Relevant bibliographies by topics / Soil moisture

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Soil moisture'

Author: Grafiati
Published: 4 June 2021
Last updated: 30 July 2024

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Journal articles on the topic "Soil moisture"

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Hatton, Thomas J., Neil R. Viney, E. A. Catchpole, and Neville J. De Mestre. "The Influence of Soil Moisture on Eucalyptus Leaf Litter Moisture." Forest Science 34, no. 2 (June 1, 1988): 292–301. http://dx.doi.org/10.1093/forestscience/34.2.292.

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Abstract An experiment was carried out to test the assumption that surface soil moisture affects fine dead fuel moisture. A randomized block design was used to test the response in Eucalyptus leaf moisture to two levels of soil moisture over a range of exposures to the sun, wind, and soil surface. Soil moisture clearly influenced daily leaf fuel moisture minima and maxima. The effect on daily minima was most pronounced for the bottom of the litter layer, which was shielded from the sun and wind and in contact with the soil. The effect of soil moisture on daily fuel moisture maxima was most pronounced for exposed samples. The responses in fuel moisture due to exposure and soil moisture were compared with fine fuel moistures predicted by three fuel moisture models. The various treatment combinations of soil moisture and exposure produced fuel moistures that varied too widely for any of the tested fuel moisture models to be consistently most accurate. For. Sci. 34(2):292-301.
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Richter, H., A. W. Western, and F. H. S. Chiew. "The Effect of Soil and Vegetation Parameters in the ECMWF Land Surface Scheme." Journal of Hydrometeorology 5, no. 6 (December 1, 2004): 1131–46. http://dx.doi.org/10.1175/jhm-362.1.

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Abstract Numerical Weather Prediction (NWP) and climate models are sensitive to evapotranspiration at the land surface. This sensitivity requires the prediction of realistic surface moisture and heat fluxes by land surface models that provide the lower boundary condition for the atmospheric models. This paper compares simulations of a stand-alone version of the European Centre for Medium-Range Weather Forecasts (ECMWF) land surface scheme, or the Viterbo and Beljaars scheme (VB95), with various soil and vegetation parameter sets against soil moisture observations across the Murrumbidgee River catchment in southeast Australia. The study is, in part, motivated by the adoption of VB95 as the operational land surface scheme by the Australian Bureau of Meteorology in 1999. VB95 can model the temporal fluctuations in soil moisture, and therefore the moisture fluxes, fairly realistically. The monthly model latent heat flux is also fairly insensitive to soil or vegetation parameters. The VB95 soil moisture is sensitive to the soil and, to a lesser degree, the vegetation parameters. The model exhibits a significant (generally wet) bias in the absolute soil moisture that varies spatially. The use of the best Australia-wide available soils and vegetation information did not improve VB95 simulations consistently, compared with the original model parameters. Comparisons of model and observed soil moistures revealed that more realistic soil parameters are needed to reduce the model soil moisture bias. Given currently available continent-wide soils parameters, any initialization of soil moisture with observed values would likely result in significant flux errors. The soil moisture bias could be largely eliminated by using soil parameters that were derived directly from the actual soil moisture observations. Such parameters, however, are only available at very few point locations.
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Reardon, James, Gary Curcio, and Roberta Bartlette. "Soil moisture dynamics and smoldering combustion limits of pocosin soils in North Carolina, USA." International Journal of Wildland Fire 18, no. 3 (2009): 326. http://dx.doi.org/10.1071/wf08085.

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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 the sustained smoldering limits of organic soils will improve our understanding of changes in ground fire potential over time. Seasonal soil moisture trends were monitored in six North Carolina coastal plain pocosin sites from January 2005 to November 2007. Measurements of the root-mat upper soil horizons were sampled at 2-week intervals while measurements of lower horizon muck (sapric) soil moisture contents and watertable depths were made with automated data logging equipment. The watertable and soil moisture responses were influenced by seasonal and yearly differences in precipitation and hydrologic factors. The maximum estimated probabilities of sustained smoldering were highest in the fall of 2007 and lowest in 2006. Watertable depth was not a consistent predictor of the smoldering combustion potential in the upper organic soil horizons. Maximum Keetch–Byram Drought Index values on all sites were between 500 and 662 during 2005 and 2007 and these values were not consistent with measured soil moistures.
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Rahman, Mohammad Mahfuzur, and Minjiao Lu. "Characterizing Soil Moisture Memory by Soil Moisture Autocorrelation." Journal of Water Resource and Hydraulic Engineering 4, no. 1 (January 15, 2015): 83–92. http://dx.doi.org/10.5963/jwrhe0401007.

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Yi, Xiaobo, Ji Luo, Pengyan Wang, Xiao Guo, Yuanjie Deng, Tao Du, Haijun Wang, Cuicui Jiao, Guofu Yuan, and Mingan Shao. "Spatial and Temporal Variations in Soil Moisture for a Tamarisk Stand under Groundwater Control in a Hyper-Arid Region." Water 15, no. 19 (September 28, 2023): 3403. http://dx.doi.org/10.3390/w15193403.

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In hyper-arid regions, soil moisture’s role in ecohydrological processes can differ significantly from that in arid or semi-arid ecosystems. We investigated the spatial–temporal dynamics of soil moisture and its relationship with groundwater depths in a 200 m × 300 m phreatophytic tamarisk stand in the lower basin of the Tarim River, a hyper-arid zone in China. Soil moisture profiles, from the surface to the water table, were derived using drilling and oven-drying techniques. Over a three-year period, the soil moisture at multiple depths was continuously monitored in a specific plot using nine frequency domain reflectometry (FDR) sensors. Our results indicate a correlation between horizontal variations in soil moisture and groundwater depths (GWDs). Nevertheless, anomalies in this correlation were observed. Variations in horizontal soil moisture were strongly influenced by the clay content in the soil, with finer soils retaining more moisture. Despite varying GWDs, soil moisture profiles remained consistent, with no distinct correlation between them. Soil moisture exhibited stability across layers, with noticeable changes only adjacent to the water table. These results imply that in hyper-arid environments, soil texture primarily governs soil moisture distribution. However, the limited spatial and temporal scopes in our dataset, constrained by the region’s inhospitable conditions, necessitate further investigation. Future work should prioritize amalgamating diverse data sources to devise a region-specific soil moisture model for in-depth analysis of hyper-arid regions.
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Tužinský, L. "Soil moisture in mountain spruce stand." Journal of Forest Science 48, No. 1 (May 17, 2019): 27–37. http://dx.doi.org/10.17221/11854-jfs.

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Mountain forests are among the main components of natural environment in Slovakia. They grow mainly in areas with cold climate, on poor soils with unfavorable reaction, often very acidic (pH in H<sub>2</sub>O &lt; 4.5) and with nutrient deficit. Immissions and acid rain attack forests to a great extent. Global climate changes also represent a new threat. Extremes in air temperatures, excessive amounts of precipitation or on the other hand the lack of water from precipitation, torrential rains or long-lasting drought periods are recorded as a result of a higher amount of heat energy accumulation from the greenhouse effect. Spruce forests are most endangered. Spruce with its root system concentrated in the upper soil layers, where also the highest amount of toxic elements accumulates, suffers more and more from dry and warm periods and it begins to wither due to drought. The occurrence of hydropedological cycles with a low or insufficient supply of available water in the soil is most frequent during summer (July, August). If the soil water potential values approach the value of the wilting point, an expressive decrease in transpiration is observed during the day, whereas its daily course is also suppressed. Gradual soil drying up from the upper layers towards the deepest ones of the physiological profile of soil represents a change in soil moisture stratification, especially after moistening the upper layers of soil with water from atmospheric precipitation. The deeper soil layers need not be re-saturated in such a case. Under drought the whole physiological profile of soil dries up in a relatively short time. Trees are exposed to a strong physiological stress in such conditions and after longlasting drought periods they can get into the state of total exhaustion.
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Li, Xin, Yudong Lu, Xiaozhou Zhang, Rong Zhang, Wen Fan, and Wangsheng Pan. "Influencing Factors of the Spatial–Temporal Variation of Layered Soils and Sediments Moistures and Infiltration Characteristics under Irrigation in a Desert Oasis by Deterministic Spatial Interpolation Methods." Water 11, no. 7 (July 17, 2019): 1483. http://dx.doi.org/10.3390/w11071483.

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Soil moisture is the main limiting factor for crop growth and the sustainable development of oases in arid desert areas. Therefore, the temporal and spatial variation and infiltration laws of oasis soil moisture should be studied. The objective of this study is to reveal the influencing factors of the spatial–temporal variation of layered soil and sediment moisture and infiltration characteristics under irrigation in desert oases. Hydraulic conductivities were measured using the double-ring infiltrometer, while the regional and site soil moistures were measured and calibrated using weighted method and neutron moisture meter. Deterministic spatial interpolation methods, including multiquadric radial basis function, inverse distance weighted, and local polynomial regression isogram, were adopted to map the regional distribution of hydraulic conductivities, spatial soil moistures, and spatial–temporal isogram of the point site soil moistures in Yaoba Oasis, respectively. Results showed that the leading influencing factors of the (1) regional spatial soil moisture were soil and sediment permeability, stream link direction, microclimate, and dewfalls; (2) spatial layered soil and sediment moistures were microclimate and dew condensation; and (3) spatial–temporal variation at the point site profiles were soil texture, water requirement, and preferential flow. Under irrigation, soil moisture increased significantly, in which the maximum increase was 10.8 times the original state, while the recharging depth substantially increased up to 580 cm with the preferential flow. The spatial–temporal variation of the soil moisture under irrigation indicated that the best irrigation frequency should be 15 days per time. Moreover, the infiltration process can be divided into the preferential flow, piston flow, and balanced infiltration stages.
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Baskoro, Dwi Putro Tejo, and Suria Darma Tarigan. "Soil Moisture Characteristics on Several Soil Types." Jurnal Ilmu Tanah dan Lingkungan 9, no. 2 (October 1, 2007): 77–81. http://dx.doi.org/10.29244/jitl.9.2.77-81.

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Soil water availability is one of the important factors injluencing plant growth. Soil that can store more water in alonger time can support a better plant growth. This study was aimed to evaluate the dynamics of soil water of four differentsoils with different characteristics. Four soils classes are clayey textured soils-Red Yellowish Podsolik Jasinga, Clayeytextured soils-Latosol Darmaga, . Sandy Textured soil-Regosol Sindang Barang, and highly organic mater content soi/sAndosolSukamantri. The result showed that at every-suction analyzed, Andosol Sukamantri had consistently highest watercontent while Regosol Sindang Barang was consistently lowest. Similar tendency wasfoundfor available water capacity. Theresult also showed that moisture content at Regosol decrease more rapidly than those of the other three soils. The time need to reach likely constant moisture content is variable with soil type; lowest at Regosol Sindangbarang (45 hours after completely saturated and drained) followed by Podsolik Jasinga (73 hours), Latosol darmaga (74 hours) and Andosol Sulcamatri (76 hours).
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Eckertová, Terézia, Karol Holý, Monika Müllerová, Ivan Sýkora, and Jozef Masarik. "EMANATION OF RADON-222 FROM DIFFERENT SOIL TYPES AND SOIL GROUPS." Radiation Protection Dosimetry 198, no. 9-11 (August 2022): 771–77. http://dx.doi.org/10.1093/rpd/ncac132.

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Abstract In this paper, we deal with measurement of 222Rn emanation coefficient (Ke) of soils using an accumulation method. We created a database of Ke values of dried soils for various soil types and soil groups, classified by the size of soil particles. For 18 different soil samples we obtained the Ke values in range 0.083–0.234. The analysis of radon emanation dependence on moisture for seven of these samples shows two different trends which were related to soil texture (clays or sands). Soils with predominant sandy particles prove weak dependence on moisture and Ke values from minimum value (at zero moisture) do not increase much (max 15% increase on every 5% of moisture), for soils with majority of clayey particles the moisture can affect the Ke more significantly (increase up to 60%).
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Hamad, Asal Mahmud, and Mahmood Gazey Jassam. "A Comparative Study for the Effect of Some Petroleum Products on the Engineering Properties of Gypseous Soils." Tikrit Journal of Engineering Sciences 29, no. 3 (October 15, 2022): 69. http://dx.doi.org/10.25130/tjes.29.3.7.

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Gypseous soils are considered problematic soils because the soil cavities happen during receiving the water or this type of soil and solving gypsum materials and contract in a soil volume. In this study, three types of gypseous soils are used; soil1, soil2, and soil3 with gypsum content (28.71%, 43.6%, and 54.88%) respectively, petroleum products (engine oil, fuel oil, and kerosene) are added to the soils with percentages (3%, 6%, 9%, and 12%) for each product. The result showed that specific gravity, liquid limit, optimum moisture content (O.M.C), and maximum dry density decreased with an increased percentage of product for all types of products. The direct shear (dry and soaked case) results show that increasing the (angle of internal friction and the soil cohesion) for soil1, soil2, and soil3 by adding engine oil and fuel oil. Still, when the soils were treated with kerosene, the angle of internal friction increased while cohesion decreased. The collapse potential for the treated soils increases with increasing gypsum content for all petroleum products. The collapse potential (CP) for (soil1) decreased by 47% when using 6% of the engine oil, 48.8% when using 9% of the fuel oil, and 55% when using 9% of the kerosene. The same percentage of the petroleum products (engine oil, fuel oil, and kerosene) decrease the collapse potential for (soil2), (47%, 46%, and 50%) respectively and decrease the collapse potential for (soil 3), (51%, 47.7%, and 52%) respectively. In the unconfined compressive test applied on (soil1) using maximum density, the results show that the soil strength increased (26% and 10%) when using 6% and engine oil and fuel oil, respectively, while the soil strength decreased by 29% when treated with 9% of kerosene.
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Dissertations / Theses on the topic "Soil moisture"

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Njie, Momodou. "Modelling soil moisture dynamics in vegetated soils." Thesis, Imperial College London, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.406159.

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Alvenäs, Gunnel. "Evaporation, soil moisture and soil temperature of bare and cropped soils /." Uppsala : Swedish Univ. of Agricultural Sciences (Sveriges lantbruksuniv.), 1999. http://epsilon.slu.se/avh/1999/91-576-5714-9.pdf.

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Sherratt, David Joseph. "Regional soil moisture modelling." Thesis, Imperial College London, 1985. http://hdl.handle.net/10044/1/8230.

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Omotere, Olumide Olubunmi. "Improvement of the Soil Moisture Diagnostic Equation for Estimating Root-Zone Soil Moisture." Thesis, University of North Texas, 2018. https://digital.library.unt.edu/ark:/67531/metadc1157607/.

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Soil moisture information can be used accurately in determining the timing and amount of irrigation applied to plants. Pan and Pan et al. proposed a robust and simple daily diagnostic equation for estimating daily soil moisture. The diagnostic equation evaluates the relationship between the soil moisture loss function and the summation weighted average of precipitation. The loss function uses the sinusoidal wave function which employs day of the year (DOY) to evaluate the seasonal variation in soil moisture loss for a given year. This was incorporated into the daily diagnostic equation to estimate the daily soil moisture for a location. Solar radiation is an energy source that drives the energy and water exchanges between vegetation and the atmosphere (i.e., evapotranspiration), and thus impacts the soil moisture dry-down. In this paper, two parameters (the actual solar radiation and the clear sky solar radiation) are introduced into loss function coefficient to improve the estimation of soil moisture. After the Introduction of the solar radiation data into soil moisture loss function, a slight improvement was observed in the estimated daily soil moisture. Pan observed that generally the correlation coefficient between the estimated and the observed soil moisture is above 0.75 and the root mean square error is below 5.0 (%v/v). The introduction solar radiation data (i.e. clear sky solar radiation and actual solar) improve the correlation coefficient average for all the sites evaluated by 0.03 when the root mean square error is generally below 4.5(%v/v) for the entire root zone.
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Franks, Carol Dawn. "Temperature, moisture and albedo properties of Arizona soils." Thesis, The University of Arizona, 1985. http://etd.library.arizona.edu/etd/GetFileServlet?file=file:///data1/pdf/etd/azu_e9791_1985_263_sip1_w.pdf&type=application/pdf.

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Soriano, Melissa. "Estimation of soil moisture in the southern united states in 2003 using multi-satellite remote sensing measurements." Fairfax, VA : George Mason University, 2008. http://hdl.handle.net/1920/3361.

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Thesis (M.S.)--George Mason University, 2008.
Vita: p. 65. Thesis director: John Qu. Submitted in partial fulfillment of the requirements for the degree of Master of Science in Earth System Science. Title from PDF t.p. (viewed Jan. 11, 2009). Includes bibliographical references (p. 59-64). Also issued in print.
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El-Bishti, Magda Bashier. "Determination of soil moisture using dielectric soil moisture sensors : effect of soil temperature and implication for evaporation estimates." Thesis, University of Reading, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.487102.

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The reliability and accuracy of several sensors that employ the relationship between dielectric constant and soil moisture constant, e, in particular capacitance sensors were investigated. Results obtained from laboratory examinations ,of a Theta probe, TP, selected as a representative model for capacitance sensors, suggested that the sensor output was affected by temperature variations, electrical conductivity levels, spatial variation in sample bulk density as well as the level of compaction of the soil surrounding the sensor's rods. Detailed in situ e data collected usmg capacitance sensors were used to calculate sub-daily estimates of evaporation, E, using the soil water balance method, combined with the zero-flux-plane (ZFP) approach, for plots of bare soil, rapeseed and a maize field. These sensors comprised Theta probes (TP), Profiles probes (PP), ECH20 probes (EP) and Aquaflex sensors (AF). / The field output data of these sensors were analysed and compared with e obtained with both, the gravimetric and neutron probe method. The absolute values of B as measured by the various capacitance sensors differed considerably. Furthermore, the outputs of these sensors (apart from the AF probes) were found to be affected by temperature, which would result in an anomalous course of diurnal E. Also, B-data were subject to noise which required smoothing to ensure a physically realistic variation in E, when compared to estimates with the Penman-Monteith equation, EPAf, and the eddy-covariance method (maize field). E was determined from diurnal changes in vertically integrated soil moisture content above the ZFP. Smoothed values of Bwere temperature-corrected using fieldbased and laboratory-based correction equations. A considerable difference between field- and laboratory-based temperature corrections procedures was noticed, and correction factors strongly depended on B. As this resulted in an overly complicated correction procedure, which consequently gave unreliable E-values, it was then decided to use a constant correction factor (based on the field correction procedure), for each capacitance probe. For the bare soil plot, with the exception ofPP and EP only Bprofiles obtained with the TP and AF sensors produced relatively reliable E values when compared to Enf. By contrast, when these capacitance sensors were used under a canopy, all sensors yielded satisfactory E-values. This was most likely caused by reduced amplitudes of soil temperatures under the canopy and the fact that the dimensions of most sensors do not allow installation in the top soil (~3-5cm) layer at which most evaporation would take place in bare soils. We therefore recommended that these sensors can be used for diurnal B measurements and E determination under canopy provided that an appropriate temperature-correction procedure for each sensor is applied. To obtain reliable Band E estimates in bare soil, more research needs to be done. For more reliable e and E estimations in bare soils further extensive field trials would be strongly advised
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Zhang, Guanghui, and 張廣輝. "Soil-water characteristics of sandy soil and soil cement with and without vegetation." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2014. http://hdl.handle.net/10722/208025.

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The use of soil cement as a growth medium was examined in this study. During the monitoring, green soil cement revealed diverse ecological values. The survival rates of plants in each soil conditions were higher than 80%,which was very promising. Furthermore, the survival rates dropped when the soil density reached95%, which means soil density might influence the survival rate of plant. Plant growth rates in sandy soil were higher than that in soil cement. In particular, low soil density facilitated plant growth in sandy soil, whereas density effect was not clear to plant growth performance in soil cement. Experiments were undertaken to study the soil-water characteristics of sandy soil and soil cement in field and laboratory condition. The influence of vegetation and material density on the development of negative pore water pressure (PWP) and degree of saturation (Sr) in the studied materials was investigated. The field planting experiments proved a promising survival rate of Schefflera heptaphylla in both types of materials while sandy soil promoted better growth of the seedlings than the soil cement. From the field study, PWP and Sr of sandy soil responded noticeably and promptly to natural drying and wetting cycles. However, the responses in soil cement were relatively mild. When subjected to the same drying-wetting cycles, PWP responded more slowly and to a smaller magnitude compared with that of soil cement. In addition, Sr changed little in soil cement. An increase in the density of the sandy soil promoted rapid development of negative PWP, while an opposite trend was observed for soil cement. Attempts have been made to explain the observations from the perspectives of material permeability and change in water content during a drying period in both soil types. Furthermore, in sandy soil, the development of PWP (with a measurement limit of -90 kPa) was minimally affected by the presence of vegetation, while vegetation noticeably helped the development of negative PWP in the soil cement. Bounds of the soil-water characteristic curve of the studied materials were presented based on estimates from the drying and wetting scanning curves derived from the field monitoring. A complementary laboratory study was carried out in an environmental chamber with controllable temperature and humidity. Monitoring results from the laboratory agreed well with that obtained from the field.
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Ridley, Andrew Martin. "The measurement of soil moisture suction." Thesis, Imperial College London, 1993. http://hdl.handle.net/10044/1/7933.

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Snapir, Boris. "SAR remote sensing of soil Moisture." Thesis, Cranfield University, 2014. http://dspace.lib.cranfield.ac.uk/handle/1826/9253.

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Synthetic Aperture Radar (SAR) has been identified as a good candidate to provide high-resolution soil moisture information over extended areas. SAR data could be used as observations within a global Data Assimilation (DA) approach to benefit applications such as hydrology and agriculture. Prior to developing an operational DA system, one must tackle the following challenges of soil moisture estimation with SAR: (1) the dependency of the measured radar signal on both soil moisture and soil surface roughness which leads to an ill-conditioned inverse problem, and (2) the difficulty in characterizing spatially/temporally surface roughness of natural soils and its scattering contribution. The objectives of this project are (1) to develop a roughness measurement method to improve the spatial/temporal characterization of soil surface roughness, and (2) to investigate to what extent the inverse problem can be solved by combining multipolarization, multi-incidence, and/or multi-frequency radar measurements. The first objective is achieved with a measurement method based on Structure from Motion (SfM). It is tailored to monitor natural surface roughness changes which have often been assumed negligible although without evidence. The measurement method is flexible, a.ordable, straightforward and generates Digital Elevation Models (DEMs) for a SAR-pixel-size plot with mm accuracy. A new processing method based on band-filtering of the DEM and its 2D Power Spectral Density (PSD) is proposed to compute the classical roughness parameters. Time series of DEMs show that non-negligible changes in surface roughness can happen within two months at scales relevant for microwave scattering. The second objective is achieved using maximum likelihood fitting of the Oh backscattering model to (1) full-polarimetric Radarsat-2 data and (2) simulated multi-polarization / multi-incidence / multi-frequency radar data. Model fitting with the Radarsat-2 images leads to poor soil moisture retrieval which is related to inaccuracy of the Oh model. Model fitting with the simulated data quantifies the amount of multilooking for di.erent combinations of measurements needed to mitigate the critical e.ect of speckle on soil moisture uncertainty. Results also suggest that dual-polarization measurements at L- and C-bands are a promising combination to achieve the observation requirements of soil moisture. In conclusion, the SfM method along with the recommended processing techniques are good candidates to improve the characterization of surface roughness. A combination of multi-polarization and multi-frequency radar measurements appears to be a robust basis for a future Data Assimilation system for global soil moisture monitoring.
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Books on the topic "Soil moisture"

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Heidmann, L. J. Comparison of moisture retention curves for representative basaltic and sedimentary soils in Arizona prepared by two methods. [Fort Collins, Colo.]: USDA Forest Service, Rocky Mountain Forest and Range Experiment Station, 1990.

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Zaĭdelʹman, F. R. Gidrologicheskiĭ rezhim pochv Nechernozemnoĭ zony: Geneticheskie, agronomicheskie i meliorativnye aspekty. Leningrad: Gidrometeoizdat, 1985.

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Iwata, Shingo. Soil-water interactions: Mechanisms and applications. 2nd ed. New York: M. Dekker, 1995.

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Sandhu, G. R. Plant available moisture in Pothwar barani area. Islamabad: Natural Resources Division, Pakistan Agriculatural Research Council, 1987.

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Séminaire scientifique de pédologie pour la région de l'Amérique centrale et des Caraïbes: Sol et eau (1er : 1985 : Havana, Cuba), ed. Sol et eau: Actes du séminaire de la Havane, 8-20 avril 1985 = Suelo y agua : actas del seminario de la Habana, 8-20 abril 1985. Paris: Editions de l'ORSTOM, 1986.

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Riou, G. L' eau et les sols dans les géosystèmes tropicaux: Systèmes d'érosion hydrique. Paris: Masson, 1990.

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Seminar on French Agronomic Research in the Tropics (1986 : World Bank), ed. Sols et eaux: Acquis et perspectives de la recherche agronomique française en zone intertropicale : actes du séminaire tenu à la Banque mondiale les 15 et 16 mai 1986. Paris: Editions de l'ORSTOM, 1986.

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Kühnel, Vít. Scale problems in soil moisture flow. Dublin: University College Dublin, 1989.

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Starr, G. Lynn. Soil bulk density and soil moisture calculated with a FORTRAN 77 program. Portland, Or: U.S. Dept. of Agriculture, Forest Service, Pacific Northwest Research Station, 1988.

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McGill University. Geotechnical Research Centre., ed. GRC studies on soil properties and soil-water relations. Montreal, Que., Canada: McGill University, Geotechnical Research Centre, 1993.

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Book chapters on the topic "Soil moisture"

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Engman, E. T., and R. J. Gurney. "Soil moisture." In Remote Sensing in Hydrology, 127–54. Dordrecht: Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-009-0407-1_7.

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Kerr, Yann. "Soil Moisture." In Encyclopedia of Remote Sensing, 783–88. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-0-387-36699-9_173.

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Engman, Edwin T. "Soil Moisture." In Remote Sensing in Hydrology and Water Management, 197–216. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-59583-7_9.

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Bakker, H. "Soil Moisture." In Sugar Cane Cultivation and Management, 107–19. Boston, MA: Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-4725-9_10.

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Carson, M. A. "Soil Moisture." In Water, Earth, and Man, 185–95. London: Routledge, 2021. http://dx.doi.org/10.4324/9781003170181-17.

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Day, Arden D., and Kenneth L. Ludeke. "Soil Moisture." In Plant Nutrients in Desert Environments, 19–22. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-77652-6_5.

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Shaxson, T. F. "Soil Moisture Conservation." In Conservation Agriculture, 317–26. Dordrecht: Springer Netherlands, 2003. http://dx.doi.org/10.1007/978-94-017-1143-2_38.

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Waller, Peter, and Muluneh Yitayew. "Modeling Soil Moisture." In Irrigation and Drainage Engineering, 493–510. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-05699-9_28.

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Dwivedi, Ravi Shankar. "Soil Moisture Estimation." In Remote Sensing of Soils, 399–456. Berlin, Heidelberg: Springer Berlin Heidelberg, 2017. http://dx.doi.org/10.1007/978-3-662-53740-4_9.

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O’Connor, Kevin M., and Charles H. Dowding. "Monitoring Soil Moisture." In GeoMeasurements by Pulsing TDR Cables and Probes, 49–79. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003067726-3.

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Conference papers on the topic "Soil moisture"

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Liu, L. S., and J. C. Shi. "Soil Moisture Variations Monitoring Using New Microwave Soil Moisture Index (MSMI)." In 2012 2nd International Conference on Remote Sensing, Environment and Transportation Engineering (RSETE). IEEE, 2012. http://dx.doi.org/10.1109/rsete.2012.6260727.

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Hatanaka, Daisuke, Alireza Ahrary, and Dennis Ludena. "Research on Soil Moisture Measurement Using Moisture Sensor." In 2015 IIAI 4th International Congress on Advanced Applied Informatics (IIAI-AAI). IEEE, 2015. http://dx.doi.org/10.1109/iiai-aai.2015.289.

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Yang, Zhengwei, Ranjay Shrestha, Wade Crow, John Bolten, Iva Mladenova, Genong Yu, and Liping Di. "Evaluation of assimilated SMOS Soil Moisture data for US cropland Soil Moisture monitoring." In IGARSS 2016 - 2016 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2016. http://dx.doi.org/10.1109/igarss.2016.7730366.

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Sure, Anudeep, Divyesh Varade, and Onkar Dikshit. "Estimating root zone soil moisture from AMSR2 remotely sensed surface soil moisture data." In 2018 3rd International Conference on Microwave and Photonics (ICMAP). IEEE, 2018. http://dx.doi.org/10.1109/icmap.2018.8354490.

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Philpot, William d. "The soil line: moisture-independent soil reflectance spectra." In Hyperspectral Imaging and Sounding of the Environment. Washington, D.C.: OSA, 2019. http://dx.doi.org/10.1364/hise.2019.htu4c.2.

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Pultz, Terry J., Jennifer Sokol, Brian Brisco, Ron J. Brown, and Q. H. J. Gwyn. "Soil moisture estimation with RADARSAT." In Aerospace Remote Sensing '97, edited by Giovanna Cecchi, Edwin T. Engman, and Eugenio Zilioli. SPIE, 1997. http://dx.doi.org/10.1117/12.298140.

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Malajner, Marko, and Dusan Gleich. "Soil moisture estimation using UWB." In 2016 IEEE/ACES International Conference on Wireless Information Technology and Systems (ICWITS) and Applied Computational Electromagnetics (ACES). IEEE, 2016. http://dx.doi.org/10.1109/ropaces.2016.7465427.

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Wu, Xiaopei, and Mingyan Liu. "In-situ soil moisture sensing." In the 11th international conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2185677.2185679.

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Bindlish, R., T. Jackson, M. Cosh, T. Koike, X. Fuiji, R. de Jeu, S. Chan, et al. "AMSR2 soil moisture product validation." In 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). IEEE, 2017. http://dx.doi.org/10.1109/igarss.2017.8128284.

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Kerr, Yann H., Jean Pierre Wigneron, Philippe Waldteufel, Jean-Christophe Calvet, and Michael Berger. "Soil moisture monitoring with SMOS." In International Symposium on Remote Sensing, edited by Manfred Owe and Guido D'Urso. SPIE, 2002. http://dx.doi.org/10.1117/12.454183.

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Reports on the topic "Soil moisture"

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DeJong, Joel, and Paul Kassel. Soil Moisture. Ames: Iowa State University, Digital Repository, 2016. http://dx.doi.org/10.31274/farmprogressreports-180814-1372.

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DeJong, Joel, and Paul Kassel. Soil Moisture. Ames: Iowa State University, Digital Repository, 2016. http://dx.doi.org/10.31274/farmprogressreports-180814-1401.

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DeJong, Joel L. Soil Moisture. Ames: Iowa State University, Digital Repository, 2010. http://dx.doi.org/10.31274/farmprogressreports-180814-152.

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DeJong, Joel. Soil Moisture. Ames: Iowa State University, Digital Repository, 2017. http://dx.doi.org/10.31274/farmprogressreports-180814-1690.

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DeJong, Joel. Soil Moisture. Ames: Iowa State University, Digital Repository, 2017. http://dx.doi.org/10.31274/farmprogressreports-180814-1721.

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DeJong, Joel. Soil Moisture. Ames: Iowa State University, Digital Repository, 2018. http://dx.doi.org/10.31274/farmprogressreports-180814-1965.

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DeJong, Joel. Soil Moisture. Ames: Iowa State University, Digital Repository, 2018. http://dx.doi.org/10.31274/farmprogressreports-180814-1977.

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DeJong, Joel L., and Paul C. Kassel. Soil Moisture. Ames: Iowa State University, Digital Repository, 2007. http://dx.doi.org/10.31274/farmprogressreports-180814-2340.

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DeJong, Joel L., and Paul C. Kassel. Soil Moisture. Ames: Iowa State University, Digital Repository, 2004. http://dx.doi.org/10.31274/farmprogressreports-180814-2398.

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DeJong, Joel L., and Paul C. Kassel. Soil Moisture. Ames: Iowa State University, Digital Repository, 2006. http://dx.doi.org/10.31274/farmprogressreports-180814-2502.

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