140 research outputs found

    Soil Water Dynamics in a Rainfed Mediterranean Agricultural System

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    [EN] Rainfed Mediterranean agriculture is characterized by low water input and by soil water content below its field capacity during most of the year. However, erratic rainfall distribution can lead to deep drainage. The understanding of soil-water dynamics is essential to prevent collateral impacts in subsuperficial waters by leached pollutants and to implement suitable soil management (e.g., agronomic measures to avoid nitrate leaching). Soil water dynamics during two fallow years and three barley crop seasons was evaluated using the Leaching estimation and chemistry model in a semiarid Mediterranean agricultural system. Model calibration was carried out using soil moisture data from disturbed soil samples and from capacitance probes installed at three depths. Drainage of water from the plots occurred in the fall and winter periods. The yearly low drainage values obtained (<15 mm) indicate that the estimated annual nitrate leaching is also small, regardless of the nature of the fertilizer applied (slurries or minerals). In fallow periods, there is a water recharge in the soil, which does not occur under barley cropping. However, annual fallow included in a winter cereal rotation, high nitrate residual soil concentrations (similar to 80 mg NO3--N L-1) and a period with substantial autumn-winter rains (70-90 mm) can enhance nitrate leaching, despite the semiarid climate.This research was funded by the Spanish Ministry of Economy and Competitiveness and the Spanish National Institute for Agricultural Research and Experimentation (MINECO-INIA) through the projects [RTA2013-57-C5-5] and [RTA2017-88-C3-3]. The PhD studies of D.E. Jimenez-de-Santiago were funded by the JADE-Plus scholarship from Bank of Santander-University of Lleida.Jimenez-De-Santiago, DE.; Lidón, A.; Bosch-Serra, AD. (2019). Soil Water Dynamics in a Rainfed Mediterranean Agricultural System. Water. 11(4):1-21. https://doi.org/10.3390/w11040799S121114Sordo-Ward, A., Granados, I., Iglesias, A., & Garrote, L. (2019). Blue Water in Europe: Estimates of Current and Future Availability and Analysis of Uncertainty. Water, 11(3), 420. doi:10.3390/w11030420Rockström, J., Karlberg, L., Wani, S. P., Barron, J., Hatibu, N., Oweis, T., … Qiang, Z. (2010). Managing water in rainfed agriculture—The need for a paradigm shift. Agricultural Water Management, 97(4), 543-550. doi:10.1016/j.agwat.2009.09.009Moret, D., Arrúe, J. L., López, M. V., & Gracia, R. (2007). Winter barley performance under different cropping and tillage systems in semiarid Aragon (NE Spain). European Journal of Agronomy, 26(1), 54-63. doi:10.1016/j.eja.2006.08.007Robinson, D. A., Campbell, C. S., Hopmans, J. W., Hornbuckle, B. K., Jones, S. B., Knight, R., … Wendroth, O. (2008). Soil Moisture Measurement for Ecological and Hydrological Watershed-Scale Observatories: A Review. Vadose Zone Journal, 7(1), 358-389. doi:10.2136/vzj2007.0143Czarnomski, N. M., Moore, G. W., Pypker, T. G., Licata, J., & Bond, B. J. (2005). Precision and accuracy of three alternative instruments for measuring soil water content in two forest soils of the Pacific Northwest. Canadian Journal of Forest Research, 35(8), 1867-1876. doi:10.1139/x05-121Lidón, A., Ramos, C., & Rodrigo, A. (1999). Comparison of drainage estimation methods in irrigated citrus orchards. Irrigation Science, 19(1), 25-36. doi:10.1007/s002710050068Jakubínský, J., Pechanec, V., Procházka, J., & Cudlín, P. (2019). Modelling of Soil Erosion and Accumulation in an Agricultural Landscape—A Comparison of Selected Approaches Applied at the Small Stream Basin Level in the Czech Republic. Water, 11(3), 404. doi:10.3390/w11030404Marinov, I., & Marinov, A. M. (2014). A Coupled Mathematical Model to Predict the Influence of Nitrogen Fertilization on Crop, Soil and Groundwater Quality. Water Resources Management, 28(15), 5231-5246. doi:10.1007/s11269-014-0664-5Porter, J. R. (1993). AFRCWHEAT2: A model of the growth and development of wheat incorporating responses to water and nitrogen. European Journal of Agronomy, 2(2), 69-82. doi:10.1016/s1161-0301(14)80136-6ADDISCOTT, T. M., & WAGENET, R. J. (1985). Concepts of solute leaching in soils: a review of modelling approaches. Journal of Soil Science, 36(3), 411-424. doi:10.1111/j.1365-2389.1985.tb00347.xBastiaanssen, W. G. M., Allen, R. G., Droogers, P., D’Urso, G., & Steduto, P. (2007). Twenty-five years modeling irrigated and drained soils: State of the art. Agricultural Water Management, 92(3), 111-125. doi:10.1016/j.agwat.2007.05.013GREENWOOD, D. J., ZHANG, K., HILTON, H. W., & THOMPSON, A. J. (2009). Opportunities for improving irrigation efficiency with quantitative models, soil water sensors and wireless technology. The Journal of Agricultural Science, 148(1), 1-16. doi:10.1017/s0021859609990487Hutson, J. L., & Wagenet, R. J. (1991). Simulating nitrogen dynamics in soils using a deterministic model. Soil Use and Management, 7(2), 74-78. doi:10.1111/j.1475-2743.1991.tb00853.xRamos, C., & Carbonell, E. A. (1991). Nitrate leaching and soil moisture prediction with the LEACHM model. Fertilizer Research, 27(2-3), 171-180. doi:10.1007/bf01051125Lidón, A., Ramos, C., Ginestar, D., & Contreras, W. (2013). Assessment of LEACHN and a simple compartmental model to simulate nitrogen dynamics in citrus orchards. Agricultural Water Management, 121, 42-53. doi:10.1016/j.agwat.2013.01.008Smith, W. N., Reynolds, W. D., Jong, R., Clemente, R. S., & Topp, E. (1995). Water Flow through Intact Soil Columns: Measurement and Simulation Using LEACHM. Journal of Environmental Quality, 24(5), 874-881. doi:10.2134/jeq1995.00472425002400050013xAkinremi, O. O., Jame, Y. W., Campbell, C. A., Zentner, R. P., Chang, C., & de Jong, R. (2005). Evaluation of LEACHMN under dryland conditions. I. Simulation of water and solute transport. Canadian Journal of Soil Science, 85(2), 223-232. doi:10.4141/s03-076Plaza-Bonilla, D., Álvaro-Fuentes, J., Hansen, N. C., Lampurlanés, J., & Cantero-Martínez, C. (2013). Winter cereal root growth and aboveground–belowground biomass ratios as affected by site and tillage system in dryland Mediterranean conditions. Plant and Soil, 374(1-2), 925-939. doi:10.1007/s11104-013-1926-3WALKLEY, A., & BLACK, I. A. (1934). AN EXAMINATION OF THE DEGTJAREFF METHOD FOR DETERMINING SOIL ORGANIC MATTER, AND A PROPOSED MODIFICATION OF THE CHROMIC ACID TITRATION METHOD. Soil Science, 37(1), 29-38. doi:10.1097/00010694-193401000-00003Topp, G. C., Davis, J. L., & Annan, A. P. (1980). Electromagnetic determination of soil water content: Measurements in coaxial transmission lines. Water Resources Research, 16(3), 574-582. doi:10.1029/wr016i003p00574Crank, J., & Nicolson, P. (1947). A practical method for numerical evaluation of solutions of partial differential equations of the heat-conduction type. Mathematical Proceedings of the Cambridge Philosophical Society, 43(1), 50-67. doi:10.1017/s0305004100023197CAMPBELL, G. S. (1974). A SIMPLE METHOD FOR DETERMINING UNSATURATED CONDUCTIVITY FROM MOISTURE RETENTION DATA. Soil Science, 117(6), 311-314. doi:10.1097/00010694-197406000-00001HUTSON, J. L., & CASS, A. (1987). A retentivity function for use in soil-water simulation models. Journal of Soil Science, 38(1), 105-113. doi:10.1111/j.1365-2389.1987.tb02128.xChilds, S. W., & Hanks, R. J. (1975). Model of Soil Salinity Effects on Crop Growth. Soil Science Society of America Journal, 39(4), 617-622. doi:10.2136/sssaj1975.03615995003900040016xNimah, M. N., & Hanks, R. J. (1973). Model for Estimating Soil Water, Plant, and Atmospheric Interrelations: I. Description and Sensitivity. Soil Science Society of America Journal, 37(4), 522-527. doi:10.2136/sssaj1973.03615995003700040018xJung, Y. W., Oh, D.-S., Kim, M., & Park, J.-W. (2009). Calibration of LEACHN model using LH-OAT sensitivity analysis. Nutrient Cycling in Agroecosystems, 87(2), 261-275. doi:10.1007/s10705-009-9337-9Lagarias, J. C., Reeds, J. A., Wright, M. H., & Wright, P. E. (1998). Convergence Properties of the Nelder--Mead Simplex Method in Low Dimensions. SIAM Journal on Optimization, 9(1), 112-147. doi:10.1137/s1052623496303470J. D. Jabro, J. M. Jemison, Jr., L. L. Lengnick, R. H. Fox, & D. D. Fritton. (1993). Field Validation and Comparison of LEACHM and NCSWAP Models for Predicting Nitrate Leaching. Transactions of the ASAE, 36(6), 1651-1657. doi:10.13031/2013.28508Jemison, J. M., Jabro, J. D., & Fox, R. H. (1994). Evaluation of LEACHM: I. Simulation of Drainage, Bromide Leaching, and Corn Bromide Uptake. Agronomy Journal, 86(5), 843-851. doi:10.2134/agronj1994.00021962008600050018xGasch, C. K., Brown, D. J., Brooks, E. S., Yourek, M., Poggio, M., Cobos, D. R., & Campbell, C. S. (2017). A pragmatic, automated approach for retroactive calibration of soil moisture sensors using a two-step, soil-specific correction. Computers and Electronics in Agriculture, 137, 29-40. doi:10.1016/j.compag.2017.03.018Plaza-Bonilla, D., Cantero-Martínez, C., Bareche, J., Arrúe, J. L., Lampurlanés, J., & Álvaro-Fuentes, J. (2017). Do no-till and pig slurry application improve barley yield and water and nitrogen use efficiencies in rainfed Mediterranean conditions? Field Crops Research, 203, 74-85. doi:10.1016/j.fcr.2016.12.008Parsinejad, M., & Feng, Y. (2003). Field evaluation and comparison of two models for simulation of soil-water dynamics. 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    An Accuracy Assessment of Long Term Soil Moisture Monitoring in Texas

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    Long-term soil moisture monitoring sites are a source of data both for drought forecasting and hydrological and land surface modeling validation. Uncertainties in soil moisture monitoring data are not well documented and more knowledge can improve the interpretations based on these data. Texas has 23 locations with long-term soil moisture monitoring, supported by the Soil Climate Analysis Network (SCAN) and the U.S. Climate Reference Network. Both networks use Stevens Water HydraProbes for measuring soil moisture and one manufacturer-provided calibration equation for all locations. The Texas SCAN sites contain soils with vertic properties and soils with large texture discontinuities with depth, which may create distinct sources of uncertainties in soil moisture measurement. The objectives of this study were to 1) compare the default calibration to soil specific calibrations made in the lab and in-situ, 2) assess temporal and spatial uncertainties associated with using the HydraProbe, and 3) report errors and recommend methods for reducing uncertainty in SCAN data. Calibration equations were developed in the laboratory and in-situ for an Alfisol and a Vertisol. These two soils were also monitored over 18 months to 1 m depth with HydraProbes and a neutron moisture meter. Additionally, nine SCAN locations were sampled at three soil moisture conditions, field capacity, very dry and somewhere in between. Results showed root mean squared errors (RMSE) of 0.077, 0.051, and 0.035 m3m-3 for the default, lab, and in-situ calibrations for the Alfisol and 0.167, 0.077, and 0.045 m3m-3 for the Vertisol. The data varied from 0.045 to 0.174 m3m-3 RMSE and 0.004 to 0.120 m3m-3 bias for individual SCAN sites. Soil properties of clay, pH, CEC, exchangeable cations, or bulk density did not explain trends in SCAN errors; however, a positive linear relationship between SCAN prediction errors and soil moisture was found. This study uniquely documents temporal and spatial variability in long-term soil monitoring networks in Texas and provides some documentation of errors to modelers and land use planners using soil moisture data for model evaluation

    Sistema integrado para a monitorização de rega no cultivo de Rosmarinus officinalis, no âmbito da agricultura de precisão

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    Diversos estudos abordam o tema da importância do aumento da eficiência de rega perante um cenário de progressiva escassez de água e uma competição cada vez maior por este recurso, entre a agricultura e o consumo urbano. Baseado no conhecimento atual, foi desenvolvido um sistema integrado de monitorização de rega de plantas em vaso ao ar livre, que utiliza a informação de sensores de humidade do substrato e os dados do clima obtidos numa estação meteorológica, para a determinação da evapotranspiração de Rosmarinus officinalis. Com estes dados, determinou-se uma variável designada por Kch que permite estimar a evapotranspiração das plantas, e consequentemente a necessidade de rega, a partir da evapotranspiração de referência (Eto). Através dos dados obtidos ao longo do ensaio, foi possível perceber qual a percentagem de humidade do substrato que mais beneficiou a absorção de água por parte das plantas.Several studies address the issue of the importance of increasing irrigation efficiency in a scenario of progressive water scarcity, and increasing competition for this resource, between agriculture and urban consumption. Based on current knowledge, an integrated system for monitoring watering potted plants outdoors has been developed, which uses information from substrate moisture sensors and climate data obtained from weather station to determine the evapotranspiration of Rosmarinus officinalis. With these data, it was determined a variable called Kch that allows estimating the evapotranspiration of the plants, and consequently the need for irrigation, from the reference evapotranspiration (Eto). Through the data obtained throughout the test, it was possible to understand which percentage of moisture in the substrate that most benefited the water absorption by the plants

    Social work with airports passengers

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    Social work at the airport is in to offer to passengers social services. The main methodological position is that people are under stress, which characterized by a particular set of characteristics in appearance and behavior. In such circumstances passenger attracts in his actions some attention. Only person whom he trusts can help him with the documents or psychologically

    A cumulative index to the 1976 issues of a continuing bibliography on Aerospace Medicine and Biology

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    This publication is a cumulative index to the abstracts contained in Supplements 151 through 162 of Aerospace Medicine and Biology: A continuing bibliography. It includes three indexes - subject, personal author, and corporate source
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