Bibliographies thématiques / Spatial variability of soils

Littérature scientifique sur le sujet « Spatial variability of soils »

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Publié le 20 juillet 2024

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Articles de revues sur le sujet "Spatial variability of soils"

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Rahman, S., L. C. Munn, R. Zhang et G. F. Vance. « Rocky Mountain forest soils : Evaluating spatial variability using conventional statistics and geostatistics ». Canadian Journal of Soil Science 76, no 4 (1 novembre 1996) : 501–7. http://dx.doi.org/10.4141/cjss96-062.

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Spatial variability of soils is a landscape attribute which soil scientists must identify and understand if they are to construct useful soils maps. This paper describes the spatial variability of soils in a forested watershed in the Medicine Bow Mountains, Wyoming, using both conventional statistics and geostatistics. Principle Components Analysis indicated that flow accumulation and aspect were the two terrain attributes that most economically described terrain variability. Thickness of A and B horizons, organic carbon and solum coarse fragments were variable in the study area (CVs of 40 to 58%). Simple correlation and regression analyses suggested there were no statistically significant relationships between soil properties (texture, pH, coarse fragments, organic carbon content) and terrain attributes (elevation, slope gradient, slope shape, flow accumulation, aspect). Geostatistical analysis indicated thickness and coarse fragment contents of the A and B horizons, and solum thickness were spatially independent variables; however, pH, organic carbon content, and solum coarse fragment content were spatially correlated. Spatial variability was described by both linear (pH and organic carbon content) and spherical (solum coarse fragment) models. Use of geostatistics provided insight into the nature of variability in soil properties across the landscape of the Libby Creek watershed when conventional statistics (analysis of variance and regression analysis) did not. Key words: Rocky Mountains, Medicine Bow Mountains, forest soils, spatial variability, principle component analysis, geostatistics
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Prasanna, Shwetha. « Analysis of Hydraulic Properties of Indian Forest Soil ». Journal of Civil Engineering and Construction 7, no 1 (24 février 2018) : 12. http://dx.doi.org/10.32732/jcec.2018.7.1.12.

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Soils are a product of the factors of formation and continuously change over the earth’s surface. The analysis of the spatial variability of soil properties is important for land management and construction of an ecological environment. Soils are characterized by high degree of spatial variability due to the combined effect of physical, chemical or biological processes that operate with different intensities and at different scales. The spatial variability of soil hydraulic properties helps us to find the subsurface flux of water. The most frequently used hydraulic properties are soil water retention curve and saturated hydraulic conductivity. Both these hydraulic properties exhibit a high degree of spatial and temporal variability. The primary objective of this study was to analyze the spatial variability of hydraulic properties of forest soils of Pavanje river basin. Correlation analysis technique has been used to analyze various soil properties. Spatial variability of the forested hillslope soils at different depths varied considerably among the soil hydraulic properties. The spatial variability of water retention at all the different pressure head is low at the top layers, and increases towards the bottom layers. The saturated hydraulic conductivity is almost same in the top layers, but more in the bottom layers of forest soil.
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Orfánus, T., Z. Bedrna, Ľ. Lichner, D. Hallett P, K. Kňava et M. Sebíň. « Spatial variability of water repellency in pine forest soil ». Soil and Water Research 3, Special Issue No. 1 (30 juin 2008) : S123—S129. http://dx.doi.org/10.17221/11/2008-swr.

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The variability of water repellency of pine-forest arenic regosols and its influence on infiltration processes were measured in southwest Slovakia. The water drop penetration time (WDPT) tests of soil water repellency and infiltration tests with a miniature tension infiltrometer (3 mm diameter) were performed. Large differences in infiltration were observed over centimetre spatial resolution, with WDPT tests suggesting water repellency varying from extreme to moderate levels. For soils with severe to extreme water repellency determined with WDPT, steady state infiltration was not reached in tests with the miniature tension infiltrometer, making it impossible to estimate sorptivity. Where sorptivity could be measured, the correlation with WDPT was poor. All results suggest that hydraulic properties of soil change below the centimetre scale resolution of the current study, probably due to a presence of unevenly distributed hydrophobic material.
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Hadi, Teeba Abdel Karim Abdel, Amal Radhi Jubeir et Mohammed A. Hussain. « Spatial Variability of Some Soil Microorganisms ». IOP Conference Series : Earth and Environmental Science 1158, no 2 (1 avril 2023) : 022023. http://dx.doi.org/10.1088/1755-1315/1158/2/022023.

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Abstract The study area was chosen in the field of the College of Agriculture of Al-Qasim Green University, confined between longitudes 22.6° 22° 044° to 00.9° 24° 0.44° east and between latitudes 19.3° 21° 32° to 21.7° 24° 32° N, and the study area was interlocked and identified The coordinates were obtained by GPS, as samples were obtained from 40 sites of cultivated soils. For two surface depths 0-30 cm and sub-surface 30-60 cm and 40 sites for leftover soils of two depths as well, The volumetric analysis results showed that the variability of the microorganisms in the soil was that the Azotobacter bacteria were the most heterogeneous compared to the Bacillus bacteria, and that the content of Azotobacter was higher in the soil than the Bacillus bacteria, and the agricultural use had an effect on the presence of these microorganisms and their heterogeneity.
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Phontusang, Porntip, Roengsak Katawatin, Krirk Pannangpetch, Sununtha Kingpaiboon et Rattana Lerdsuwansri. « Spatial Variability of Sodium Adsorption Ratio and Sodicity in Salt-Affected Soils of Northeast Thailand ». Advanced Materials Research 931-932 (mai 2014) : 709–15. http://dx.doi.org/10.4028/www.scientific.net/amr.931-932.709.

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Information on spatial variability of Sodium Adsorption Ratio (SAR) is useful for implementation of appropriate control measures for the salt-affected soils. The major objective of this study was to use geostatistics to describe the spatial variability of (i) the SAR and consequently (ii) the soil sodicity, in areas of different classes of salt-affected soils. Attention was on areas of very severely salt-affected soils (class 1), severely salt-affected soils (class 2), and moderately salt-affected soils (class 3). For each class, 2 study sites were chosen, totally 6 sites were taken into consideration. In each site, 100 soil samples were collected at 0-30 cm depth according to the stratified systematic unaligned sampling method in the dry season of 2012, and analyzed for the SAR in the laboratory. Descriptive statistics and Geostatistics were applied to describe the variability and spatial variability of SAR and soil sodicity, respectively. The result revealed very high variability of SAR. Descriptive statistics showed the CV values of ≥ 35% for every site of every class. When using semivariogram to describe the spatial correlation of SAR, it was found that in 3 study sites, the semivariogram models fitted well with the corresponding semivariogram samples indicating spatial correlation of SAR in the areas. In these cases, the Ordinary Kriging was applied to generate soil sodicity map. The relatively short range values especially for class 1 indicated very high variation of SAR. However, for the other 3 study sites, the linear models were fitted indicating no spatial correlation. Consequently, Trend Surface Analysis was applied instead. According to the soil sodicity maps generated in this study, the areas of class 1 were entirely occupied by strongly sodic soils. For classes 2 and 3, the soils in all study sites belonging to these classes included normal and slightly sodic soils of different proportions. Furthermore, inconsistency of the spatial variability patterns of SAR was found even in areas within the same class of salt-affected soils. As a result, prior to the intensive management of this problem soil in a particular area, investigation on the spatial variability pattern should be performed
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SAMRA, J. S., K. N. S. SHARMA et N. K. TYAGI. « ANALYSIS OF SPATIAL VARIABILITY IN SODIC SOILS ». Soil Science 145, no 3 (mars 1988) : 180–87. http://dx.doi.org/10.1097/00010694-198803000-00004.

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SAMRA, J. S., V. P. SINGH et K. N. S. SHARMA. « ANALYSIS OF SPATIAL VARIABILITY IN SODIC SOILS ». Soil Science 145, no 4 (avril 1988) : 250–56. http://dx.doi.org/10.1097/00010694-198804000-00003.

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Iqbal, Javed, John A. Thomasson, Johnie N. Jenkins, Phillip R. Owens et Frank D. Whisler. « Spatial Variability Analysis of Soil Physical Properties of Alluvial Soils ». Soil Science Society of America Journal 69, no 4 (juillet 2005) : 1338–50. http://dx.doi.org/10.2136/sssaj2004.0154.

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Hani, Abbas, Narges Sinaei et Ali Gholami. « Spatial Variability of Heavy Metals in the Soils of Ahwaz Using Geostatistical Methods ». International Journal of Environmental Science and Development 5, no 3 (2014) : 294–98. http://dx.doi.org/10.7763/ijesd.2014.v5.495.

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Guérin, Julie, Léon-Étienne Parent et Bing Si. « Spatial and seasonal variability of phosphorus risk indexes in cultivated organic soils ». Canadian Journal of Soil Science 91, no 2 (mai 2011) : 291–302. http://dx.doi.org/10.4141/cjss10089.

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Guérin, J. É., Parent, L.-É. and Si, B. C. 2011. Spatial and seasonal variability of phosphorus risk indexes in cultivated organic soils. Can. J. Soil Sci. 91: 291–302. Many reports have attributed phosphorus (P) leaching from cultivated organic soils and the eutrophication of adjacent surface waters to P fertilization exceeding the P sorption capacity of the soil. The index of phosphorus saturation (IPS) using the Mehlich III method (M-III) has been proposed to define an agri-environmental threshold of P saturation in cultivated organic soils. The spatial and temporal variability of IPSM-III must be documented and related to the risk of P pollution to recommend more efficient fertilization practices. The objective of this research was to measure spatial and seasonal variation patterns of P in cultivated organic soils and to evaluate the losses of soil test extractable P between autumn and the following spring. Composite soil samples were taken on a 25-× 25-m grid within 7-ha areas in three representative types of cultivated organic soils of southwestern Quebec in fall 2006 and spring 2007. Soil P, iron, and aluminum were extracted in duplicate using the M-III and the acid ammonium oxalate methods (OX). The spatial analysis of organic soils showed that the PM-III and the IPSM-III were spatially autocorrelated and that the experimental semivariograms can be described by linear to sill or spherical models with ranges of 68 to 168 m. There was a high seasonal variability among the PM-III and the IPSM-III values. The IPSM-III values were generally higher than the environmental threshold of 0.05 across sites and sampling periods. Losses of M-III and OX extractable P averaged 41 kg PM-III ha−1 and 84 kg POX ha−1, respectively, between fall and the following spring, suggesting substantial contribution of cultivated organic soils to the pollution of downstream surface waters.
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Thèses sur le sujet "Spatial variability of soils"

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Young, Fred J. « Spatial variability of soil properties within a loess-covered, upland landscape / ». free to MU campus, to others for purchase, 1996. http://wwwlib.umi.com/cr/mo/fullcit?p9823319.

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Kim, Hyunki. « Spatial variability in soils stiffness and strength / ». Diss., Available online, Georgia Institute of Technology, 2005, 2005. http://etd.gatech.edu/theses/available/etd-07132005-194445/.

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Thesis (Ph. D.)--Civil and Environmental Engineering, Georgia Institute of Technology, 2006.
Mayne, Paul, Committee Member ; Frost, David, Committee Member ; Santamarina, Carlos, Committee Chair ; Rix, Glenn, Committee Member ; Ruppel, Carolyn, Committee Member.
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Hendrayanto. « Analyses on Spatial Variability in Hydraulic Properties of Forest Soils ». Kyoto University, 1999. http://hdl.handle.net/2433/181882.

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Kyoto University (京都大学)
0048
新制・課程博士
博士(農学)
甲第7873号
農博第1031号
新制||農||775(附属図書館)
学位論文||H11||N3236(農学部図書室)
UT51-99-G467
京都大学大学院農学研究科森林科学専攻
(主査)教授 水山 高久, 教授 三野 徹, 教授 吉田 博宣
学位規則第4条第1項該当
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El-Haris, Mamdouh Khamis. « Soil spatial variability : Areal interpolations of physical and chemical parameters ». Diss., The University of Arizona, 1987. http://hdl.handle.net/10150/184290.

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Four fields of 117 ha area located at the University of Arizona's Maricopa Agricultural Center were selected for this study. Two soil series, the Casa Grande sandy clay loam and Trix clay loam occur. Surface samples (0-25 cm) were collected on a 98 m interval and 3 rows providing 47 sites per field. Sites were classified either as surveying (32) or testing (15) in each of the four fields. Additional samples at 25-50, 50-75, 75-100, and 100-125 cm were obtained with duplicate surface undisturbed cores at 5 sites per field. Soil parameters include bulk density, saturated hydraulic conductivity, moisture retention, particle size analysis, pH, EC, soluble cations, SAR, and ESP. A quantification of the spatial interdependence of samples was developed based on the variogram of soil parameters. A linear model was best fitted to the clay, EC, Ca²⁺, Mg²⁺, Na⁺, SAR and ESP, and a spherical model to the sand, silt, pH, and K⁺ observed variograms. A comparison of variograms obtained conventionally and with the robust estimation of Cressie and Hawkins (1980) for sand and Ca²⁺ were performed with a fixed couples number per class and with a fixed class size. Additionally, a negative log-likelihood function along with cross-validation criteria were used with the jackknifing method to validate and determine variogram parameters. Three interpolation techniques have been compared for estimating 11 soil properties at the test sites. The techniques include Arithmetic Mean, Inversely Weighted Average, and Kriging with various numbers of neighbor estimates. Using 4 point estimates resulted in nearly identical results, but the 8 point estimates gave more contrast for results among the alternative techniques. Jackknifing was used with 4, 8, 15, 25 neighbors for estimating 188 points of sand and Ca²⁺ with the three techniques. Sand showed a definite advantage of Kriging by lowering the Mean Square Error with increasing neighbor number. The simple interpolator Arithmetic Mean was comparable and sometimes even better than the other techniques. Kriging, the most complex technique, was not the absolute best interpolator over all situations as perhaps expected. The spatial dependence for the 11 soil variables was studied by preparing contour maps by punctual Kriging. Sand and Ca²⁺ were also mapped by block Kriging estimates.
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Okae-Anti, Daniel Theophilus Akwa. « Spatial variability studies in relation to pedogenic processes in alluvial soils ». Thesis, University of Reading, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.239027.

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Saez, Carolin Cordova. « Spatial variability of soil organic matter fractions in arable and grassland soils - implications for soil N supply ». Thesis, University of Reading, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.542058.

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Huang, Xuewen. « Analysis of effects of soil properties, topographical variables and management practices on spatial-temporal variability of crop yields ». Diss., Connect to online resource - MSU authorized users, 2008.

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Parker, Ronald Dean 1948. « The effect of spatial variability on output from the water erosion prediction project soil erosion computer model ». Diss., The University of Arizona, 1991. http://hdl.handle.net/10150/191165.

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Spatial variability is all that stands between hydrology and science, forcing us to deal in probabilities and averages. Because of scale, we can not consider forces on individual soil particles, water molecules and solute ions when addressing human size problems. We must therefore look at aggregate properties and mean values for parameters and inputs in computer modeling of hydrologic phenomena. This research explores the impact of spatially variable inputs on the Water Erosion Prediction Project soil erosion computer program. Distributions of input variables are generated and assigned randomly to a grid of homogeneous rangeland hillslope elements. Values for runoff volume and sediment loss from each flow path are recorded and averaged to provide a distribution of outputs in the form of a sensitivity analysis. Variabilities of slope, slope length, soil textures, soil characteristics, terrain, convex and concave slopes, soil saturation, rainfall amount and vegetation were examined. Results show that use of mean inputs values in the WEPP representative hillslope model yields very similar outputs to the spatially variable research model using a distribution of inputs in all simulations in the case of totally random bare rangeland soils. When a decreasing trend in soil clay content is introduced in the variable model, the hillslope model using average values as inputs no longer provides a good estimate of the sediment loss. When random vegetation is generated and added to the simulation, runoff volume continues to be similar between the two models, but the sediment loss is much higher in the spatially variable model. In addition, the results of the standard hillslope model are much less responsive to changes in slope than those of the spatially variable model. It is concluded that spatial variability of soils must be considered when there is a linear change in input values with slope position. Likewise spatial variability of vegetation needs to be addressed in order to accurately estimate erosion on the rangeland watersheds considered in this dissertation. It is also found that this type of simulation provides a model for sensitivity analysis of a complex computer programs. Physically related inputs can be generated in such a way as to preserve the desired interrationships and distributions of inputs can be directly compared to generated distributions of outputs.
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Schöning, Ingo. « Organic matter stocks in temperate forest soils composition, radiocarbon age and spatial variability / ». [S.l.] : [s.n.], 2005. http://deposit.ddb.de/cgi-bin/dokserv?idn=978952839.

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Suliman, Ahmed Saeid Ahmed. « Spectral and spatial variability of the soils on the Maricopa Agricultural Center, Arizona ». Diss., The University of Arizona, 1989. http://hdl.handle.net/10150/184678.

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Dry and wet fine earth spectral measurements were made on the Ap soil surface horizons on the Maricopa Agricultural Center by using a Barnes Modular Multiband Radiometer. Three subsets were used in the analyses 552, 101 and 11. There were three soil series, Casa Grande, Shontik and Trix, four soil mapping units, and three texture classes identified on the farm. The wet soil condition reduced the amplitude of the spectral curves over the entire spectrum range (0.45 to 2.35 μm). The spectral curves were statistically related to the soil mapping units to determine if the soil mapping units and texture classes could be separated. The wet soil condition and the smaller sample size increased the correct classification percentages for soil mapping units and texture classes. LSD tests showed there were significant differences between these groups. Simple- and Multiple-linear regression analysis were used to relate some soil physical (sand, silt and clay contents and color components) and chemical (iron oxide, organic carbon and calcium carbonate contents) to soil spectral responses in the seven bands under dry and wet conditions. There were high correlations levels among the spectral bands showing an overlap of spectral information. Generally, the red (MMR3) and near-infrared (MMR4) bands had the highest correlations with the studied soil properties under dry and wet conditions. Usually, the wet soil condition resulted in higher correlations than that for the dry soil condition over the total spectrum range. The predictive equations for sand, silt and clay and iron oxide contents were satisfactory. For organic carbon and color components, the greatest success was achieved when variation in spectral response within individual samples are smaller than that between soil mapping unit group averages. There was a poor relation between calcium carbonate and spectral response. A comparison of multi-level remotely sensed data collected by SPOT, aircraft, and ground instruments showed a strong agreement among the data sets, which correlated well to fine earth data, except for the SPOT data. Rough soil surfaces showed a reduction in reflectance altitude compared to laser level, and it appears to be directly proportional to the percent shadow in the viewing area measured by SPOT satellite and aircraft.
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Livres sur le sujet "Spatial variability of soils"

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Maji, A. K. Acid soils of India : Their extent and spatial variability. Nagpur : National Bureau of Soil Survey and Land Use Planning, Indian Council of Agricultural Research, 2012.

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Bowers, Fred Howard. Effects of windthrow on soil properties and spatial variability in southeast Alaska. [Alaska] : United States Dept. of Agriculture, Forest Service, Alaska Region, 1987.

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L, Baehr Arthur, et Geological Survey (U.S.), dir. Estimating spatial variability of recharge in southern New Jersey from unsaturated-zone measurements. West Trenton, N.J : U.S. Dept. of the Interior, U.S. Geological Survey, 2003.

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DeLiberty, Tracy L. Spatial and temporal variability of soil moisture in Oklahoma. Elmer, N.J : C.W. Thornthwaite Associates, Laboratory of Climatology, 1994.

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Sukop, Michael. Retention of pesticides by alluvial soils in western Washington : Experimental variables, relation to soil properties, and spatial variability. Pullman, Wash : State of Washington Water Research Center, Washington State University and the University of Washington, 1989.

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Hansen, S. Spatial variability of soil physical properties : Theoretical and experimental analyses : II. Soil water variables--data acquisition, processing and basic statistics. Copenhagen : Dept. of Soil and Water and Plant Nutrition, Royal Veterinary and Agricultural University, 1988.

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Knox, Nichola Maria. Observing temporal and spatial variability of forage quality. Enschede : ITC, 2010.

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Mausbach, M. J., et L. P. Wilding, dir. Spatial Variabilities of Soils and Landforms. Madison, WI, USA : Soil Science Society of America, 1991. http://dx.doi.org/10.2136/sssaspecpub28.

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Åhas, Rein. Spatial and temporal variability of phenological phases in Estonia. Tartu : Tartu University Press, 1999.

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Robeson, Scott M. Spatial interpolation, network bias, and terrestrial air temperature variability. Elmer, N.J : C.W. Thornthwaite Associates, Laboratory of Climatology, 1993.

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Chapitres de livres sur le sujet "Spatial variability of soils"

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Zhang, Jie, Te Xiao, Jian Ji, Peng Zeng et Zijun Cao. « Spatial Variability of Soils ». Dans Geotechnical Reliability Analysis, 173–226. Singapore : Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-6254-7_5.

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Rate, Andrew W. « Spatial Variability and Data Analysis in Urban Soils ». Dans Urban Soils, 53–88. Cham : Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-87316-5_3.

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Wilding, L. P., et L. R. Drees. « Spatial Variability : A Pedologist's Viewpoint1 ». Dans Diversity of Soils in the Tropics, 1–12. Madison, WI, USA : American Society of Agronomy and Soil Science Society of America, 2015. http://dx.doi.org/10.2134/asaspecpub34.c1.

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Czajka, Michał, Stanisław Podsiadłowski, Alfred Stach et Ryszard Walkowiak. « Spatial Variability of Light Morainic Soils ». Dans Land Degradation and Desertification : Assessment, Mitigation and Remediation, 517–28. Dordrecht : Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-8657-0_38.

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Görres, Josef H. « Soil : Spatial Variability ». Dans Landscape and Land Capacity, 283–95. Second edition. | Boca Raton : CRC Press, [2020] | Revised edition of : Encyclopedia of natural resources. [2014]. : CRC Press, 2020. http://dx.doi.org/10.1201/9780429445552-37.

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Bresler, Eshel. « Soil Spatial Variability ». Dans Agronomy Monographs, 145–80. Madison, WI, USA : American Society of Agronomy, Crop Science Society of America, Soil Science Society of America, 2015. http://dx.doi.org/10.2134/agronmonogr31.c8.

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Yost, R. S., X. Wang, R. E. Green, C. Sangchyoswat et C. S. Smith. « Incorporating spatial variability into existing soils databases ». Dans Assessment of Non‐Point Source Pollution in the Vadose Zone, 107–17. Washington, D. C. : American Geophysical Union, 1999. http://dx.doi.org/10.1029/gm108p0107.

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Nielsen, D. R., P. J. Wierenga et J. W. Biggar. « Spatial Soil Variability and Mass Transfers from Agricultural Soils ». Dans SSSA Special Publications, 65–78. Madison, WI, USA : Soil Science Society of America and American Society of Agronomy, 2015. http://dx.doi.org/10.2136/sssaspecpub11.c5.

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Bolle, A. « How to Manage the Spatial Variability of Natural Soils ». Dans Probabilities and Materials, 505–16. Dordrecht : Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-1142-3_41.

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Uehara, G., et R. S. Yost. « Spatial and Temporal Agroecosystem Variability ». Dans Future Developments in Soil Science Research, 43–57. Madison, WI, USA : Soil Science Society of America, 2015. http://dx.doi.org/10.2136/1987.futuredevelopmentssoil.c6.

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Actes de conférences sur le sujet "Spatial variability of soils"

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Hendrickx, Jan M. H., Brian Borchers, J. Woolslayer, Louis W. Dekker, Coen Ritsema et S. Paton. « Spatial variability of dielectric properties in field soils ». Dans Aerospace/Defense Sensing, Simulation, and Controls, sous la direction de Abinash C. Dubey, James F. Harvey, J. Thomas Broach et Vivian George. SPIE, 2001. http://dx.doi.org/10.1117/12.445491.

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Mason, George L., et Christopher Cummins. « Spatial variability of soils in support of countermine operations ». Dans Defense and Security, sous la direction de Russell S. Harmon, J. Thomas Broach et John H. Holloway, Jr. SPIE, 2005. http://dx.doi.org/10.1117/12.604349.

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Liu, Yong, Yanan Ding, Guan Chen et Jiang Tao Yi. « Quantitative Risk Assessment on Landslides Considering Spatial Variability of Soils ». Dans Proceedings of the 29th European Safety and Reliability Conference (ESREL). Singapore : Research Publishing Services, 2019. http://dx.doi.org/10.3850/978-981-11-2724-3_1065-cd.

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Lu, Guanghui, Qingdong Shi, Xiaoling Pan, Weiqing Li, Xiwu Zhan et Shunli Chang. « Spatial variability of soils in vegetation zone of Fukang oasis ». Dans Optical Science and Technology, SPIE's 48th Annual Meeting. SPIE, 2004. http://dx.doi.org/10.1117/12.511846.

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Kravtsova, N. E. « SPATIAL VARIABILITY OF INDICATORS OF THE PHOSPHORUS STATE OF CHERNOZEMS OF THE LOWER DON UNDER ». Dans STATE AND DEVELOPMENT PROSPECTS OF AGRIBUSINESS. DSTU-PRINT, 2020. http://dx.doi.org/10.23947/interagro.2020.1.172-174.

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The development of measures aimed at the rational use of the phosphate Fund of soils is relevant, especially in the ecological and agrochemical aspect. Studies of spatial variability of indicators of the phosphoric state of ordinary chernozems of the Lower don are carried out. A data Bank of indicators of the phosphorus regime of the studied soils was formed. It was found that high variability in the composition of mineral phosphates is more typical for arable horizons. Down the profile, the variability decreases. The lowest level of natural variability is observed in the AB horizon of the studied soils.
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Luo, Zhe, Biao Hu et Youwen Wang. « Excavation-Induced Structural Responses Due to Inherent Spatial Variability of Soils ». Dans Eighth International Conference on Case Histories in Geotechnical Engineering. Reston, VA : American Society of Civil Engineers, 2019. http://dx.doi.org/10.1061/9780784482155.018.

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Campello, Izabela Couto, Maria Das Graças Gardoni, Karla Cristina Araujo Pimentel et Andre Assis. « Characterization of Vertical Spatial Variability of Soils Using CPTu Data Exploration ». Dans International Symposium for Geotechnical Safety & Risk. Singapore : Research Publishing Services, 2022. http://dx.doi.org/10.3850/978-981-18-5182-7_00-03-010.xml.

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Govindaraju, R. S., et K. V. Nedunuri. « Geostatistical Analysis of TPH Degradation in Field Soils ». Dans ASME 1998 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1998. http://dx.doi.org/10.1115/imece1998-0988.

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Abstract Evaluation of remediation strategies in the field is difficult because of the inherent spatial heterogeneity in the hydraulic and chemical properties of the soil. In this study, total petroleum hydrocarbon (TPH) degradation was monitored over a field site with three vegetative treatment plots, and one control plot undergoing natural attenuation. First-order kinetics were assumed applicable at the local scale. The degradation rates and the initial contaminant concentrations were treated as spatially correlated random fields. Our results indicate the importance of spatial variability for an accurate assessment of phytoremediation in the field.
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Shen, Guangrong, Jingjing Xu, Zhenhua Qian et Apostolos Sarris. « Spatial variability of trace elements in agricultural soils of Chongming, Shanghai(China) ». Dans 2009 17th International Conference on Geoinformatics. IEEE, 2009. http://dx.doi.org/10.1109/geoinformatics.2009.5293441.

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Liu, Yong, Ruohan Wang, Manyu Wang et Elton J. Chen. « Seepage Evaluation in Tunnel Construction Considering the Spatial Variability of Surrounding Soils ». Dans Proceedings of the 29th European Safety and Reliability Conference (ESREL). Singapore : Research Publishing Services, 2019. http://dx.doi.org/10.3850/978-981-11-2724-3_1062-cd.

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Rapports d'organisations sur le sujet "Spatial variability of soils"

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Zhang, Renduo, et David Russo. Scale-dependency and spatial variability of soil hydraulic properties. United States Department of Agriculture, novembre 2004. http://dx.doi.org/10.32747/2004.7587220.bard.

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Water resources assessment and protection requires quantitative descriptions of field-scale water flow and contaminant transport through the subsurface, which, in turn, require reliable information about soil hydraulic properties. However, much is still unknown concerning hydraulic properties and flow behavior in heterogeneous soils. Especially, relationships of hydraulic properties changing with measured scales are poorly understood. Soil hydraulic properties are usually measured at a small scale and used for quantifying flow and transport in large scales, which causes misleading results. Therefore, determination of scale-dependent and spatial variability of soil hydraulic properties provides the essential information for quantifying water flow and chemical transport through the subsurface, which are the key processes for detection of potential agricultural/industrial contaminants, reduction of agricultural chemical movement, improvement of soil and water quality, and increase of agricultural productivity. The original research objectives of this project were: 1. to measure soil hydraulic properties at different locations and different scales at large fields; 2. to develop scale-dependent relationships of soil hydraulic properties; and 3. to determine spatial variability and heterogeneity of soil hydraulic properties as a function of measurement scales. The US investigators conducted field and lab experiments to measure soil hydraulic properties at different locations and different scales. Based on the field and lab experiments, a well-structured database of soil physical and hydraulic properties was developed. The database was used to study scale-dependency, spatial variability, and heterogeneity of soil hydraulic properties. An improved method was developed for calculating hydraulic properties based on infiltration data from the disc infiltrometer. Compared with the other methods, the proposed method provided more accurate and stable estimations of the hydraulic conductivity and macroscopic capillary length, using infiltration data collected atshort experiment periods. We also developed scale-dependent relationships of soil hydraulic properties using the fractal and geostatistical characterization. The research effort of the Israeli research team concentrates on tasks along the second objective. The main accomplishment of this effort is that we succeed to derive first-order, upscaled (block effective) conductivity tensor, K'ᵢⱼ, and time-dependent dispersion tensor, D'ᵢⱼ, i,j=1,2,3, for steady-state flow in three-dimensional, partially saturated, heterogeneous formations, for length-scales comparable with those of the formation heterogeneity. Numerical simulations designed to test the applicability of the upscaling methodology to more general situations involving complex, transient flow regimes originating from periodic rain/irrigation events and water uptake by plant roots suggested that even in this complicated case, the upscaling methodology essentially compensated for the loss of sub-grid-scale variations of the velocity field caused by coarse discretization of the flow domain. These results have significant implications with respect to the development of field-scale solute transport models capable of simulating complex real-world scenarios in the subsurface, and, in turn, are essential for the assessment of the threat posed by contamination from agricultural and/or industrial sources.
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Workman, Austin, et Jay Clausen. Meteorological property and temporal variable effect on spatial semivariance of infrared thermography of soil surfaces for detection of foreign objects. Engineer Research and Development Center (U.S.), juin 2021. http://dx.doi.org/10.21079/11681/41024.

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The environmental phenomenological properties responsible for the thermal variability evident in the use of thermal infrared (IR) sensor systems is not well understood. The research objective of this work is to understand the environmental and climatological properties contributing to the temporal and spatial thermal variance of soils. We recorded thermal images of surface temperature of soil as well as several meteorological properties such as weather condition and solar irradiance of loamy soil located at the Cold Regions Research and Engineering Lab (CRREL) facility. We assessed sensor performance by analyzing how recorded meteorological properties affected the spatial structure by observing statistical differences in spatial autocorrelation and dependence parameter estimates.
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Jury, William A., et David Russo. Characterization of Field-Scale Solute Transport in Spatially Variable Unsaturated Field Soils. United States Department of Agriculture, janvier 1994. http://dx.doi.org/10.32747/1994.7568772.bard.

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This report describes activity conducted in several lines of research associated with field-scale water and solute processes. A major effort was put forth developing a stochastic continuum analysis for an important class of problems involving flow of reactive and non reactive chemicals under steady unsaturated flow. The field-scale velocity covariance tensor has been derived from local soil properties and their variability, producing a large-scale description of the medium that embodies all of the local variability in a statistical sense. Special cases of anisotropic medium properties not aligned along the flow direction of spatially variable solute sorption were analysed in detail, revealing a dependence of solute spreading on subtle features of the variability of the medium, such as cross-correlations between sorption and conductivity. A novel method was developed and tested for measuring hydraulic conductivity at the scale of observation through the interpretation of a solute transport outflow curve as a stochastic-convective process. This undertaking provided a host of new K(q) relationships for existing solute experiments and also laid the foundation for future work developing a self-consistent description of flow and transport under these conditions. Numerical codes were developed for calculating K(q) functions for a variety of solute pulse outflow shapes, including lognormal, Fickian, Mobile-Immobile water, and bimodal. Testing of this new approach against conventional methodology was mixed, and agreed most closely when the assumptions of the new method were met. We conclude that this procedure offers a valuable alternative to conventional methods of measuring K(q), particularly when the application of the method is at a scale (e.g. and agricultural field) that is large compared to the common scale at which conventional K(q) devices operate. The same problem was approached from a numerical perspective, by studying the feasibility of inverting a solute outflow signal to yield the hydraulic parameters of the medium that housed the experiment. We found that the inverse problem was solvable under certain conditions, depending on the amount of noise in the signal and the degree of heterogeneity in the medium. A realistic three dimensional model of transient water and solute movement in a heterogeneous medium that contains plant roots was developed and tested. The approach taken was to generate a single realization of this complex flow event, and examine the results to see whether features were present that might be overlooked in less sophisticated model efforts. One such feature revealed is transverse dispersion, which is a critically important component in the development of macrodispersion in the longitudinal direction. The lateral mixing that was observed greatly exceeded that predicted from simpler approaches, suggesting that at least part of the important physics of the mixing process is embedded in the complexity of three dimensional flow. Another important finding was the observation that variability can produce a pseudo-kinetic behavior for solute adsorption, even when the local models used are equilibrium.
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Russo, David, et William A. Jury. Characterization of Preferential Flow in Spatially Variable Unsaturated Field Soils. United States Department of Agriculture, octobre 2001. http://dx.doi.org/10.32747/2001.7580681.bard.

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Preferential flow appears to be the rule rather than the exception in field soils and should be considered in the quantitative description of solute transport in the unsaturated zone of heterogeneous formations on the field scale. This study focused on both experimental monitoring and computer simulations to identify important features of preferential flow in the natural environment. The specific objectives of this research were: (1) To conduct dye tracing and multiple tracer experiments on undisturbed field plots to reveal information about the flow velocity, spatial prevalence, and time evolution of a preferential flow event; (2) To conduct numerical experiments to determine (i) whether preferential flow observations are consistent with the Richards flow equation; and (ii) whether volume averaging over a domain experiencing preferential flow is possible; (3) To develop a stochastic or a transfer function model that incorporates preferential flow. Regarding our field work, we succeeded to develop a new method for detecting flow patterns faithfully representing the movement of water flow paths in structured and non-structured soils. The method which is based on application of ammonium carbonate was tested in a laboratory study. Its use to detect preferential flow was also illustrated in a field experiment. It was shown that ammonium carbonate is a more conservative tracer of the water front than the popular Brilliant Blue. In our detailed field experiments we also succeeded to document the occurrence of preferential flow during soil water redistribution following the cessation of precipitation in several structureless field soils. Symptoms of the unstable flow observed included vertical fingers 20 - 60 cm wide, isolated patches, and highly concentrated areas of the tracers in the transmission zone. Soil moisture and tracer measurements revealed that the redistribution flow became fingered following a reversal of matric potential gradient within the wetted area. Regarding our simulation work, we succeeded to develop, implement and test a finite- difference, numerical scheme for solving the equations governing flow and transport in three-dimensional, heterogeneous, bimodal, flow domains with highly contrasting soil materials. Results of our simulations demonstrated that under steady-state flow conditions, the embedded clay lenses (with very low conductivity) in bimodal formations may induce preferential flow, and, consequently, may enhance considerably both the solute spreading and the skewing of the solute breakthrough curves. On the other hand, under transient flow conditions associated with substantial redistribution periods with diminishing water saturation, the effect of the embedded clay lenses on the flow and the transport might diminish substantially. Regarding our stochastic modeling effort, we succeeded to develop a theoretical framework for flow and transport in bimodal, heterogeneous, unsaturated formations, based on a stochastic continuum presentation of the flow and a general Lagrangian description of the transport. Results of our analysis show that, generally, a bimodal distribution of the formation properties, characterized by a relatively complex spatial correlation structure, contributes to the variability in water velocity and, consequently, may considerably enhance solute spreading. This applies especially in formations in which: (i) the correlation length scales and the variances of the soil properties associated with the embedded soil are much larger than those of the background soil; (ii) the contrast between mean properties of the two subdomains is large; (iii) mean water saturation is relatively small; and (iv) the volume fraction of the flow domain occupied by the embedded soil is relatively large.
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Clausen, Jay, Susan Frankenstein, Jason Dorvee, Austin Workman, Blaine Morriss, Keran Claffey, Terrance Sobecki et al. Spatial and temporal variance of soil and meteorological properties affecting sensor performance—Phase 2. Engineer Research and Development Center (U.S.), septembre 2021. http://dx.doi.org/10.21079/11681/41780.

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An approach to increasing sensor performance and detection reliability for buried objects is to better understand which physical processes are dominant under certain environmental conditions. The present effort (Phase 2) builds on our previously published prior effort (Phase 1), which examined methods of determining the probability of detection and false alarm rates using thermal infrared for buried-object detection. The study utilized a 3.05 × 3.05 m test plot in Hanover, New Hampshire. Unlike Phase 1, the current effort involved removing the soil from the test plot area, homogenizing the material, then reapplying it into eight discrete layers along with buried sensors and objects representing targets of inter-est. Each layer was compacted to a uniform density consistent with the background undisturbed density. Homogenization greatly reduced the microscale soil temperature variability, simplifying data analysis. The Phase 2 study spanned May–November 2018. Simultaneous measurements of soil temperature and moisture (as well as air temperature and humidity, cloud cover, and incoming solar radiation) were obtained daily and recorded at 15-minute intervals and coupled with thermal infrared and electro-optical image collection at 5-minute intervals.
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Anderson, Andrew, et Mark Yacucci. Inventory and Statistical Characterization of Inorganic Soil Constituents in Illinois : Appendices. Illinois Center for Transportation, juin 2021. http://dx.doi.org/10.36501/0197-9191/21-007.

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This report presents detailed histograms of data from the Regulated Substances Library (RSL) developed by the Illinois Department of Transportation (IDOT). RSL data are provided for state and IDOT region, IDOT district, and county spatial subsets to examine the spatial variability and its relationship to thresholds defining natural background concentrations. The RSL is comprised of surficial soil chemistry data obtained from rights-of-way (ROW) subsurface soil sampling conducted for routine preliminary site investigations. A selection of 22 inorganic soil analytes are examined in this report: Al, Sb, As, Ba, Be, Cd, Ca, Cr, Co, Cu, Fe, Pb, Mg, Mn, Hg, Ni, K, Se, Na, Tl, V, and Zn. RSL database summary statistics, mean, median, minimum, maximum, 5th percentile, and 95th percentile, are determined for Illinois counties and for recognized environmental concern, non-recognized environmental concern, and de minimis site contamination classifications.
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Ziegler, Nancy, Nicholas Webb, John Gillies, Brandon Edward, George Nikolich, Justin Van Zee, Brad Cooper, Dawn Browning, Ericha Courtright et Sandra LeGrand. Plant phenology drives seasonal changes in shear stress partitioning in a semi-arid rangeland. Engineer Research and Development Center (U.S.), septembre 2023. http://dx.doi.org/10.21079/11681/47680.

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Accurate representation of surface roughness in predictive models of aeolian sediment transport and dust emission is required for model accuracy. While past studies have examined roughness effects on drag partitioning, the spatial and temporal variability of surface shear velocity and the shear stress ratio remain poorly described. Here, we use a four-month dataset of total shear velocity (u*) and soil surface shear velocity (us*) measurements to examine the spatiotemporal variability of the shear stress ratio (R) before, during, and after vegetation green-up at a honey mesquite (Prosopis glandulosa Torr.) shrub-invaded grassland in the Chihuahuan Desert, New Mexico, USA. Results show that vegetation green-up, the emergence of leaves, led to increased drag and surface aerodynamic sheltering and a reduction in us* and R magnitude and variability. We found that us* decreased from 20% to 5% of u* as the vegetation form drag and its sheltering effect increased. Similarly, the spatiotemporal variability of R was found to be linked directly to plant phenological phases. We conclude that drag partition schemes should incorporate seasonal vegetation change, via dynamic drag coefficients and/or R, to accurately predict the timing and magnitude of seasonal aeolian sediment fluxes.
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Sprague, R. A. Spatial Correlation of Ionospheric Variability. Fort Belvoir, VA : Defense Technical Information Center, mars 1994. http://dx.doi.org/10.21236/ada278105.

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Sparrow, Kent, et Sandra LeGrand. Establishing a series of dust event case studies for North Africa. Engineer Research and Development Center (U.S.), février 2023. http://dx.doi.org/10.21079/11681/46445.

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Dust aerosols often create hazardous air quality conditions that affect human health, visibility, agriculture, and communication in various parts of the world. While substantial progress has been made in dust-event simulation and hazard mitigation over the last several decades, accurately forecasting the spatial and temporal variability of dust emissions continues to be a challenge. This report documents an analysis of atmospheric conditions for a series of dust events in North Africa. The researchers highlight four analyzed events that occurred between January 2016 to present in the following locations: (1) the western Sahara Desert; (2) East Algeria and the Iberian Peninsula; (3) Chad-Bodélé Depression; (4) Algeria and Morocco. For each event, the researchers developed an overview of the general synoptic, mesoscale, and local environmental forcing conditions that controlled the event evolution and used a combination of available lidar data, surface weather observations, upper-air soundings, aerosol optical depth, and satellite imagery to characterize the dust conditions. These assessments will support downstream forecast model evaluation and sensitivity testing; however, the researchers also encourage broader use of these assessments as reference case studies for dust transport, air quality modeling, remote sensing, soil erosion, and land management research applications.
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Baxter, W., Amanda Barker, Samuel Beal, Lauren Bosche, Ryan Busby, Zoe Courville, Elias Deeb et al. A comprehensive approach to data collection, management, and visualization for terrain characterization in cold regions. Engineer Research and Development Center (U.S.), février 2024. http://dx.doi.org/10.21079/11681/48212.

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As global focus shifts to northern latitudes for their enhanced access to newly viable resources, US Army operational readiness in these extreme environments is increasingly important. Rapid and accurate intelligence on the conditions influencing operations in these regions is essential to mission success and warfighter safety. Arctic and boreal environments are highly heterogeneous, including changing extents of frozen versus thawing ground, snow, and ice that affect ground trafficability and visibility, terrain physics, and physicochemical properties of water and soil. Furthermore, projected climatic warming in these regions makes the timing of seasonal transitions increasingly uncertain. Broad coverage of long-term datasets is critical for assessing spatial and temporal variability in these northern environments at the landscape-scale. However, decadal measurements are difficult to acquire, manage, and visualize in the field setting. Here, we present a synopsis of data collection, management, and visualization for long-term permafrost, snow, vegetation, geophysics, and biogeochemical data from Alaska and review related literature. We also synthesize short-term data from various permafrost affected sites in the US and northern Europe to further assess the state of northern landscapes. Altogether, this work provides a comprehensive approach for high-latitude field site management to accurately inform mission-related operations in extreme northern environments.
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