would affect soil respiration and feedbacks to the greenhouse effect. A modified closed dynamic chamber method was employed to measure total soil respiration fluxes. In addition to soil respiration rates, environmental factors such as soil moisture and temperature, and ambient air temperature were monitored for the site in an attempt to evaluate their control on the observed fluxes. Measurements of soil-atmosphere CO2 exchanges are reported for four experimental plots within the Singtel-Kranji Radio Transmission Station (103o43'49E, 1o25'53N), an area dominated by Axonopus compressus. Different treatments such as the removal of turf, and application of clippings were effected as a means to determine the fluxes from the various components (respiration of soil and turf, and decomposition of clippings), and to explore the effects of human intervention on observed effluxes. The soil surface CO2 fluxes observed during the daylight hours ranges from 2.835 + 0.772 umol m-2 s-1 for the bare plot as compared to 6.654 + 1.134 umol m-2 s-1 for the turfed plot; this could be attributed to both autotrophic and heterotrophic respiration. Strong controls of both soil temperature and soil moisture are observed on measured soil fluxes. On the base soils, fluxes were positively correlated to soil temperature and negatively to soil moisture. Above the grass, fluxes are negatively correlated soil temperature and positively to soil moisture. The measured values will be combined to carbon stock evaluation in the different compartments to assess carbon budget for green area under different grass management in Singapore.
A comparison of soil-moisture loss from forested and clearcut areas in West Virginia
Charles A. Troendle
1970-01-01
Soil-moisture losses from forested and clearcut areas were compared on the Fernow Experimental Forest. As expected, hardwood forest soils lost most moisture while revegetated clearcuttings, clearcuttings, and barren areas lost less, in that order. Soil-moisture losses from forested soils also correlated well with evapotranspiration and streamflow.
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.
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.
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)
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.
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.
NASA Astrophysics Data System (ADS)
Arumugam, S.; Mazrooei, A.; Lakshmi, V.; Wood, A.
2017-12-01
Subseasonal-to-seasonal (S2S) forecasts of soil moisture and streamflow provides critical information for water and agricultural systems to support short-term planning and mangement. This study evaluates the role of observed streamflow and remotely-sensed soil moisture from SMAP (Soil Moisture Active Passive) mission in improving S2S streamflow and soil moisture forecasting using data assimilation (DA). We first show the ability to forecast soil moisture at monthly-to-seaasonal time scale by forcing climate forecasts with NASA's Land Information System and then compares the developed soil moisture forecast with the SMAP data over the Southeast US. Our analyses show significant skill in forecasting real-time soil moisture over 1-3 months using climate information. We also show that the developed soil moisture forecasts capture the observed severe drought conditions (2007-2008) over the Southeast US. Following that, we consider both SMAP data and observed streamflow for improving S2S streamflow and soil moisture forecasts for a pilot study area, Tar River basin, in NC. Towards this, we consider variational assimilation (VAR) of gauge-measured daily streamflow data in improving initial hydrologic conditions of Variable Infiltration Capacity (VIC) model. The utility of data assimilation is then assessed in improving S2S forecasts of streamflow and soil moisture through a retrospective analyses. Furthermore, the optimal frequency of data assimilation and optimal analysis window (number of past observations to use) are also assessed in order to achieve the maximum improvement in S2S forecasts of streamflow and soil moisture. Potential utility of updating initial conditions using DA and providing skillful forcings are also discussed.
NASA Astrophysics Data System (ADS)
Cotrufo, M. F.; Alberti, G.; Inglima, I.; Marjanović, H.; Lecain, D.; Zaldei, A.; Peressotti, A.; Miglietta, F.
2011-09-01
Precipitation patterns are expected to change in the Mediterranean region within the next decades, with projected decreases in total rainfall and increases in extreme events. We manipulated precipitation patterns in a Mediterranean woodland, dominated by Arbutus unedo L., to study the effects of changing precipitation regimes on above-ground net primary production (ANPP) and soil C dynamics, specifically plant-derived C input to soil and soil respiration (SR). Experimental plots were exposed to either a 20 % reduction of throughfall or to water addition targeted at maintaining soil water content above a minimum of 10 % v/v. Treatments were compared to control plots which received ambient precipitation. Enhanced soil moisture during summer months highly stimulated annual stem primary production, litter fall, SR and net annual plant-derived C input to soil which on average increased by 130 %, 26 %, 58 % and 220 %, respectively, as compared to the control. In contrast, the 20 % reduction in throughfall (equivalent to 10 % reduction in precipitation) did not significantly change soil moisture at the site, and therefore did not significantly affect ANPP or SR. We conclude that minor changes (around 10 % reduction) in precipitation amount are not likely to significantly affect ANPP or soil C dynamics in Mediterranean woodlands. However, if summer rain increases, C cycling will significantly accelerate but soil C stocks are not likely to be changed in the short-term. More studies involving modelling of long-term C dynamics are needed to predict if the estimated increases in soil C input under wet conditions is going to be sustained and if labile C is being substituted to stable C, with a negative effect on long-term soil C stocks.
NASA Astrophysics Data System (ADS)
Cotrufo, M. F.; Alberti, G.; Inglima, I.; Marjanović, H.; Lecain, D.; Zaldei, A.; Peressotti, A.; Miglietta, F.
2011-06-01
Precipitation patterns are expected to change in the Mediterranean region within the next decades, with projected decreases in total rainfall and increases in extreme events. We manipulated precipitation patterns in a Mediterranean woodland, dominated by Arbutus unedo L., to study the effects of changing precipitation regimes on above-ground net primary production (ANPP) and soil C dynamics, specifically plant-derived C input to soil and soil respiration (SR). Experimental plots were exposed to either a 20 % reduction of throughfall or to water addition targeted at maintaining soil water content above a minimum of 10 % v/v. Treatments were compared to control plots which received ambient precipitation. The throughfall manipulation experiment started in 2004 and we report data up to the 2009 growing season. Enhanced soil moisture during summer months highly stimulated annual stem primary production, litter fall, SR and net annual plant-derived C input to soil which on average increased by 130 %, 26 %, 50 % and 220 %, respectively, as compared to control. In contrast, the 20 % reduction in throughfall (equivalent to 10 % reduction of precipitation) did not significantly change soil moisture at the site, and therefore did not significantly affect ANPP or SR. We conclude that minor changes (around 10 % reduction) in precipitation amount are not likely to significantly affect ANPP or soil C dynamics in Mediterranean woodland. However, if summer rain increases, C cycling will significantly accelerate but soil C stocks are not likely to be changed in the short-term. More studies involving modelling of long term C dynamics are needed to predict if the estimated increases in soil C input under wet conditions is going to be sustained and if labile C is being substituted to stable C, with a negative effect on long term soil C stocks.
Means, Mary M.; Ahn, Changwoo; Noe, Gregory
2017-01-01
The resilience of constructed wetland ecosystems to severe disturbance, such as a mass herbivory eat-out or soil disturbance, remains poorly understood. In this study, we use a controlled mesocosm experiment to examine how original planting diversity affects the ability of constructed freshwater wetlands to recover structurally and functionally after a disturbance (i.e., aboveground harvesting and soil coring). We assessed if the planting richness of macrophyte species influences recovery of constructed wetlands one year after a disturbance. Mesocosms were planted in richness groups with various combinations of either 1, 2, 3, or 4 species (RG 1–4) to create a gradient of richness. Structural wetland traits measured include morphological regrowth of macrophytes, soil bulk density, soil moisture, soil %C, and soil %N. Functional wetland traits measured include above ground biomass production, soil potential denitrification, and soil potential microbial respiration. Total mesocosm cover increased along the gradient of plant richness (43.5% in RG 1 to 84.5% in RG 4) in the growing season after the disturbance, although not all planted individuals recovered. This was largely attributed to the dominance of the obligate annual species. The morphology of each species was affected negatively by the disturbance, producing shorter, and fewer stems than in the years prior to the disturbance, suggesting that the communities had not fully recovered one year after the disturbance. Soil characteristics were almost uniform across the planting richness gradient, but for a few exceptions (%C, C:N, and non-growing season soil moisture were higher slightly in RG 2). Denitrification potential (DEA) increased with increasing planting richness and was influenced by the abundance and quality of soil C. Increased open space in unplanted mesocosms and mesocosms with lower species richness increased labile C, leading to higher C mineralization rates.
NASA Astrophysics Data System (ADS)
Akbar, Ruzbeh; Short Gianotti, Daniel; McColl, Kaighin A.; Haghighi, Erfan; Salvucci, Guido D.; Entekhabi, Dara
2018-03-01
The soil water content profile is often well correlated with the soil moisture state near the surface. They share mutual information such that analysis of surface-only soil moisture is, at times and in conjunction with precipitation information, reflective of deeper soil fluxes and dynamics. This study examines the characteristic length scale, or effective depth Δz, of a simple active hydrological control volume. The volume is described only by precipitation inputs and soil water dynamics evident in surface-only soil moisture observations. To proceed, first an observation-based technique is presented to estimate the soil moisture loss function based on analysis of soil moisture dry-downs and its successive negative increments. Then, the length scale Δz is obtained via an optimization process wherein the root-mean-squared (RMS) differences between surface soil moisture observations and its predictions based on water balance are minimized. The process is entirely observation-driven. The surface soil moisture estimates are obtained from the NASA Soil Moisture Active Passive (SMAP) mission and precipitation from the gauge-corrected Climate Prediction Center daily global precipitation product. The length scale Δz exhibits a clear east-west gradient across the contiguous United States (CONUS), such that large Δz depths (>200 mm) are estimated in wetter regions with larger mean precipitation. The median Δz across CONUS is 135 mm. The spatial variance of Δz is predominantly explained and influenced by precipitation characteristics. Soil properties, especially texture in the form of sand fraction, as well as the mean soil moisture state have a lesser influence on the length scale.
Variation in microbial activity in histosols and its relationship to soil moisture.
Tate, R L; Terry, R E
1980-08-01
Microbial biomass, dehydrogenase activity, carbon metabolism, and aerobic bacterial populations were examined in cropped and fallow Pahokee muck (a lithic medisaprist) of the Florida Everglades. Dehydrogenase activity was two- to sevenfold greater in soil cropped to St. Augustinegrass (Stenotaphrum secundatum (Walt) Kuntz) compared with uncropped soil, whereas biomass ranged from equivalence in the two soils to a threefold stimulation in the cropped soil. Biomass in soil cropped to sugarcane (Saccharum spp. L) approximated that from the grass field, whereas dehydrogenase activities of the cane soil were nearly equivalent to those of the fallow soil. Microbial biomass, dehydrogenase activity, aerobic bacterial populations, and salicylate oxidation rates all correlated with soil moisture levels. These data indicate that within the moisture ranges detected in the surface soils, increased moisture stimulated microbial activity, whereas within the soil profile where moisture ranges reached saturation, increased moisture inhibited aerobic activities and stimulated anaerobic processes.
Variation in Microbial Activity in Histosols and Its Relationship to Soil Moisture †
Tate, Robert L.; Terry, Richard E.
1980-01-01
Microbial biomass, dehydrogenase activity, carbon metabolism, and aerobic bacterial populations were examined in cropped and fallow Pahokee muck (a lithic medisaprist) of the Florida Everglades. Dehydrogenase activity was two- to sevenfold greater in soil cropped to St. Augustinegrass (Stenotaphrum secundatum (Walt) Kuntz) compared with uncropped soil, whereas biomass ranged from equivalence in the two soils to a threefold stimulation in the cropped soil. Biomass in soil cropped to sugarcane (Saccharum spp. L) approximated that from the grass field, whereas dehydrogenase activities of the cane soil were nearly equivalent to those of the fallow soil. Microbial biomass, dehydrogenase activity, aerobic bacterial populations, and salicylate oxidation rates all correlated with soil moisture levels. These data indicate that within the moisture ranges detected in the surface soils, increased moisture stimulated microbial activity, whereas within the soil profile where moisture ranges reached saturation, increased moisture inhibited aerobic activities and stimulated anaerobic processes. PMID:16345610
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.
Climate Prediction Center - United States Drought Information
Crop Moisture Indices  Soil Moisture Percentiles (based on NLDAS)  Standardized Runoff Index (based /Minimum  Mean Surface Hydrology (based on NLDAS)  Total Soil Moisture  Total SM Change  MOSAIC Soil Moisture Profile  NOAH Soil Moisture Profile  NOAH Soil T Profile  Evaporation  E-P Â
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)
Wu, Qiusheng; Liu, Hongxing; Wang, Lei; Deng, Chengbin
2016-03-01
High quality soil moisture datasets are required for various environmental applications. The launch of the Advanced Microwave Scanning Radiometer 2 (AMSR2) on board the Global Change Observation Mission 1-Water (GCOM-W1) in May 2012 has provided global near-surface soil moisture data, with an average revisit frequency of two days. Since AMSR2 is a new passive microwave system in operation, it is very important to evaluate the quality of AMSR2 products before widespread utilization of the data for scientific research. In this paper, we provide a comprehensive evaluation of the AMSR2 soil moisture products retrieved by the Japan Aerospace Exploration Agency (JAXA) algorithm. The evaluation was performed for a three-year period (July 2012-June 2015) over the contiguous United States. The AMSR2 soil moisture products were evaluated by comparing ascending and descending overpass products to each other as well as comparing them to in situ soil moisture observations of 598 monitoring stations obtained from the International Soil Moisture Network (ISMN). The accuracy of AMSR2 soil moisture product was evaluated against several types of monitoring networks, and for different land cover types and ecoregions. Three performance metrics, including mean difference (MD), root mean squared difference (RMSD), and correlation coefficient (R), were used in our accuracy assessment. Our evaluation results revealed that AMSR2 soil moisture retrievals are generally lower than in situ measurements. The AMSR2 soil moisture retrievals showed the best agreement with in situ measurements over the Great Plains and the worst agreement over forested areas. This study offers insights into the suitability and reliability of AMSR2 soil moisture products for different ecoregions. Although AMSR2 soil moisture retrievals represent useful and effective measurements for some regions, further studies are required to improve the data accuracy.
NASA Astrophysics Data System (ADS)
Cui, Y.; Long, D.; Hong, Y.; Zeng, C.; Han, Z.
2016-12-01
Reconstruction of FY-3B/MWRI soil moisture using an artificial neural network based on reconstructed MODIS optical products over the Tibetan Plateau Yaokui Cui, Di Long, Yang Hong, Chao Zeng, and Zhongying Han State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China Abstract: Soil moisture is a key variable in the exchange of water and energy between the land surface and the atmosphere, especially over the Tibetan Plateau (TP) which is climatically and hydrologically sensitive as the world's third pole. Large-scale consistent and continuous soil moisture datasets are of importance to meteorological and hydrological applications, such as weather forecasting and drought monitoring. The Fengyun-3B Microwave Radiation Imager (FY-3B/MWRI) soil moisture product is one of relatively new passive microwave products. The FY-3B/MWRI soil moisture product is reconstructed using the back-propagation neural network (BP-NN) based on reconstructed MODIS products, i.e., LST, NDVI, and albedo using different gap-filling methods. The reconstruction method of generating the soil moisture product not only considers the relationship between the soil moisture and the NDVI, LST, and albedo, but also the relationship between the soil moisture and the four-dimensional variation using the longitude, latitude, DEM and day of year (DOY). Results show that the soil moisture could be well reconstructed with R2 larger than 0.63, and RMSE less than 0.1 cm3 cm-3 and bias less than 0.07 cm3 cm-3 for both frozen and unfrozen periods, compared with in-situ measurements in the central TP. The reconstruction method is subsequently applied to generate spatially consistent and temporally continuous surface soil moisture over the TP. The reconstructed FY-3B/MWRI soil moisture product could be valuable in studying meteorology, hydrology, and agriculture over the TP. Keywords: FY-3B/MWRI; Soil moisture; Reconstruction; Tibetan Plateau
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.
Downscaled soil moisture from SMAP evaluated using high density observations
USDA-ARS?s Scientific Manuscript database
Recently, a soil moisture downscaling algorithm based on a regression relationship between daily temperature changes and daily average soil moisture was developed to produce an enhanced spatial resolution on soil moisture product for the Advanced Microwave Scanning Radiometer–EOS (AMSR-E) satellite ...
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...
NASA Astrophysics Data System (ADS)
Xu, Lina; Niu, Ruiqing; Li, Jiong; Dong, Yanfang
2011-12-01
Soil moisture is the important indicator of climate, hydrology, ecology, agriculture and other parameters of the land surface and atmospheric interface. Soil moisture plays an important role on the water and energy exchange at the land surface/atmosphere interface. Remote sensing can provide information on large area quickly and easily, so it is significant to do research on how to monitor soil moisture by remote sensing. This paper presents a method to assess soil moisture status using Landsat TM data over Three Gorges area in China based on TVDI. The potential of Temperature- Vegetation Dryness Index (TVDI) from Landsat TM data in assessing soil moisture was investigated in this region. After retrieving land surface temperature and vegetation index a TVDI model based on the features of Ts-NDVI space is established. And finally, soil moisture status is estimated according to TVDI. It shows that TVDI has the advantages of stability and high accuracy to estimating the soil moisture status.
Evaluating Land-Atmosphere Interactions with the North American Soil Moisture Database
NASA Astrophysics Data System (ADS)
Giles, S. M.; Quiring, S. M.; Ford, T.; Chavez, N.; Galvan, J.
2015-12-01
The North American Soil Moisture Database (NASMD) is a high-quality observational soil moisture database that was developed to study land-atmosphere interactions. It includes over 1,800 monitoring stations the United States, Canada and Mexico. Soil moisture data are collected from multiple sources, quality controlled and integrated into an online database (soilmoisture.tamu.edu). The period of record varies substantially and only a few of these stations have an observation record extending back into the 1990s. Daily soil moisture observations have been quality controlled using the North American Soil Moisture Database QAQC algorithm. The database is designed to facilitate observationally-driven investigations of land-atmosphere interactions, validation of the accuracy of soil moisture simulations in global land surface models, satellite calibration/validation for SMOS and SMAP, and an improved understanding of how soil moisture influences climate on seasonal to interannual timescales. This paper provides some examples of how the NASMD has been utilized to enhance understanding of land-atmosphere interactions in the U.S. Great Plains.
NASA Giovanni: A Tool for Visualizing, Analyzing, and Inter-Comparing Soil Moisture Data
NASA Technical Reports Server (NTRS)
Teng, William; Rui, Hualan; Vollmer, Bruce; deJeu, Richard; Fang, Fan; Lei, Guang-Dih
2012-01-01
There are many existing satellite soil moisture algorithms and their derived data products, but there is no simple way for a user to inter-compare the products or analyze them together with other related data (e.g., precipitation). An environment that facilitates such inter-comparison and analysis would be useful for validation of satellite soil moisture retrievals against in situ data and for determining the relationships between different soil moisture products. The latter relationships are particularly important for applications users, for whom the continuity of soil moisture data, from whatever source, is critical. A recent example was provided by the sudden demise of EOS Aqua AMSR-E and the end of its soil moisture data production, as well as the end of other soil moisture products that had used the AMSR-E brightness temperature data. The purpose of the current effort is to create an environment, as part of the NASA Giovanni family of portals, that facilitates inter-comparisons of soil moisture algorithms and their derived data products.
Microwave remote sensing and its application to soil moisture detection
NASA Technical Reports Server (NTRS)
Newton, R. W. (Principal Investigator)
1977-01-01
The author has identified the following significant results. Experimental measurements were utilized to demonstrate a procedure for estimating soil moisture, using a passive microwave sensor. The investigation showed that 1.4 GHz and 10.6 GHz can be used to estimate the average soil moisture within two depths; however, it appeared that a frequency less than 10.6 GHz would be preferable for the surface measurement. Average soil moisture within two depths would provide information on the slope of the soil moisture gradient near the surface. Measurements showed that a uniform surface roughness similar to flat tilled fields reduced the sensitivity of the microwave emission to soil moisture changes. Assuming that the surface roughness was known, the approximate soil moisture estimation accuracy at 1.4 GHz calculated for a 25% average soil moisture and an 80% degree of confidence, was +3% and -6% for a smooth bare surface, +4% and -5% for a medium rough surface, and +5.5% and -6% for a rough surface.
NASA Astrophysics Data System (ADS)
Bouda, M.
2017-12-01
Root system architecture (RSA) can significantly affect plant access to water, total transpiration, as well as its partitioning by soil depth, with implications for surface heat, water, and carbon budgets. Despite recent advances in land surface model (LSM) descriptions of plant hydraulics, RSA has not been included because of its three-dimensional complexity, which makes RSA modelling generally too computationally costly. This work builds upon the recently introduced "RSA stencil," a process-based 1D layered model that captures the dynamic shifts in water potential gradients of 3D RSA in response to heterogeneous soil moisture profiles. In validations using root systems calibrated to the rooting profiles of four plant functional types (PFT) of the Community Land Model, the RSA stencil predicts plant water potentials within 2% of the outputs of full 3D models, despite its trivial computational cost. In transient simulations, the RSA stencil yields improved predictions of water uptake and soil moisture profiles compared to a 1D model based on root fraction alone. Here I show how the RSA stencil can be calibrated to time-series observations of soil moisture and transpiration to yield a water uptake PFT definition for use in terrestrial models. This model-data integration exercise aims to improve LSM predictions of soil moisture dynamics and, under water-limiting conditions, surface fluxes. These improvements can be expected to significantly impact predictions of downstream variables, including surface fluxes, climate-vegetation feedbacks and soil nutrient cycling.
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.
Bento, Célia P M; Yang, Xiaomei; Gort, Gerrit; Xue, Sha; van Dam, Ruud; Zomer, Paul; Mol, Hans G J; Ritsema, Coen J; Geissen, Violette
2016-12-01
The dissipation kinetics of glyphosate and its metabolite aminomethylphosphonic acid (AMPA) were studied in loess soil, under biotic and abiotic conditions, as affected by temperature, soil moisture (SM) and light/darkness. Nonsterile and sterile soil samples were spiked with 16mgkg -1 of glyphosate, subjected to three SM contents (20% WHC, 60% WHC, saturation), and incubated for 30days at 5°C and 30°C, under dark and light regimes. Glyphosate and AMPA dissipation kinetics were fit to single-first-order (SFO) or first-order-multicompartment (FOMC) models, per treatment combination. AMPA kinetic model included both the formation and decline phases. Glyphosate dissipation kinetics followed SFO at 5°C, but FOMC at 30°C. AMPA followed SFO dissipation kinetics for all treatments. Glyphosate and AMPA dissipation occurred mostly by microbial activity. Abiotic processes played a negligible role for both compounds. Under biotic conditions, glyphosate dissipation and AMPA formation/dissipation were primarily affected by temperature, but also by SM. Light regimes didn't play a significant role. Glyphosate DT50 varied between 1.5 and 53.5days, while its DT90 varied between 8.0 and 280days, depending on the treatment. AMPA persisted longer in soil than glyphosate, with its DT50 at 30°C ranging between 26.4 and 44.5days, and its DT90 between 87.8 and 148days. The shortest DT50/DT90 values for both compounds occurred at 30°C and under optimal/saturated moisture conditions, while the largest occurred at 5°C and reaching drought stress conditions. Based on these results, we conclude that glyphosate and AMPA dissipate rapidly under warm and rainy climate conditions. However, repeated glyphosate applications in fallows or winter crops in countries where cold and dry winters normally occur could lead to on-site soil pollution, with consequent potential risks to the environment and human health. To our knowledge, this study is the first evaluating the combined effect of temperature, soil moisture and light/dark conditions on AMPA formation/dissipation kinetics and behaviour. Copyright © 2016 Elsevier B.V. All rights reserved.
NASA Technical Reports Server (NTRS)
Case, Jonathan L.; Zavodsky, Bradley T.; White, Kristopher D.; Bell, Jesse E.
2015-01-01
This paper provided a brief background on the work being done at NASA SPoRT and the CDC to create a soil moisture climatology over the CONUS at high spatial resolution, and to provide a valuable source of soil moisture information to the CDC for monitoring conditions that could favor the development of Valley Fever. The soil moisture climatology has multi-faceted applications for both the NOAA/NWS situational awareness in the areas of drought and flooding, and for the Public Health community. SPoRT plans to increase its interaction with the drought monitoring and Public Health communities by enhancing this testbed soil moisture anomaly product. This soil moisture climatology run will also serve as a foundation for upgrading the real-time (currently southeastern CONUS) SPoRT-LIS to a full CONUS domain based on LIS version 7 and incorporating real-time GVF data from the Suomi-NPP Visible Infrared Imaging Radiometer Suite (Vargas et al. 2013) into LIS-Noah. The upgraded SPoRT-LIS run will serve as a testbed proof-of-concept of a higher-resolution NLDAS-2 modeling member. The climatology run will be extended to near real-time using the NLDAS-2 meteorological forcing from 2011 to present. The fixed 1981-2010 climatology shall provide the soil moisture "normals" for the production of real-time soil moisture anomalies. SPoRT also envisions a web-mapping type of service in which an end-user could put in a request for either an historical or real-time soil moisture anomaly graph for a specified county (as exemplified by Figure 2) and/or for local and regional maps of soil moisture proxy percentiles. Finally, SPoRT seeks to assimilate satellite soil moisture data from the current Soil Moisture Ocean Salinity (SMOS; Blankenship et al. 2014) and the recently-launched NASA Soil Moisture Active Passive (SMAP; Entekhabi et al. 2010) missions, using the EnKF capability within LIS. The 9-km combined active radar and passive microwave retrieval product from SMAP (Das et al. 2011) has the potential to provide valuable information about the near-surface soil moisture state for improving land surface modeling output.
Long-Term Evaluation of the AMSR-E Soil Moisture Product Over the Walnut Gulch Watershed, AZ
NASA Astrophysics Data System (ADS)
Bolten, J. D.; Jackson, T. J.; Lakshmi, V.; Cosh, M. H.; Drusch, M.
2005-12-01
The Advanced Microwave Scanning Radiometer -Earth Observing System (AMSR-E) was launched aboard NASA's Aqua satellite on May 4th, 2002. Quantitative estimates of soil moisture using the AMSR-E provided data have required routine radiometric data calibration and validation using comparisons of satellite observations, extended targets and field campaigns. The currently applied NASA EOS Aqua ASMR-E soil moisture algorithm is based on a change detection approach using polarization ratios (PR) of the calibrated AMSR-E channel brightness temperatures. To date, the accuracy of the soil moisture algorithm has been investigated on short time scales during field campaigns such as the Soil Moisture Experiments in 2004 (SMEX04). Results have indicated self-consistency and calibration stability of the observed brightness temperatures; however the performance of the moisture retrieval algorithm has been poor. The primary objective of this study is to evaluate the quality of the current version of the AMSR-E soil moisture product for a three year period over the Walnut Gulch Experimental Watershed (150 km2) near Tombstone, AZ; the northern study area of SMEX04. This watershed is equipped with hourly and daily recording of precipitation, soil moisture and temperature via a network of raingages and a USDA-NRCS Soil Climate Analysis Network (SCAN) site. Surface wetting and drying are easily distinguished in this area due to the moderately-vegetated terrain and seasonally intense precipitation events. Validation of AMSR-E derived soil moisture is performed from June 2002 to June 2005 using watershed averages of precipitation, and soil moisture and temperature data from the SCAN site supported by a surface soil moisture network. Long-term assessment of soil moisture algorithm performance is investigated by comparing temporal variations of moisture estimates with seasonal changes and precipitation events. Further comparisons are made with a standard soil dataset from the European Centre for Medium-Range Weather Forecasts. The results of this research will contribute to a better characterization of the low biases and discrepancies currently observed in the AMSR-E soil moisture product.
Data documentation for the bare soil experiment at the University of Arkansas
NASA Technical Reports Server (NTRS)
Waite, W. P.; Scott, H. D. (Principal Investigator); Hancock, G. D.
1980-01-01
The reflectivities of several controlled moisture test plots were investigated. These test plots were of a similar soil texture which was clay loam and were prepared to give a desired initial soil moisture and density profile. Measurements were conducted on the plots as the soil water redistributed for both long term and diurnal cycles. These measurements included reflectivity, gravimetric and volumetric soil moisture, soil moisture potential, and soil temperature.
Soil moisture dynamics and smoldering combustion limits of pocosin soils in North Carolina, USA
James Reardon; Gary Curcio; Roberta Bartlette
2009-01-01
Smoldering combustion of wetland organic soils in the south-eastern USA is a serious management concern. Previous studies have reported smoldering was sensitive to a wide range of moisture contents, but studies of soil moisture dynamics and changing smoldering combustion potential in wetland communities are limited. Linking soil moisture measurements with estimates of...
USDA-ARS?s Scientific Manuscript database
NASA’s Soil Moisture Active Passive (SMAP) mission, scheduled for launch in 2014, will carry the first combined L-band radar and radiometer system with the objective of mapping near surface soil moisture and freeze/thaw state globally at near-daily time step (2-3 days). SMAP will provide three soil ...
[Characteristics of soil moisture in artificial impermeable layers].
Suo, Gai-Di; Xie, Yong-Sheng; Tian, Fei; Chuai, Jun-Feng; Jing, Min-Xiao
2014-09-01
For the problem of low water and fertilizer use efficiency caused by nitrate nitrogen lea- ching into deep soil layer and soil desiccation in dryland apple orchard, characteristics of soil moisture were investigated by means of hand tamping in order to find a new approach in improving the water and fertilizer use efficiency in the apple orchard. Two artificial impermeable layers of red clay and dark loessial soil were built in soil, with a thickness of 3 or 5 cm. Results showed that artificial impermeable layers with the two different thicknesses were effective in reducing or blocking water infiltration into soil and had higher seepage controlling efficiency. Seepage controlling efficiency for the red clay impermeable layer was better than that for the dark loessial soil impermeable layer. Among all the treatments, the red clay impermeable layer of 5 cm thickness had the highest bulk density, the lowest initial infiltration rate (0.033 mm · min(-1)) and stable infiltration rate (0.018 mm · min(-1)) among all treatments. After dry-wet alternation in summer and freezing-thawing cycle in winter, its physiochemical properties changed little. Increase in years did not affect stable infiltration rate of soil water. The red clay impermeable layer of 5 cm thickness could effectively increase soil moisture content in upper soil layer which was conducive to raise the water and nutrient use efficiency. The approach could be applied to the apple production of dryland orchard.
1986-10-01
AD-AI?5 394 RESILIENT MODULUS OF FREEZE-THAN AFFECTED GRANULAR 1/1 SOILS FOR PAVEMENT DES . .( U) COLD REGIONS RESEARCH AND ENGINEERING LAB HANOVER NH...Chamberlain, who had a major role in the de - velopment of the laboratory testing techniques; Glenn Durell, who conducted the resilient modulus testing; and...notorious. In areas of seasonal moisture tension, and the stresses imposed in the frost the supporting capacity of subgrade soils and triaxial tests. For
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.
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.
Multifrequency remote sensing of soil moisture. [Guymon, Oklahoma and Dalhart, Texas
NASA Technical Reports Server (NTRS)
Theis, S. W.; Mcfarland, M. J.; Rosenthal, W. D.; Jones, C. L. (Principal Investigator)
1982-01-01
Multifrequency sensor data collected at Guymon, Oklahoma and Dalhart, Texas using NASA's C-130 aircraft were used to determine which of the all-weather microwave sensors demonstrated the highest correlation to surface soil moisture over optimal bare soil conditions, and to develop and test techniques which use visible/infrared sensors to compensate for the vegetation effect in this sensor's response to soil moisture. The L-band passive microwave radiometer was found to be the most suitable single sensor system to estimate soil moisture over bare fields. In comparison to other active and passive microwave sensors the L-band radiometer (1) was influenced least by ranges in surface roughness; (2) demonstrated the most sensitivity to soil moisture differences in terms of the range of return from the full range of soil moisture; and (3) was less sensitive to errors in measurement in relation to the range of sensor response. L-band emissivity related more strongly to soil moisture when moisture was expressed as percent of field capacity. The perpendicular vegetation index as determined from the visible/infrared sensors was useful as a measure of the vegetation effect on the L-band radiometer response to soil moisture.
Evaluation of soil pH and moisture content on in-situ ozonation of pyrene in soils.
Luster-Teasley, S; Ubaka-Blackmoore, N; Masten, S J
2009-08-15
In this study, pyrene spiked soil (300 ppm) was ozonated at pH levels of 2, 6, and 8 and three moisture contents. It was found that soil pH and moisture content impacted the effectiveness of PAH oxidation in unsaturated soils. In air-dried soils, as pH increased, removal increased, such that pyrene removal efficiencies at pH 6 and pH 8 reached 95-97% at a dose of 2.22 mg O(3)/mg pyrene. Ozonation at 16.2+/-0.45 mg O(3)/ppm pyrene in soil resulted in 81-98% removal of pyrene at all pH levels tested. Saturated soils were tested at dry, 5% or 10% moisture conditions. The removal of pyrene was slower in moisturized soils, with the efficiency decreasing as the moisture content increased. Increasing the pH of the soil having a moisture content of 5% resulted in improved pyrene removals. On the contrary, in the soil having a moisture content of 10%, as the pH increased, pyrene removal decreased. Contaminated PAH soils were stored for 6 months to compare the efficiency of PAH removal in freshly contaminated soil and aged soils. PAH adsorption to soil was found to increase with longer exposure times; thus requiring much higher doses of ozone to effectively oxidize pyrene.
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
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.
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.
Tucker, Colin L.; Tamang, Shanker; Pendall, Elise; ...
2016-05-01
In sagebrush steppe, snowpack may govern soil respiration through its effect on multiple abiotic and biotic factors. Across the Intermountain West of the United States, snowpack has been declining for decades and is projected to decline further over the next century, making the response of soil respiration to snowpack a potentially important factor in the ecosystem carbon cycle. In this study, we evaluated the direct and indirect roles of the snowpack in driving soil respiration in sagebrush steppe ecosystems by taking advantage of highway snowfences in Wyoming to manipulate snowpack. An important contribution of this study is the use ofmore » Bayesian modeling to quantify the effects of soil moisture and temperature on soil respiration across a wide range of conditions from frozen to hot and dry, while simultaneously accounting for biotic factors (e.g., vegetation cover, root density, and microbial biomass and substrate-use diversity) affected by snowpack. Elevated snow depth increased soil temperature (in the winter) and moisture (winter and spring), and was associated with reduced vegetation cover and microbial biomass carbon. Soil respiration showed an exponential increase with temperature, with a temperature sensitivity that decreased with increasing seasonal temperature (Q 10 = 4.3 [winter], 2.3 [spring], and 1.7 [summer]); frozen soils were associated with unrealistic Q 10 approximate to 7989 due to the liquid-to-ice transition of soil water. Soil respiration was sensitive to soil water content; predicted respiration under very dry conditions was less than 10% of respiration under moist conditions. While higher vegetation cover increased soil respiration, this was not due to increased root density, and may reflect differences in litter inputs. Microbial substrate-use diversity was negatively related to reference respiration (i.e., respiration rate at a reference temperature and optimal soil moisture), although the mechanism remains unclear. Lastly, this study indicates that soil respiration is inhibited by shallow snowpack through multiple mechanisms; thus, future decreases in snowpack across the sagebrush steppe have the potential to reduce losses of soil C, potentially affecting regional carbon balance.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tucker, Colin L.; Tamang, Shanker; Pendall, Elise
In sagebrush steppe, snowpack may govern soil respiration through its effect on multiple abiotic and biotic factors. Across the Intermountain West of the United States, snowpack has been declining for decades and is projected to decline further over the next century, making the response of soil respiration to snowpack a potentially important factor in the ecosystem carbon cycle. In this study, we evaluated the direct and indirect roles of the snowpack in driving soil respiration in sagebrush steppe ecosystems by taking advantage of highway snowfences in Wyoming to manipulate snowpack. An important contribution of this study is the use ofmore » Bayesian modeling to quantify the effects of soil moisture and temperature on soil respiration across a wide range of conditions from frozen to hot and dry, while simultaneously accounting for biotic factors (e.g., vegetation cover, root density, and microbial biomass and substrate-use diversity) affected by snowpack. Elevated snow depth increased soil temperature (in the winter) and moisture (winter and spring), and was associated with reduced vegetation cover and microbial biomass carbon. Soil respiration showed an exponential increase with temperature, with a temperature sensitivity that decreased with increasing seasonal temperature (Q 10 = 4.3 [winter], 2.3 [spring], and 1.7 [summer]); frozen soils were associated with unrealistic Q 10 approximate to 7989 due to the liquid-to-ice transition of soil water. Soil respiration was sensitive to soil water content; predicted respiration under very dry conditions was less than 10% of respiration under moist conditions. While higher vegetation cover increased soil respiration, this was not due to increased root density, and may reflect differences in litter inputs. Microbial substrate-use diversity was negatively related to reference respiration (i.e., respiration rate at a reference temperature and optimal soil moisture), although the mechanism remains unclear. Lastly, this study indicates that soil respiration is inhibited by shallow snowpack through multiple mechanisms; thus, future decreases in snowpack across the sagebrush steppe have the potential to reduce losses of soil C, potentially affecting regional carbon balance.« less
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)
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)
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.
Drought monitoring with soil moisture active passive (SMAP) measurements
NASA Astrophysics Data System (ADS)
Mishra, Ashok; Vu, Tue; Veettil, Anoop Valiya; Entekhabi, Dara
2017-09-01
Recent launch of space-borne systems to estimate surface soil moisture may expand the capability to map soil moisture deficit and drought with global coverage. In this study, we use Soil Moisture Active Passive (SMAP) soil moisture geophysical retrieval products from passive L-band radiometer to evaluate its applicability to forming agricultural drought indices. Agricultural drought is quantified using the Soil Water Deficit Index (SWDI) based on SMAP and soil properties (field capacity and available water content) information. The soil properties are computed using pedo-transfer function with soil characteristics derived from Harmonized World Soil Database. The SMAP soil moisture product needs to be rescaled to be compatible with the soil parameters derived from the in situ stations. In most locations, the rescaled SMAP information captured the dynamics of in situ soil moisture well and shows the expected lag between accumulations of precipitation and delayed increased in surface soil moisture. However, the SMAP soil moisture itself does not reveal the drought information. Therefore, the SMAP based SWDI (SMAP_SWDI) was computed to improve agriculture drought monitoring by using the latest soil moisture retrieval satellite technology. The formulation of SWDI does not depend on longer data and it will overcome the limited (short) length of SMAP data for agricultural drought studies. The SMAP_SWDI is further compared with in situ Atmospheric Water Deficit (AWD) Index. The comparison shows close agreement between SMAP_SWDI and AWD in drought monitoring over Contiguous United States (CONUS), especially in terms of drought characteristics. The SMAP_SWDI was used to construct drought maps for CONUS and compared with well-known drought indices, such as, AWD, Palmer Z-Index, sc-PDSI and SPEI. Overall the SMAP_SWDI is an effective agricultural drought indicator and it provides continuity and introduces new spatial mapping capability for drought monitoring. As an agricultural drought index, SMAP_SWDI has potential to capture short term moisture information similar to AWD and related drought indices.
National Centers for Environmental Prediction
) soilm1 0-10cm soil moisture soilm2 10-40cm soil moisture soilm3 40-100cm soil moisture soilm4 100-200cm soil moisture soilt1 0-10cm soil temperature soilt2 10-40cm soil temperature soilt3 40-100cm soil temperature soilt4 100-200cm soil temperature thick700.ptype 850-700mb thickness precipitation type thick850
Wang, Yongsheng; Cheng, Shulan; Fang, Huajun; Yu, Guirui; Xu, Minjie; Dang, Xusheng; Li, Linsen; Wang, Lei
2014-01-01
To date, few studies are conducted to quantify the effects of reduced ammonium (NH4+) and oxidized nitrate (NO3-) on soil CH4 uptake and N2O emission in the subtropical forests. In this study, NH4Cl and NaNO3 fertilizers were applied at three rates: 0, 40 and 120 kg N ha(-1) yr(-1). Soil CH4 and N2O fluxes were determined twice a week using the static chamber technique and gas chromatography. Soil temperature and moisture were simultaneously measured. Soil dissolved N concentration in 0-20 cm depth was measured weekly to examine the regulation to soil CH4 and N2O fluxes. Our results showed that one year of N addition did not affect soil temperature, soil moisture, soil total dissolved N (TDN) and NH4+-N concentrations, but high levels of applied NH4Cl and NaNO3 fertilizers significantly increased soil NO3(-)-N concentration by 124% and 157%, respectively. Nitrogen addition tended to inhibit soil CH4 uptake, but significantly promoted soil N2O emission by 403% to 762%. Furthermore, NH4+-N fertilizer application had a stronger inhibition to soil CH4 uptake and a stronger promotion to soil N2O emission than NO3(-)-N application. Also, both soil CH4 and N2O fluxes were driven by soil temperature and moisture, but soil inorganic N availability was a key integrator of soil CH4 uptake and N2O emission. These results suggest that the subtropical plantation soil sensitively responses to atmospheric N deposition, and inorganic N rather than organic N is the regulator to soil CH4 uptake and N2O emission.
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.
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.
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.
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.
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.
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.
Hamerlynck, Erik P; Scott, Russell L; Susan Moran, M; Schwander, Andrea M; Connor, Erin; Huxman, Travis E
2011-01-01
It is not clear if tree canopies in savanna ecosystems exert positive or negative effects on soil moisture, and how these might affect understory plant carbon balance. To address this, we quantified rooting-zone volumetric soil moisture (θ(25 cm)), plant size, leaf-level and whole-plant gas exchange of the bunchgrass, bush muhly (Muhlenbergia porteri), growing under and between mesquite (Prosopis velutina) in a southwestern US savanna. Across two contrasting monsoon seasons, bare soil θ(25 cm) was 1.0-2.5% lower in understory than in the intercanopy, and was consistently higher than in soils under grasses, where θ(25 cm) was similar between locations. Understory plants had smaller canopy areas and volumes with larger basal diameters than intercanopy plants. During an above-average monsoon, intercanopy and understory plants had similar seasonal light-saturated leaf-level photosynthesis (A(net-sat)), stomatal conductance (g(s-sat)), and whole-plant aboveground respiration (R(auto)), but with higher whole-plant photosynthesis (GEP(plant)) and transpiration (T(plant)) in intercanopy plants. During a below-average monsoon, intercanopy plants had higher diurnally integrated GEP(plant), R(auto), and T(plant). These findings showed little evidence of strong, direct positive canopy effects to soil moisture and attendant plant performance. Rather, it seems understory conditions foster competitive dominance by drought-tolerant species, and that positive and negative canopy effects on soil moisture and community and ecosystem processes depends on a suite of interacting biotic and abiotic factors.
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)
Dorigo, W. A.; Wagner, W.; Hohensinn, R.; Hahn, S.; Paulik, C.; Drusch, M.; Mecklenburg, S.; van Oevelen, P.; Robock, A.; Jackson, T.
2011-02-01
In situ measurements of soil moisture are invaluable for calibrating and validating land surface models and satellite-based soil moisture retrievals. In addition, long-term time series of in situ soil moisture measurements themselves can reveal trends in the water cycle related to climate or land cover change. Nevertheless, on a worldwide basis the number of meteorological networks and stations measuring soil moisture, in particular on a continuous basis, is still limited and the data they provide lack standardization of technique and protocol. To overcome many of these limitations, the International Soil Moisture Network (ISMN; http://www.ipf.tuwien.ac.at/insitu) was initiated to serve as a centralized data hosting facility where globally available in situ soil moisture measurements from operational networks and validation campaigns are collected, harmonized, and made available to users. Data collecting networks share their soil moisture datasets with the ISMN on a voluntary and no-cost basis. Incoming soil moisture data are automatically transformed into common volumetric soil moisture units and checked for outliers and implausible values. Apart from soil water measurements from different depths, important metadata and meteorological variables (e.g., precipitation and soil temperature) are stored in the database. These will assist the user in correctly interpreting the soil moisture data. The database is queried through a graphical user interface while output of data selected for download is provided according to common standards for data and metadata. Currently (status January 2011), the ISMN contains data of 16 networks and more than 500 stations located in the North America, Europe, Asia, and Australia. The time period spanned by the entire database runs from 1952 until the present, although most datasets have originated during the last decade. The database is rapidly expanding, which means that both the number of stations and the time period covered by the existing stations are still growing. Hence, it will become an increasingly important resource for validating and improving satellite-derived soil moisture products and studying climate related trends. As the ISMN is animated by the scientific community itself, we invite potential networks to enrich the collection by sharing their in situ soil moisture data.
NASA Astrophysics Data System (ADS)
Dorigo, W. A.; Wagner, W.; Hohensinn, R.; Hahn, S.; Paulik, C.; Xaver, A.; Gruber, A.; Drusch, M.; Mecklenburg, S.; van Oevelen, P.; Robock, A.; Jackson, T.
2011-05-01
In situ measurements of soil moisture are invaluable for calibrating and validating land surface models and satellite-based soil moisture retrievals. In addition, long-term time series of in situ soil moisture measurements themselves can reveal trends in the water cycle related to climate or land cover change. Nevertheless, on a worldwide basis the number of meteorological networks and stations measuring soil moisture, in particular on a continuous basis, is still limited and the data they provide lack standardization of technique and protocol. To overcome many of these limitations, the International Soil Moisture Network (ISMN; http://www.ipf.tuwien.ac.at/insitu) was initiated to serve as a centralized data hosting facility where globally available in situ soil moisture measurements from operational networks and validation campaigns are collected, harmonized, and made available to users. Data collecting networks share their soil moisture datasets with the ISMN on a voluntary and no-cost basis. Incoming soil moisture data are automatically transformed into common volumetric soil moisture units and checked for outliers and implausible values. Apart from soil water measurements from different depths, important metadata and meteorological variables (e.g., precipitation and soil temperature) are stored in the database. These will assist the user in correctly interpreting the soil moisture data. The database is queried through a graphical user interface while output of data selected for download is provided according to common standards for data and metadata. Currently (status May 2011), the ISMN contains data of 19 networks and more than 500 stations located in North America, Europe, Asia, and Australia. The time period spanned by the entire database runs from 1952 until the present, although most datasets have originated during the last decade. The database is rapidly expanding, which means that both the number of stations and the time period covered by the existing stations are still growing. Hence, it will become an increasingly important resource for validating and improving satellite-derived soil moisture products and studying climate related trends. As the ISMN is animated by the scientific community itself, we invite potential networks to enrich the collection by sharing their in situ soil moisture data.
Hinkle, M.E.
1991-01-01
To increase understanding of natural variations in soil gas concentrations, CO2, He, O2 and N2 were measured in soil gases collected regularly for several months from four sites at the Roosevelt Hot Springs Known Geothermal Resource Area, Utah. Soil temperature, air temperature, per cent relative humidity, barometric pressure and amounts of rain and snowfall were also monitored to determine the effect of meteorological parameters on concentrations of the measured gases. Considerable seasonal variation existed in concentrations of CO2 and He. The parameters that most affected the soil-gas concentrations were soil and air temperatures. Moisture from rain and snow probably affected the soil-gas concentrations also. However, annual variations in meteorological parameters did not appear to affect measurements of anomalous concentrations in samples collected within a time period of a few days. Production from some of the geothermal wells probably affected the soil-gas concentrations. ?? 1990.
Alba, Christina; NeSmith, Julienne E; Fahey, Catherine; Angelini, Christine; Flory, Stephen Luke
2017-03-01
Abiotic global change drivers affect ecosystem structure and function, but how they interact with biotic factors such as invasive plants is understudied. Such interactions may be additive, synergistic, or offsetting, and difficult to predict. We present methods to test the individual and interactive effects of drought and plant invasion on native ecosystems. We coupled a factorial common garden experiment containing resident communities exposed to drought (imposed with rainout shelters) and invasion with a field experiment where the invader was removed from sites spanning a natural soil moisture gradient. We detail treatments and their effects on abiotic conditions, including soil moisture, light, temperature, and humidity, which shape community and ecosystem responses. Ambient precipitation during the garden experiment exceeded historic norms despite severe drought in prior years. Soil moisture was 48% lower in drought than ambient plots, but the invader largely offset drought effects. Additionally, temperature and light were lower and humidity higher in invaded plots. Field sites spanned up to a 10-fold range in soil moisture and up to a 2.5-fold range in light availability. Invaded and resident vegetation did not differentially mediate soil moisture, unlike in the garden experiment. Herbicide effectively removed invaded and resident vegetation, with removal having site-specific effects on soil moisture and light availability. However, light was generally higher in invader-removal than control plots, whereas resident removal had less effect on light, similar to the garden experiment. Invasion mitigated a constellation of abiotic conditions associated with drought stress in the garden experiment. In the field, where other factors co-varied, these patterns did not emerge. Still, neither experiment suggested that drought and invasion will have synergistic negative effects on ecosystems, although invasion can limit light availability. Coupling factorial garden experiments with field experiments across environmental gradients will be effective for predicting how multiple stressors interact in natural systems.
NASA Astrophysics Data System (ADS)
Padhee, S. K.; Nikam, B. R.; Aggarwal, S. P.; Garg, V.
2014-11-01
Drought is an extreme condition due to moisture deficiency and has adverse effect on society. Agricultural drought occurs when restraining soil moisture produces serious crop stress and affects the crop productivity. The soil moisture regime of rain-fed agriculture and irrigated agriculture behaves differently on both temporal and spatial scale, which means the impact of meteorologically and/or hydrological induced agriculture drought will be different in rain-fed and irrigated areas. However, there is a lack of agricultural drought assessment system in Indian conditions, which considers irrigated and rain-fed agriculture spheres as separate entities. On the other hand recent advancements in the field of earth observation through different satellite based remote sensing have provided researchers a continuous monitoring of soil moisture, land surface temperature and vegetation indices at global scale, which can aid in agricultural drought assessment/monitoring. Keeping this in mind, the present study has been envisaged with the objective to develop agricultural drought assessment and prediction technique by spatially and temporally assimilating effective drought index (EDI) with remote sensing derived parameters. The proposed technique takes in to account the difference in response of rain-fed and irrigated agricultural system towards agricultural drought in the Bundelkhand region (The study area). The key idea was to achieve the goal by utilizing the integrated scenarios from meteorological observations and soil moisture distribution. EDI condition maps were prepared from daily precipitation data recorded by Indian Meteorological Department (IMD), distributed within the study area. With the aid of frequent MODIS products viz. vegetation indices (VIs), and land surface temperature (LST), the coarse resolution soil moisture product from European Space Agency (ESA) were downscaled using linking model based on Triangle method to a finer resolution soil moisture product. EDI and spatially downscaled soil moisture products were later used with MODIS 16 days NDVI product as key elements to assess and predict agricultural drought in irrigated and rain-fed agricultural systems in Bundelkhand region of India. Meteorological drought, soil moisture deficiency and NDVI degradation were inhabited for each and every pixel of the image in GIS environment, for agricultural impact assessment at a 16 day temporal scale for Rabi seasons (October-April) between years 2000 to 2009. Based on the statistical analysis, good correlations were found among the parameters EDI and soil moisture anomaly; NDVI anomaly and soil moisture anomaly lagged to 16 days and these results were exploited for the development of a linear prediction model. The predictive capability of the developed model was validated on the basis of spatial distribution of predicted NDVI which was compared with MODIS NDVI product in the beginning of preceding Rabi season (Oct-Dec of 2010).The predictions of the model were based on future meteorological data (year 2010) and were found to be yielding good results. The developed model have good predictive capability based on future meteorological data (rainfall data) availability, which enhances its utility in analyzing future Agricultural conditions if meteorological data is available.
USDA-ARS?s Scientific Manuscript database
The contrast between the point-scale nature of current ground-based soil moisture instrumentation and the footprint resolution (typically >100 square kilometers) of satellites used to retrieve soil moisture poses a significant challenge for the validation of data products from satellite missions suc...
Remote sensing of an agricultural soil moisture network in Walnut Creek, Iowa
USDA-ARS?s Scientific Manuscript database
The calibration and validation of soil moisture remote sensing products is complicated by the logistics of installing a soil moisture network for a long term period in an active landscape. Usually soil moisture sensors are added to existing precipitation networks which have as a singular requiremen...
Evaluation of SMOS soil moisture products over the CanEx-SM10 area
USDA-ARS?s Scientific Manuscript database
The Soil Moisture and Ocean Salinity (SMOS) Earth observation satellite was launched in November 2009 to provide global soil moisture and ocean salinity measurements based on L-Band passive microwave measurements. Since its launch, different versions of SMOS soil moisture products processors have be...
SMOS soil moisture validation with U.S. in situ newworks
USDA-ARS?s Scientific Manuscript database
Estimation of soil moisture at large scale has been performed using several satellite-based passive microwave sensors using a variety of retrieval methods. The most recent source of soil moisture is the European Space Agency Soil Moisture and Ocean Salinity (SMOS) mission. Since it is a new sensor u...
Potential of bias correction for downscaling passive microwave and soil moisture data
USDA-ARS?s Scientific Manuscript database
Passive microwave satellites such as SMOS (Soil Moisture and Ocean Salinity) or SMAP (Soil Moisture Active Passive) observe brightness temperature (TB) and retrieve soil moisture at a spatial resolution greater than most hydrological processes. Bias correction is proposed as a simple method to disag...
Validation of SMAP surface soil moisture products with core validation sites
USDA-ARS?s Scientific Manuscript database
The NASA Soil Moisture Active Passive (SMAP) mission has utilized a set of core validation sites as the primary methodology in assessing the soil moisture retrieval algorithm performance. Those sites provide well-calibrated in situ soil moisture measurements within SMAP product grid pixels for diver...
Evaluating soil moisture retrievals from ESA's SMOS and NASA's SMAP brightness temperature datasets
USDA-ARS?s Scientific Manuscript database
Two satellites are currently monitoring surface soil moisture (SM) from L-band observations: SMOS (Soil Moisture and Ocean Salinity), a European Space Agency (ESA) satellite that was launched on November 2, 2009 and SMAP (Soil Moisture Active Passive), a National Aeronautics and Space Administration...
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...
Precipitation estimation using L-Band and C-Band soil moisture retrievals
USDA-ARS?s Scientific Manuscript database
An established methodology for estimating precipitation amounts from satellite-based soil moisture retrievals is applied to L-band products from the Soil Moisture Active Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) satellite missions and to a C-band product from the Advanced Scatterome...
USDA-ARS?s Scientific Manuscript database
Soil moisture is an intrinsic state variable that varies considerably in space and time. From a hydrologic viewpoint, soil moisture controls runoff, infiltration, storage and drainage. Soil moisture determines the partitioning of the incoming radiation between latent and sensible heat fluxes. Althou...
NASA Astrophysics Data System (ADS)
Azorin-Molina, Cesar; Vicente-Serrano, Sergio M.; Cerdà, Artemi
2013-04-01
Within the Soil Erosion and Degradation Research Group Experimental Stations, soil moisture is being researched as a key factor of the soil hydrology and soil erosion (Cerdà, 1995; Cerda, 1997; Cerdà 1998). This because under semiarid conditions soil moisture content plays a crucial role for agriculture, forest, groundwater recharge and soil chemistry and scientific improvement is of great interest in agriculture, hydrology and soil sciences. Soil moisture has been seeing as the key factor for plant photosynthesis, respiration and transpiration in orchards (Schneider and Childers, 1941) and plant growth (Veihmeyer and Hendrickson, 1950). Moreover, soil moisture determine the root growth and distribution (Levin et al., 1979) and the soil respiration ( Velerie and Orchard, 1983). Water content is expressed as a ratio, ranging from 0 (dry) to the value of soil porosity at saturation (wet). In this study we present 1-year of soil moisture measurements at two experimental sites in the Valencia region, Eastern Spain: one representing rainfed orchard typical from the Mediterranean mountains (El Teularet-Sierra de Enguera), and a second site corresponding to an irrigated orange crop (Alcoleja). The EC-5 soil moisture smart sensor S-SMC-M005 integrated with the field-proven ECH2O™ Sensor and a 12-bit A/D has been choosen for measuring soil water content providing ±3% accuracy in typical soil conditions. Soil moisture measurements were carried out at 5-minute intervals from January till December 2012. In addition, soil moisture was measured at two depths in each landscape: 2 and 20 cm depth - in order to retrieve a representative vertical cross-section of soil moisture. Readings are provided directly from 0 (dry) to 0.450 m3/m3 (wet) volumetric water content. The soil moisture smart sensor is conected to a HOBO U30 Station - GSM-TCP which also stored 5-minute temperature, relative humidity, dew point, global solar radiation, precipitation, wind speed and wind direction data. These complementary atmospheric measurements will serve to explain the intraannual and vertical variations observed in the soil moisture content in both experimental landscapes. This kind of study is aimed to understand the soil moisture content in two different environments such as irrigated rainfed orchards in a semi-arid region. For instance, these measurements have a direct impact on water availability for crops, plant transpiration and could have practical applications to schedule irrigation. Additionally, soil water content has also implications for erosion processes. Key Words: Water, Agriculture, Irrigation, Eastern Spain, Citrus. Acknowledgements The research projects GL2008-02879/BTE and LEDDRA 243857 supported this research. References Cerdà, A. 1995. Soil moisture regime under simulated rainfall in a three years abandoned field in Southeast Spain. Physics and Chemistry of The Earth, 20 (3-4), 271-279. Cerdà, A. 1997. Seasonal Changes of the Infiltration Rates in a Typical Mediterranean Scrubland on Limestone in Southeast Spain. Journal of Hydrology, 198 (1-4) 198-209 Cerdà, A. 1998. Effect of climate on surface flow along a climatological gradient in Israel. A field rainfall simulation approach. Journal of Arid Environments, 38, 145-159. Levin, I., Assaf, R., and Bravdo, B. 1979. Soil moisture and root distribution in an apple orchard irrigated by tricklers. Plant and Soil, 52, 31-40. Schneider, G. W. And Childers, N.F. 1941. Influence of soil moisture on photosynthesis, respiration and transpiration of apples leaves. Plant Physiol., 16, 565-583. Valerie, A. and Orchard, F.J. Cook. 1983. Relationship between soil respiration and soil moisture. Soil Biology and Biochemistry, 15, 447-453. Veihmeyer, F. J. and Hendrickson, A. H. 1950. Soil Moisture in Relation to Plant Growth. Annual Review of Plant Physiology, 1, 285-304.
Inventory of File gfs.t06z.sfluxgrbf00.grib2
Volumetric Soil Moisture Content [Fraction] 007 0.1-0.4 m below ground SOILW analysis Volumetric Soil Volumetric Soil Moisture Content [Fraction] 068 1-2 m below ground SOILW analysis Volumetric Soil Moisture analysis Temperature [K] 071 0-0.1 m below ground SOILL analysis Liquid Volumetric Soil Moisture (non
Impact of DEM and soils on topographic index, as used in TopoSWAT
USDA-ARS?s Scientific Manuscript database
A topographic index (TI), comprised of slope and upstream contributing area, is used in TopoSWAT to help account for variable source runoff and soil moisture. The level of precision in the GIS input data layers can substantially impact the calculations of the topographic index layer and affect the a...
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.
Soil water dynamics during precipitation in genetic horizons of Retisol
NASA Astrophysics Data System (ADS)
Zaleski, Tomasz; Klimek, Mariusz; Kajdas, Bartłomiej
2017-04-01
Retisols derived from silty deposits dominate in the soil cover of the Carpathian Foothills. The hydrophysical properties of these are determined by the grain-size distribution of the parent material and the soil's "primary" properties shaped in the deposition process. The other contributing factors are the soil-forming processes, such as lessivage (leaching of clay particles), and the morphogenetic processes that presently shape the relief. These factors are responsible for the "secondary" differentiation of hydrophysical properties across the soil profile. Both the primary and secondary hydrophysical properties of soils (the rates of water retention, filtration and infiltration, and the moisture distribution over the soil profile) determine their ability to take in rainfall, the amount of rainwater taken in, and the ways of its redistribution. The aims of the study, carried out during 2015, were to investigate the dynamics of soil moisture in genetic horizons of Retisol derived from silty deposits and to recognize how fast and how deep water from precipitation gets into soil horizons. Data of soil moisture were measured using 5TM moisture and temperature sensor and collected by logger Em50 (Decagon Devices USA). Data were captured every 10 minutes from 6 sensors at depths: - 10 cm, 20 cm, 40 cm, 60 cm and 80 cm. Precipitation data come from meteorological station situated 50 m away from the soil profile. Two zones differing in the type of water regime were distinguished in Retisol: an upper zone comprising humic and eluvial horizons, and a lower zone consisting of illuvial and parent material horizons. The upper zone shows smaller retention of water available for plants, and relatively wide fluctuations in moisture content, compared to the lower zone. The lower zone has stable moisture content during the vegetation season, with values around the water field capacity. Large changes in soil moisture were observed while rainfall. These changes depend on the volume of the precipitation and soil moisture before the precipitation. The following changes of moisture in the soil profile during precipitation were distinguished: if soil moisture in upper zone horizons oscillates around field capacity (higher than 0.30 m3ṡm-3) there is an evident increase in soil moisture also in the lower zone horizons. If soil moisture in the upper zone horizons is much lower than the field capacity (less than 0.20 m3ṡm-3), the soil moisture in the lower zone has very little fluctuations. The range of wetting front in the soil profile depends on the volume of the precipitation and soil moisture. The heavier precipitation, the wetting front in soil profile reaches deeper horizons. The wetter the soil is, the faster soil moisture in the deeper genetic horizons increase. This Research was financed by the Ministry of Science and Higher Education of the Republic of Poland, DS No. 3138/KGiOG/2016.
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.
The response of arid soil communities to climate change: Chapter 8
Steven, Blaire; McHugh, Theresa Ann; Reed, Sasha C.
2017-01-01
Arid and semiarid ecosystems cover approximately 40% of Earth’s terrestrial surface and are present on each of the planet’s continents [1]. Drylands are characterized by their aridity, but there is substantial geographic, edaphic, and climatic variability among these vast ecosystems, and these differences underscore substantial variation in dryland soil microbial communities, as well as in the future climates predicted among arid and semiarid systems globally. Furthermore, arid ecosystems are commonly patchy at a variety of spatial scales [2,3]. Vascular plants are widely interspersed in drylands and bare soil, or soil that is covered with biological soil crusts, fill these spaces. The variability acts to further enhance spatial heterogeneity, as these different zones within dryland ecosystems differ in characteristics such as water retention, albedo, and nutrient cycling [4–6]. Importantly, the various soil patches of an arid landscape may be differentially sensitive to climate change. Soil communities are only active when enough moisture is available, and drylands show large spatial variability in soil moisture, with potentially long dry periods followed by pulses of moisture. The pulse dynamics associated with this wetting and drying affect the composition, structure, and function of dryland soil communities, and integrate biotic and abiotic processes via pulse-driven exchanges, interactions, transitions, and transfers. Climate change will likely alter the size, frequency, and intensity of future precipitation pulses, as well as influence non-rainfall sources of soil moisture, and aridland ecosystems are known to be highly sensitive to such climate variability. Despite great heterogeneity, arid ecosystems are united by a key parameter: a limitation in water availability. This characteristic may help to uncover unifying aspects of dryland soil responses to global change. The dryness of an ecosystem can be described by its aridity index (AI). Several AIs have been proposed, but the most widely used metrics determine the difference between average precipitation and potential evapotranspiration, where evapotranspiration is the sum of evaporation and plant transpiration, both of which move water from the ecosystem to the atmosphere [7–9]. Because evapotranspiration can be affected by various environmental factors such as temperature and incident radiation (Fig. 10.1), regions that receive the same average precipitation may have significantly different AI values [10,11]. Multiple studies have documented that mean annual precipitation, and thus AI, is highly correlated with biological diversity and net primary productivity [12–15]. Accordingly, AI is considered to be a central regulator of the diversity, structure, and productivity of an ecosystem, playing an especially influential role in arid ecosystems. Thus, the climate parameters that drive alterations in the AI of a region are likely to play an disproportionate role in shaping the response of arid soil communities to a changing climate. In this chapter we consider climate parameters that have been shown to be altered through climate change, with a focus on how these parameters are likely to affect dryland soil communities, including microorganisms and invertebrates. In particular, our goal is to highlight dryland soil community structure and function in the context of climate change, and we will focus on community relationships with increased atmospheric CO2 concentrations (a primary driver of climate change), temperature, and sources of soil moisture.
Retrieving pace in vegetation growth using precipitation and soil moisture
NASA Astrophysics Data System (ADS)
Sohoulande Djebou, D. C.; Singh, V. P.
2013-12-01
The complexity of interactions between the biophysical components of the watershed increases the challenge of understanding water budget. Hence, the perspicacity of the continuum soil-vegetation-atmosphere's functionality still remains crucial for science. This study targeted the Texas Gulf watershed and evaluated the behavior of vegetation covers by coupling precipitation and soil moisture patterns. Growing season's Normalized Differential Vegetation Index NDVI for deciduous forest and grassland were used over a 23 year period as well as precipitation and soil moisture data. The role of time scales on vegetation dynamics analysis was appraised using both entropy rescaling and correlation analysis. This resulted in that soil moisture at 5 cm and 25cm are potentially more efficient to use for vegetation dynamics monitoring at finer time scale compared to precipitation. Albeit soil moisture at 5 cm and 25 cm series are highly correlated (R2>0.64), it appeared that 5 cm soil moisture series can better explain the variability of vegetation growth. A logarithmic transformation of soil moisture and precipitation data increased correlation with NDVI for the different time scales considered. Based on a monthly time scale we came out with a relationship between vegetation index and the couple soil moisture and precipitation [NDVI=a*Log(% soil moisture)+b*Log(Precipitation)+c] with R2>0.25 for each vegetation type. Further, we proposed to assess vegetation green-up using logistic regression model and transinformation entropy using the couple soil moisture and precipitation as independent variables and vegetation growth metrics (NDVI, NDVI ratio, NDVI slope) as the dependent variable. The study is still ongoing and the results will surely contribute to the knowledge in large scale vegetation monitoring. Keywords: Precipitation, soil moisture, vegetation growth, entropy Time scale, Logarithmic transformation and correlation between soil moisture and NDVI, precipitation and NDVI. The analysis is performed by combining both scenes 7 and 8 data. Schematic illustration of the two dimension transinformation entropy approach. T(P,SM;VI) stand for the transinformation contained in the couple soil moisture (SM)/precipitation (P) and explaining vegetation growth (VI).
NASA Astrophysics Data System (ADS)
Sihi, Debjani; Davidson, Eric; Chen, Min; Savage, Kathleen; Richardson, Andrew; Keenan, Trevor; Hollinger, David
2017-04-01
Soils represent the largest terrestrial carbon (C) pool, and microbial decomposition of soil organic matter (SOM) to carbon dioxide, also called heterotrophic respiration (Rh), is an important component of the global C cycle. Temperature sensitivity of Rh is often represented with a simple Q10 function in ecosystem models and earth system models (ESMs), sometimes accompanied by an empirical soil moisture modifier. More explicit representation of the effects of soil moisture, substrate supply, and their interactions with temperature has been proposed to disentangle the confounding factors of apparent temperature sensitivity of SOM decomposition and improve performance of ecosystem models and ESMs. The objective of this work was to incorporate into an ecosystem model a more mechanistic, but still parsimonious, model of environmental factors controlling Rh. The Dual Arrhenius and Michaelis-Menten (DAMM) model simulates Rh using Michaelis-Menten, Arrhenius, and diffusion functions. Soil moisture affects Rh and its apparent temperature sensitivity in DAMM by regulating the diffusion of oxygen and soluble carbon substrates to the enzymatic reaction site. However, in its current configuration, DAMM depends on assumptions or inputs from other models regarding soil C inputs. Here we merged the DAMM soil flux model with a parsimonious ecosystem flux model, FöBAAR (Forest Biomass, Assimilation, Allocation and Respiration) by replacing FöBAAR's algorithms for Rh with those of DAMM. Classical root trenching experiments provided data to partition soil CO2 efflux into Rh (trenched plot) and root respiration (untrenched minus trenched plots). We used three years of high-frequency soil flux data from automated soil chambers (trenched and untrenched plots) and landscape-scale ecosystem fluxes from eddy covariance towers from two mid-latitude forests (Harvard Forest, MA and Howland Forest, ME) of northeastern USA to develop and validate the merged model and to quantify the uncertainties in a multiple constraints approach. The optimized DAMM-FöBAAR model better captured the seasonal dynamics of Rh compared to the FöBAAR-only model for the Harvard Forest, as indicated by lower cost functions (model-data mismatch). However, DAMM-FöBAAR showed less improvement over FöBAAR-only for the boreal transition forest at Howland. The frequency of droughts is lower at Howland, due to a shallow water table, resulting in only brief water limitation affecting Rh in some years. At both sites, the declining trend of soil respiration during drought episodes was captured by the DAMM-FöBAAR model, but not the FöBAAR-only model, which simulates Rh using only a Q10 type function. Greater confidence in model prediction resulting from the inclusion of mechanistic simulation of moisture limitation on substrate availability, an emergent property of DAMM, depends on site conditions, climate, and the temporal scale of interest. While the DAMM functions require a few more parameters than a simple Q10 function, we have demonstrated that they can be included in an ecosystem model and reduce the cost function. Moreover, the mechanistic structure of the soil moisture effects using DAMM functions should be more generalizable than other commonly used empirical functions.
Impacts of Soil-aquifer Heat and Water Fluxes on Simulated Global Climate
NASA Technical Reports Server (NTRS)
Krakauer, N.Y.; Puma, Michael J.; Cook, B. I.
2013-01-01
Climate models have traditionally only represented heat and water fluxes within relatively shallow soil layers, but there is increasing interest in the possible role of heat and water exchanges with the deeper subsurface. Here, we integrate an idealized 50m deep aquifer into the land surface module of the GISS ModelE general circulation model to test the influence of aquifer-soil moisture and heat exchanges on climate variables. We evaluate the impact on the modeled climate of aquifer-soil heat and water fluxes separately, as well as in combination. The addition of the aquifer to ModelE has limited impact on annual-mean climate, with little change in global mean land temperature, precipitation, or evaporation. The seasonal amplitude of deep soil temperature is strongly damped by the soil-aquifer heat flux. This not only improves the model representation of permafrost area but propagates to the surface, resulting in an increase in the seasonal amplitude of surface air temperature of >1K in the Arctic. The soil-aquifer water and heat fluxes both slightly decrease interannual variability in soil moisture and in landsurface temperature, and decrease the soil moisture memory of the land surface on seasonal to annual timescales. The results of this experiment suggest that deepening the modeled land surface, compared to modeling only a shallower soil column with a no-flux bottom boundary condition, has limited impact on mean climate but does affect seasonality and interannual persistence.
Effect of rainfall seasonality on carbon storage in tropical dry ecosystems
NASA Astrophysics Data System (ADS)
Rohr, Tyler; Manzoni, Stefano; Feng, Xue; Menezes, Rômulo S. C.; Porporato, Amilcare
2013-07-01
seasonally dry conditions are typical of large areas of the tropics, their biogeochemical responses to seasonal rainfall and soil carbon (C) sequestration potential are not well characterized. Seasonal moisture availability positively affects both productivity and soil respiration, resulting in a delicate balance between C deposition as litterfall and C loss through heterotrophic respiration. To understand how rainfall seasonality (i.e., duration of the wet season and rainfall distribution) affects this balance and to provide estimates of long-term C sequestration, we develop a minimal model linking the seasonal behavior of the ensemble soil moisture, plant productivity, related C inputs through litterfall, and soil C dynamics. A drought-deciduous caatinga ecosystem in northeastern Brazil is used as a case study to parameterize the model. When extended to different patterns of rainfall seasonality, the results indicate that for fixed annual rainfall, both plant productivity and soil C sequestration potential are largely, and nonlinearly, dependent on wet season duration. Moreover, total annual rainfall is a critical driver of this relationship, leading at times to distinct optima in both production and C storage. These theoretical predictions are discussed in the context of parameter uncertainties and possible changes in rainfall regimes in tropical dry ecosystems.
NASA Astrophysics Data System (ADS)
Vergnes, Jean-Pierre; Decharme, Bertrand; Habets, Florence
2014-05-01
Groundwater is a key component of the global hydrological cycle. It sustains base flow in humid climate while it receives seepage in arid region. Moreover, groundwater influences soil moisture through water capillary rise into the soil and potentially affects the energy and water budget between the land surface and the atmosphere. Despite its importance, most global climate models do not account for groundwater and their possible interaction with both the surface hydrology and the overlying atmosphere. This study assesses the impact of capillary rise from shallow groundwater on the simulated water budget over France. The groundwater scheme implemented in the Total Runoff Integrated Pathways (TRIP) river routing model in a previous study is coupled with the Interaction between Soil Biosphere Atmosphere (ISBA) land surface model. In this coupling, the simulated water table depth acts as the lower boundary condition for the soil moisture diffusivity equation. An original parameterization accounting for the subgrid elevation inside each grid cell is proposed in order to compute this fully-coupled soil lower boundary condition. Simulations are performed at high (1/12°) and low (0.5°) resolutions and evaluated over the 1989-2009 period. Compared to a free-drain experiment, upward capillary fluxes at the bottom of soil increase the mean annual evapotranspiration simulated over the aquifer domain by 3.12 % and 1.54 % at fine and low resolutions respectively. This process logically induces a decrease of the simulated recharge from ISBA to the aquifers and contributes to enhance the soil moisture memory. The simulated water table depths are then lowered, which induces a slight decrease of the simulated mean annual river discharges. However, the fully-coupled simulations compare well with river discharge and water table depth observations which confirms the relevance of the coupling formalism.
Ultrasound Algorithm Derivation for Soil Moisture Content Estimation
NASA Technical Reports Server (NTRS)
Belisle, W.R.; Metzl, R.; Choi, J.; Aggarwal, M. D.; Coleman, T.
1997-01-01
Soil moisture content can be estimated by evaluating the velocity at which sound waves travel through a known volume of solid material. This research involved the development of three soil algorithms relating the moisture content to the velocity at which sound waves moved through dry and moist media. Pressure and shear wave propagation equations were used in conjunction with soil property descriptions to derive algorithms appropriate for describing the effects of moisture content variation on the velocity of sound waves in soils with and without complete soil pore water volumes, An elementary algorithm was used to estimate soil moisture contents ranging from 0.08 g/g to 0.5 g/g from sound wave velocities ranging from 526 m/s to 664 m/s. Secondary algorithms were also used to estimate soil moisture content from sound wave velocities through soils with pores that were filled predominantly with air or water.
Huang, Gang; Zhao, Xue-yong; Huang, Ying-xin; Su, Yan-gui
2009-03-01
Based on the investigation data of vegetation and soil moisture regime of Caragana microphylla shrubs widely distributed in Horqin sandy land, the spatiotemporal variations of soil moisture regime and soil water storage of artificial sand-fixing C. microphylla shrubs at different topographical sites in the sandy land were studied, and the evapotranspiration was measured by water balance method. The results showed that the soil moisture content of the shrubs was the highest in the lowland of dunes, followed by in the middle, and in the crest of the dunes, and increased with increasing depth. No water stress occurred during the growth season of the shrubs. Soil moisture content of the shrubs was highly related to precipitation event, and the relationship of soil moisture content with precipitation was higher in deep soil layer (50-180 cm) than in shallow soil layer (0-50 cm). The variation coefficient of soil moisture content was also higher in deep layer than in shallow layer. Soil water storage was increasing in the whole growth season of the shrubs, which meant that the accumulation of soil water occurred in this area. The evapotranspiriation of the shrubs occupied above 64% of the precipitation.
NASA Technical Reports Server (NTRS)
Bolten, John D.; Lakshmi, Venkat
2009-01-01
The Soil Moisture Experiments conducted in Iowa in the summer of 2002 (SMEX02) had many remote sensing instruments that were used to study the spatial and temporal variability of soil moisture. The sensors used in this paper (a subset of the suite of sensors) are the AQUA satellite-based AMSR-E (Advanced Microwave Scanning Radiometer- Earth Observing System) and the aircraft-based PSR (Polarimetric Scanning Radiometer). The SMEX02 design focused on the collection of near simultaneous brightness temperature observations from each of these instruments and in situ soil moisture measurements at field- and domain- scale. This methodology provided a basis for a quantitative analysis of the soil moisture remote sensing potential of each instrument using in situ comparisons and retrieved soil moisture estimates through the application of a radiative transfer model. To this end, the two sensors are compared with respect to their estimation of soil moisture.
USDA-ARS?s Scientific Manuscript database
Remote sensing of soil moisture has reached a level of maturity and accuracy for which the retrieved products can be used to improve hydrological and meteorological applications. In this study, the soil moisture product from the European Space Agency’s Soil Moisture and Ocean Salinity (SMOS) is used...
USDA-ARS?s Scientific Manuscript database
The validation of the soil moisture retrievals from the recently-launched NASA Soil Moisture Active/Passive (SMAP) satellite is important prior to their full public release. Uncertainty in attempts to characterize footprint-scale surface-layer soil moisture using point-scale ground observations has ...
Soil-moisture constants and their variation
Walter M. Broadfoot; Hubert D. Burke
1958-01-01
"Constants" like field capacity, liquid limit, moisture equivalent, and wilting point are used by most students and workers in soil moisture. These constants may be equilibrium points or other values that describe soil moisture. Their values under specific soil and cover conditions have been discussed at length in the literature, but few general analyses and...
USDA-ARS?s Scientific Manuscript database
Soil moisture is an intrinsic state variable that varies considerably in space and time. Although soil moisture is highly variable, repeated measurements of soil moisture at the field or small watershed scale can often reveal certain locations as being temporally stable and representative of the are...
Soil moisture depletion patterns around scattered trees
Robert R. Ziemer
1968-01-01
Soil moisture was measured around an isolated mature sugar pine tree (Pinus lambertiana Dougl.) in the mixed conifer forest type of the north central Sierra Nevada, California, from November 1965 to October 1966. From a sequence of measurements, horizontal and vertical soil moisture profiles were developed. Estimated soil moisture depletion from the 61-foot radius plot...
USDA-ARS?s Scientific Manuscript database
A very promising technique for spatial disaggregation of soil moisture is on the combination of radiometer and radar observations. Despite their demonstrated potential for long term large scale monitoring of soil moisture, passive and active have their disadvantages in terms of temporal and spatial ...
Calibration and validation of the COSMOS rover for surface soil moisture
USDA-ARS?s Scientific Manuscript database
The mobile COsmic-ray Soil Moisture Observing System (COSMOS) rover may be useful for validating satellite-based estimates of near surface soil moisture, but the accuracy with which the rover can measure 0-5 cm soil moisture has not been previously determined. Our objectives were to calibrate and va...
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.
Simelane, David O
2007-06-01
Laboratory studies were conducted to determine the influence of soil texture, moisture and surface cracks on adult preference and survival of the root-feeding flea beetle, Longitarsus bethae Savini and Escalona (Coleoptera: Chrysomelidae), a natural enemy of the weed, Lantana camara L. (Verbenaceae). Adult feeding, oviposition preference, and survival of the immature stages of L. bethae were examined at four soil textures (clayey, silty loam, sandy loam, and sandy soil), three soil moisture levels (low, moderate, and high), and two soil surface conditions (with or without surface cracks). Both soil texture and moisture had no influence on leaf feeding and colonization by adult L. bethae. Soil texture had a significant influence on oviposition, with adults preferring to lay on clayey and sandy soils to silty or sandy loam soils. However, survival to adulthood was significantly higher in clayey soils than in other soil textures. There was a tendency for females to deposit more eggs at greater depth in both clayey and sandy soils than in other soil textures. Although oviposition preference and depth of oviposition were not influenced by soil moisture, survival in moderately moist soils was significantly higher than in other moisture levels. Development of immature stages in high soil moisture levels was significantly slower than in other soil moisture levels. There were no variations in the body size of beetles that emerged from different soil textures and moisture levels. Females laid almost three times more eggs on cracked than on noncracked soils. It is predicted that clayey and moderately moist soils will favor the survival of L. bethae, and under these conditions, damage to the roots is likely to be high. This information will aid in the selection of suitable release sites where L. bethae would be most likely to become established.
Smith, J.A.; Chiou, C.T.; Kammer, J.A.; Kile, D.E.
1990-01-01
This report presents data on the sorption of trichloroethene (TCE) vapor to vadose-zone soil above a contaminated water-table aquifer at Picatinny Arsenal in Morris County, NJ. To assess the impact of moisture on TCE sorption, batch experiments on the sorption of TCE vapor by the field soil were carried out as a function of relative humidity. The TCE sorption decreases as soil moisture content increases from zero to saturation soil moisture content (the soil moisture content in equilibrium with 100% relative humidity). The moisture content of soil samples collected from the vadose zone was found to be greater than the saturation soil-moisture content, suggesting that adsorption of TCE by the mineral fraction of the vadose-zone soil should be minimal relative to the partition uptake by soil organic matter. Analyses of soil and soil-gas samples collected from the field indicate that the ratio of the concentration of TCE on the vadose-zone soil to its concentration in the soil gas is 1-3 orders of magnitude greater than the ratio predicted by using an assumption of equilibrium conditions. This apparent disequilibrium presumably results from the slow desorption of TCE from the organic matter of the vadose-zone soil relative to the dissipation of TCE vapor from the soil gas.
Assessment of Version 4 of the SMAP Passive Soil Moisture Standard Product
NASA Technical Reports Server (NTRS)
O'neill, P. O.; Chan, S.; Bindlish, R.; Jackson, T.; Colliander, A.; Dunbar, R.; Chen, F.; Piepmeier, Jeffrey R.; Yueh, S.; Entekhabi, D.;
2017-01-01
NASAs Soil Moisture Active Passive (SMAP) mission launched on January 31, 2015 into a sun-synchronous 6 am6 pm orbit with an objective to produce global mapping of high-resolution soil moisture and freeze-thaw state every 2-3 days. The SMAP radiometer began acquiring routine science data on March 31, 2015 and continues to operate nominally. SMAPs radiometer-derived standard soil moisture product (L2SMP) provides soil moisture estimates posted on a 36-km fixed Earth grid using brightness temperature observations and ancillary data. A beta quality version of L2SMP was released to the public in October, 2015, Version 3 validated L2SMP soil moisture data were released in May, 2016, and Version 4 L2SMP data were released in December, 2016. Version 4 data are processed using the same soil moisture retrieval algorithms as previous versions, but now include retrieved soil moisture from both the 6 am descending orbits and the 6 pm ascending orbits. Validation of 19 months of the standard L2SMP product was done for both AM and PM retrievals using in situ measurements from global core calval sites. Accuracy of the soil moisture retrievals averaged over the core sites showed that SMAP accuracy requirements are being met.
The global distribution and dynamics of surface soil moisture
NASA Astrophysics Data System (ADS)
McColl, Kaighin A.; Alemohammad, Seyed Hamed; Akbar, Ruzbeh; Konings, Alexandra G.; Yueh, Simon; Entekhabi, Dara
2017-01-01
Surface soil moisture has a direct impact on food security, human health and ecosystem function. It also plays a key role in the climate system, and the development and persistence of extreme weather events such as droughts, floods and heatwaves. However, sparse and uneven observations have made it difficult to quantify the global distribution and dynamics of surface soil moisture. Here we introduce a metric of soil moisture memory and use a full year of global observations from NASA's Soil Moisture Active Passive mission to show that surface soil moisture--a storage believed to make up less than 0.001% of the global freshwater budget by volume, and equivalent to an, on average, 8-mm thin layer of water covering all land surfaces--plays a significant role in the water cycle. Specifically, we find that surface soil moisture retains a median 14% of precipitation falling on land after three days. Furthermore, the retained fraction of the surface soil moisture storage after three days is highest over arid regions, and in regions where drainage to groundwater storage is lowest. We conclude that lower groundwater storage in these regions is due not only to lower precipitation, but also to the complex partitioning of the water cycle by the surface soil moisture storage layer at the land surface.
Kaplan, D; Muñoz-Carpena, R; Wan, Y; Hedgepeth, M; Zheng, F; Roberts, R; Rossmanith, R
2010-01-01
Floodplain forests provide unique ecological structure and function, which are often degraded or lost when watershed hydrology is modified. Restoration of damaged ecosystems requires an understanding of surface water, groundwater, and vadose (unsaturated) zone hydrology in the floodplain. Soil moisture and porewater salinity are of particular importance for seed germination and seedling survival in systems affected by saltwater intrusion but are difficult to monitor and often overlooked. This study contributes to the understanding of floodplain hydrology in one of the last bald cypress [Taxodium distichum (L.) Rich.] floodplain swamps in southeast Florida. We investigated soil moisture and porewater salinity dynamics in the floodplain of the Loxahatchee River, where reduced freshwater flow has led to saltwater intrusion and a transition to salt-tolerant, mangrove-dominated communities. Twenty-four dielectric probes measuring soil moisture and porewater salinity every 30 min were installed along two transects-one in an upstream, freshwater location and one in a downstream tidal area. Complemented by surface water, groundwater, and meteorological data, these unique 4-yr datasets quantified the spatial variability and temporal dynamics of vadose zone hydrology. Results showed that soil moisture can be closely predicted based on river stage and topographic elevation (overall Nash-Sutcliffe coefficient of efficiency = 0.83). Porewater salinity rarely exceeded tolerance thresholds (0.3125 S m(-1)) for bald cypress upstream but did so in some downstream areas. This provided an explanation for observed vegetation changes that both surface water and groundwater salinity failed to explain. The results offer a methodological and analytical framework for floodplain monitoring in locations where restoration success depends on vadose zone hydrology and provide relationships for evaluating proposed restoration and management scenarios for the Loxahatchee River.
NASA Astrophysics Data System (ADS)
Sanchez-Mejia, Zulia Mayari; Papuga, Shirley A.
2014-01-01
We present an observational analysis examining soil moisture control on surface energy dynamics and planetary boundary layer characteristics. Understanding soil moisture control on land-atmosphere interactions will become increasingly important as climate change continues to alter water availability. In this study, we analyzed 4 years of data from the Santa Rita Creosote Ameriflux site. We categorized our data independently in two ways: (1) wet or dry seasons and (2) one of the four cases within a two-layer soil moisture framework for the root zone based on the presence or absence of moisture in shallow (0-20 cm) and deep (20-60 cm) soil layers. Using these categorizations, we quantified the soil moisture control on surface energy dynamics and planetary boundary layer characteristics using both average responses and linear regression. Our results highlight the importance of deep soil moisture in land-atmosphere interactions. The presence of deep soil moisture decreased albedo by about 10%, and significant differences were observed in evaporative fraction even in the absence of shallow moisture. The planetary boundary layer height (PBLh) was largest when the whole soil profile was dry, decreasing by about 1 km when the whole profile was wet. Even when shallow moisture was absent but deep moisture was present the PBLh was significantly lower than when the entire profile was dry. The importance of deep moisture is likely site-specific and modulated through vegetation. Therefore, understanding these relationships also provides important insights into feedbacks between vegetation and the hydrologic cycle and their consequent influence on the climate system.
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.
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.
Where did my wifi go? Measuring soil moisture using wifi signal strength
NASA Astrophysics Data System (ADS)
Hut, Rolf; de Jeu, Richard
2015-04-01
Soil moisture is tricky to measure. Currently soil moisture is measured at small footprints using probes and other field devices, or at large footprints using satellites. Promising developments in measuring soil moisture are using fiber optic cables for measurements along a line, or using cosmos rays for field scale measurements. In this demonstration we present a low cost alternative to measure soil moisture at footprints of a few square meters. We use a wifi hotspot and a wifi dongle, both mounted in a cantenna for beam forming. We aim the hotspot on a piece of soil and put the dongle in the path of the reflection. By logging the signal strength of the wifi netwerk, we have a proxy for soil moisture. A first proof of concept is presented.
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.