Tendencias mundiales en la aplicación de modelos hidrológicos en el estudio y planificación de la agricultura: una revisión

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dc.contributor.advisorPortela Ramírez, Albert Johan
dc.contributor.authorHuertas Beltrán, Ruddy Lizette
dc.contributor.corporatenameUniversidad Santo Tomásspa
dc.contributor.orcidhttps://orcid.org/ 0000-0001-6246-8010spa
dc.coverage.campusCRAI-USTA Duadspa
dc.date.accessioned2022-06-16T21:54:35Z
dc.date.available2022-06-16T21:54:35Z
dc.date.issued2022-06-16
dc.descriptionLos modelos hidrológicos son herramientas que contribuyen a comprender, explorar y analizar los procesos de ocurrencia y obtener opciones de gestión sostenibles. Los resultados que generan estos modelos constituyen una información muy valiosa para la toma de decisiones estratégicas a futuro o en tiempo real. El objetivo de esta revisión es identificar las tendencias de los modelos hidrológicos asociados al estudio y planificación de la agricultura entre los años 2011 a 2021 a escala mundial. Se utilizó un método de revisión sistemática de literatura, que incluyó un índice de frecuencia de citación mediante cuartiles (Q) (Ome y Zafra, 2018). Se evidenció a Estados Unidos a nivel mundial como país tendencia de la aplicación de los modelos hidrológicos en el estudio y planificación de la agricultura, seguido por China y México. Además, se pudo identificar que el modelo RZWQM2 fue el de mayor tendencia, debido a su integralidad al evaluar eficazmente el impacto de las prácticas de gestión agrícola en la producción de cultivos y la calidad del agua y del suelo. Finalmente, esta revisión servirá como insumo para investigaciones futuras de entes gubernamentales e instituciones ambientales para la elección de herramientas de gestión del recurso.spa
dc.description.abstractHydrological models are tools that help us understand, explore and analyze the processes of occurrence and obtain sustainable management options. The results generated by these models constitute very valuable information for making strategic decisions in the future or in real time. The objective of this review is to identify trends in hydrological models associated with the study and planning of agriculture between the years 2011 to 2021 on a global scale. A systematic literature review method was used, which included a citation frequency index by quartiles (Q). The United States was evidenced worldwide as a trend country for the application of hydrological models in the study and planning of agriculture, followed by China and Mexico. In addition, it was possible to identify that the RZWQM2 model was the one with the greatest trend, due to its comprehensiveness when effectively evaluating the impact of agricultural management practices on crop production and the quality of water and soil. Finally, this review will serve as input for future research by government entities and environmental institutions for the choice of resource management tools.spa
dc.description.degreelevelEspecializaciónspa
dc.description.degreenameEspecialista en Ordenamiento y Gestión Integral de Cuencas Hidrográficasspa
dc.format.mimetypeapplication/pdfspa
dc.identifier.citationHuertas Beltrán, R. (2022). Tendencias mundiales en la aplicación de modelos hidrológicos en el estudio y planificación de la agricultura: una revisión. [Trabajo de grado, Universidad Santo Tomás]: Repositorio institucional.spa
dc.identifier.instnameinstname:Universidad Santo Tomásspa
dc.identifier.reponamereponame:Repositorio Institucional Universidad Santo Tomásspa
dc.identifier.repourlrepourl:https://repository.usta.edu.cospa
dc.identifier.urihttp://hdl.handle.net/11634/45180
dc.language.isospaspa
dc.publisherUniversidad Santo Tomásspa
dc.publisher.facultyFacultad de Ciencias y Tecnologíasspa
dc.publisher.programEspecialización Ordenamiento y Gestión Integral de Cuencas Hidrográficasspa
dc.relation.referencesAdger, W. N. (2006). Vulnerability. Global environmental change, 16(3), 268-281.spa
dc.relation.referencesAhuja, L. R., Ma, L., Lascano, R. J., Saseendran, S. A., Fang, Q. X., Nielsen, D. C., ... & Colaizzi, P. D. (2014). Syntheses of the current model applications for managing water and needs for experimental data and model improvements to enhance these applications. Practical applications of agricultural system models to optimize the use of limited water, 5, 399-437.spa
dc.relation.referencesAhuja, L., Rojas, K. W., & Hanson, J. D. (Eds.). (2000). Root zone water quality model: modelling management effects on water quality and crop production. Water Resources Publication.spa
dc.relation.referencesAllen, R. G., Pereira, L. S., Raes, D., & Smith, M. (1998). Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56. Fao, Rome, 300(9), D05109.spa
dc.relation.referencesBenjamin, J. G., Ahuja, L. R., & Allmaras, R. R. (1996). Modelling corn rooting patterns and their effects on water uptake and nitrate leaching. Plant and Soil, 179(2), 223-232.spa
dc.relation.referencesBowen, W., & Jaramillo, R. (2001). Modelos de dinámica de nutrientes en el suelo y en la planta. In Congreso Sociedad Ecuatoriana de la Ciencia del Suelo [CD-ROM archivo]. Sociedad Ecuatoriana de la ciencia del Suelo (7: 2000 oct. 19-20 octubre: Quito).spa
dc.relation.referencesBrooks, N., Adger, W. N., & Kelly, P. M. (2005). The determinants of vulnerability and adaptive capacity at the national level and the implications for adaptation. Global environmental change, 15(2), 151-163.spa
dc.relation.referencesBruinsma, J. (2009, June). The resource outlook to 2050: by how much do land, water and crop yields need to increase by 2050. In Expert meeting on how to feed the world in (Vol. 2050, pp. 24-26).spa
dc.relation.referencesBruins, H. J., Bithan-Guedj, H., & Svoray, T. (2019). GIS-based hydrological modelling to assess runoff yields in ancient-agricultural terraced wadi fields (central Negev desert). Journal of arid environments, 166, 91-107.spa
dc.relation.referencesCandelaria Martínez, B., Ruiz Rosado, O., Gallardo López, F., Pérez Hernández, P., Martínez Becerra, Á., & Vargas Villamil, L. (2011). Aplicación de modelos de simulación en el estudio y planificación de la agricultura, una revisión. Tropical and subtropical agroecosystems, 14(3), 999-1010.spa
dc.relation.referencesChallinor, A. J., Ewert, F., Arnold, S., Simelton, E., & Fraser, E. (2009). Crops and climate change: progress, trends, and challenges in simulating impacts and informing adaptation. Journal of experimental botany, 60(10), 2775-2789.spa
dc.relation.referencesChallinor, A. J., Simelton, E. S., Fraser, E. D., Hemming, D., & Collins, M. (2010). Increased crop failure due to climate change: assessing adaptation options using models and socio-economic data for wheat in China. Environmental Research Letters, 5(3), 034012.spa
dc.relation.referencesConnolly, R. D. (1998). Modelling effects of soil structure on the water balance of soil–crop systems: a review. Soil and Tillage Research, 48(1-2), 1-19. crop yield, Wageningen, 189 p.spa
dc.relation.referencesEvett, S. R., & Tolk, J. A. (2009). Introduction: Can water use efficiency be modeled well enough to impact crop management?. Agronomy Journal, 101(3), 423-425.spa
dc.relation.referencesFraser, E. D., Simelton, E., Termansen, M., Gosling, S. N., & South, A. (2013). “Vulnerability hotspots”: Integrating socio-economic and hydrological models to identify where cereal production may decline in the future due to climate change induced drought. Agricultural and Forest Meteorology, 170, 195-205.spa
dc.relation.referencesGodfray, H. C. J., Beddington, J. R., Crute, I. R., Haddad, L., Lawrence, D., Muir, J. F., ... & Toulmin, C. (2010). Food security: the challenge of feeding 9 billion people. science, 327(5967), 812-818.spa
dc.relation.referencesGosling, S. N., & Arnell, N. W. (2011). Simulating current global river runoff with a global hydrological model: model revisions, validation, and sensitivity analysis. Hydrological Processes, 25(7), 1129-1145spa
dc.relation.referencesGosling, S. N., Bretherton, D., Haines, K., & Arnell, N. W. (2010). Global hydrology modelling and uncertainty: running multiple ensembles with a campus grid. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 368(1926), 4005-4021.cspa
dc.relation.referencesGosling, S. N., Taylor, R. G., Arnell, N. W., & Todd, M. C. (2011). A comparative analysis of projected impacts of climate change on river runoff from global and catchment-scale hydrological models. Hydrology and Earth System Sciences, 15(1), 279-294.spa
dc.relation.referencesGuía para el uso eficiente y ahorro del agua: Una visión colectiva para el uso sostenible y responsable del agua [recurso electrónico] / Dirección de Gestión Integral de Recurso Hídrico. Edición y textos: Moreno Barco, Diana Marcela; Callejas Moncaleano, Diana Carolina. ---- Bogotá, D. C.: Colombia. Ministerio de Ambiente y Desarrollo Sostenible, 2018.spa
dc.relation.referencesHaddeland, I., Clark, D. B., Franssen, W., Ludwig, F., Voß, F., Arnell, N. W., ... & Yeh, P. (2011). Multimodel estimate of the global terrestrial water balance: Setup and first results. Journal of Hydrometeorology, 12(5), 869-884.spa
dc.relation.referencesJaggard, K. W., Qi, A., & Ober, E. S. (2010). Possible changes to arable crop yields by 2050. Philosophical Transactions of the Royal Society B: Biological Sciences, 365(1554), 2835-2851.spa
dc.relation.referencesJeong, H., & Adamowski, J. (2016). A system dynamics based socio-hydrological model for agricultural wastewater reuse at the watershed scale. Agricultural Water Management, 171, 89-107.spa
dc.relation.referencesJones, J. W., Hoogenboom, G., Porter, C. H., Boote, K. J., Batchelor, W. D., Hunt, L. A., ... & Ritchie, J. T. (2003). The DSSAT cropping system model. European journal of agronomy, 18(3-4), 235-265.spa
dc.relation.referencesJones, J. W., Tsuji, G. Y., Hoogenboom, G., Hunt, L. A., Thornton, P. K., Wilkens, P. W., ... & Singh, U. (1998). Decision support system for agrotechnology transfer: DSSAT v3. In Understanding options for agricultural production (pp. 157-177). Springer, Dordrecht.spa
dc.relation.referencesKanda, E. K., Mabhaudhi, T., & Senzanje, A. (2018). Coupling hydrological and crop models for improved agricultural water management–A review. Bulgarian Journal of Agricultural Science, 24(3), 380-390.spa
dc.relation.referencesKrysanova, V., Müller-Wohlfeil, D. I., & Becker, A. (1998). Development and test of a spatially distributed hydrological/water quality model for mesoscale watersheds. Ecological modelling, 106(2-3), 261-289.spa
dc.relation.referencesKrysanova, V., Wechsung, F., Arnold, J., Srinivasan, R., Williams, J., 2000. SWIM - Soil and Water Integrated Model. User Manual. PIK Report 69, Potsdam Institute for D. Sietz et al. Agricultural Systems 193 (2021) 10318311 Climate Impact Research, Potsdam, Germany.spa
dc.relation.referencesLobell, D. B., & Field, C. B. (2007). Global scale climate–crop yield relationships and the impacts of recent warming. Environmental research letters, 2(1), 014002.spa
dc.relation.referencesLong, S. P., Ainsworth, E. A., Leakey, A. D., & Morgan, P. B. (2005). Global food insecurity. Treatment of major food crops with elevated carbon dioxide or ozone under large-scale fully open-air conditions suggests recent models may have overestimated future yields. Philosophical Transactions of the Royal Society B: Biological Sciences, 360(1463), 2011-2020.spa
dc.relation.referencesMa, L., Hoogenboom, G., Ahuja, L. R., Ascough Ii, J. C., & Saseendran, S. A. (2006). Evaluation of the RZWQM-CERES-Maize hybrid model for maize production. Agricultural Systems, 87(3), 274-295.spa
dc.relation.referencesMinisterio de Ambiente, Vivienda y Desarrollo Territorial -MAVDT. (2010). Política Nacional para la Gestión Integral del Recurso Hídrico. Bogotá: Imprenta Nacional.spa
dc.relation.referencesNousiainen, R., Warsta, L., Turunen, M., Huitu, H., Koivusalo, H., & Pesonen, L. (2015). Analyzing subsurface drain network performance in an agricultural monitoring site with a three-dimensional hydrological model. Journal of Hydrology, 529, 82-93spa
dc.relation.referencesOme Barrera, Ó., & Zafra Mejía, C. (2018). Key factors in bioremediation processes for wastewater treatment. A review.. Revista UDCA Actualidad & Divulgación Científica, 21(2), 573-585.spa
dc.relation.referencesPatt, A., Suarez, P., & Gwata, C. (2005). Effects of seasonal climate forecasts and participatory workshops among subsistence farmers in Zimbabwe. Proceedings of the National Academy of Sciences, 102(35), 12623-12628.spa
dc.relation.referencesPsomas, A., Dagalaki, V., Panagopoulos, Y., Konsta, D., & Mimikou, M. (2016). Sustainable agricultural water management in Pinios River basin using remote sensing and hydrologic modeling. Procedia engineering, 162, 277-283.spa
dc.relation.referencesRaes, D., Steduto, P., Hsiao, T. C., & Fereres, E. (2009). AquaCrop—the FAO crop model to simulate yield response to water: II. Main algorithms and software description. Agronomy Journal, 101(3), 438-447.spa
dc.relation.referencesRoyal Society, 2008. Ground-level ozone in the 21st century: future trends, impacts and policy implications. R. Soc. Sci. Policy Rep. 15 (08), 1–148.spa
dc.relation.referencesSalo, H., Warsta, L., Turunen, M., Paasonen-Kivekäs, M., Nurminen, J., & Koivusalo, H. (2015). Development and application of a solute transport model to describe field-scale nitrogen processes during autumn rains. Acta Agriculturae Scandinavica, Section B—Soil & Plant Science, 65(sup1), 30-43.spa
dc.relation.referencesShaffer, M. J., & Gupta, S. C. (1981). Hydrosalinity models and field validation. In Modeling wastewater renovation (pp. 136-181). John Wiley New York, NY.spa
dc.relation.referencesShuttleworth, W. J., & Wallace, J. S. (1985). Evaporation from sparse crops‐an energy combination theory. Quarterly Journal of the Royal Meteorological Society, 111(469), 839-855.spa
dc.relation.referencesSietz, D., Conradt, T., Krysanova, V., Hattermann, F. F., & Wechsung, F. (2021). The Crop Generator: Implementing crop rotations to effectively advance eco-hydrological modelling. Agricultural Systems, 193, 103183.spa
dc.relation.referencesSimunek, J. I. R. K. A., & Van Genuchten, M. (1994). The chain_2d code for simulating two-dimensional movement of water flow, heat, and multiple solutes in variably-saturated porous media, version 1.1 USSL research report no. 136. Laboratory publication.spa
dc.relation.referencesSimunek, J. I. R. K. A., Van Genuchten, M. T., & Sejna, M. (2006). The HYDRUS software package for simulating the two-and three-dimensional movement of water, heat, and multiple solutes in variably-saturated media. Technical manual, 1.spa
dc.relation.referencesSimunek, J., Van Genuchten, M. T., & Sejna, M. (2005). The HYDRUS-1D software package for simulating the one-dimensional movement of water, heat, and multiple solutes in variably-saturated media. University of California-Riverside Research Reports, 3, 1-240.spa
dc.relation.referencesSitch, S., Cox, P. M., Collins, W. J., & Huntingford, C. (2007). Indirect radiative forcing of climate change through ozone effects on the land-carbon sink. Nature, 448(7155), 791-794.spa
dc.relation.referencesSmit, B., & Skinner, M. W. (2002). Adaptation options in agriculture to climate change: a typology. Mitigation and adaptation strategies for global change, 7(1), 85-114.spa
dc.relation.referencesSun, M., Zhang, X., Huo, Z., Feng, S., Huang, G., & Mao, X. (2016). Uncertainty and sensitivity assessments of an agricultural–hydrological model (RZWQM2) using the GLUE method. Journal of hydrology, 534, 19-30.spa
dc.relation.referencesTester, M., & Langridge, P. (2010). Breeding technologies to increase crop production in a changing world. Science, 327(5967), 818-822.spa
dc.relation.referencesThomas, D. S., Twyman, C., Osbahr, H., & Hewitson, B. (2007). Adaptation to climate change and variability: farmer responses to intra-seasonal precipitation trends in South Africa. Climatic change, 83(3), 301-322.spa
dc.relation.referencesTodorovic, M., Albrizio, R., Zivotic, L., Saab, M. T. A., Stöckle, C., & Steduto, P. (2009). Assessment of AquaCrop, CropSyst, and WOFOST models in the simulation of sunflower growth under different water regimes. Agronomy Journal, 101(3), 509-521.spa
dc.relation.referencesTurunen, M., Warsta, L., Paasonen-Kivekäs, M., Nurminen, J., Myllys, M., Alakukku, L., ... & Koivusalo, H. (2013). Modeling water balance and effects of different subsurface drainage methods on water outflow components in a clayey agricultural field in boreal conditions. Agricultural Water Management, 121, 135-spa
dc.relation.referencesVan Diepen, C. V., Wolf, J., Van Keulen, H., & Rappoldt, C. (1989). WOFOST: a simulation model of crop production. Soil use and management, 5(1), 16-24.spa
dc.relation.referencesVereecken, H., Schnepf, A., Hopmans, J. W., Javaux, M., Or, D., Roose, T., ... & Young, I. M. (2016). Modeling soil processes: Review, key challenges, and new perspectives. Vadose zone journal, 15(5).spa
dc.relation.referencesWang, D., Yates, S. R., Simunek, J., & Genuchten, M. T. V. (1997). Solute transport in simulated conductivity fields under different irrigations. Journal of irrigation and drainage engineering, 123(5), 336-343.spa
dc.relation.referencesWang, X., Williams, J. R., Gassman, P. W., Baffaut, C., Izaurralde, R. C., Jeong, J., & Kiniry, J. R. (2012). EPIC and APEX: Model use, calibration, and validation. Transactions of the ASABE, 55(4), 1447-1462.spa
dc.relation.referencesWarsta, L., Karvonen, T., Koivusalo, H., Paasonen-Kivekäs, M., & Taskinen, A. (2013). Simulation of water balance in a clayey, subsurface drained agricultural field with three-dimensional FLUSH model. Journal of hydrology, 476, 395-409.spa
dc.relation.referencesWatts, M. J., & Bohle, H. G. (1993). The space of vulnerability: the causal structure of hunger and famine. Progress in human geography, 17(1), 43-67.spa
dc.relation.referencesWilliams, J. R., Jones, C. A., Gassman, P. W., & Hauck, L. M. (1995). Simulation of animal waste management with APEX. Innovations and New Horizons in Livestock and Poultry Manure Management, 1, 22-26.spa
dc.relation.referencesXi, M., Lu, D., Gui, D., Qi, Z., & Zhang, G. (2017). Calibration of an agricultural-hydrological model (RZWQM2) using surrogate global optimization. Journal of Hydrology, 544, 456-466.spa
dc.rightsAtribución-NoComercial-SinDerivadas 2.5 Colombia*
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.rights.coarhttp://purl.org/coar/access_right/c_abf2
dc.rights.localAbierto (Texto Completo)spa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.5/co/*
dc.subject.keywordhydrological modelsspa
dc.subject.keywordcrop modelsspa
dc.subject.keywordagriculturespa
dc.subject.lembConservación de recursos naturalesspa
dc.subject.lembHidrometríaspa
dc.subject.lembAgricultura Abastecimiento de aguaspa
dc.subject.proposalmodelos hidrológicosspa
dc.subject.proposalmodelos de cultivosspa
dc.subject.proposalagriculturaspa
dc.titleTendencias mundiales en la aplicación de modelos hidrológicos en el estudio y planificación de la agricultura: una revisiónspa
dc.typebachelor thesis
dc.type.coarhttp://purl.org/coar/resource_type/c_7a1f
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.driveinfo:eu-repo/semantics/bachelorThesis
dc.type.localTesis de pregradospa
dc.type.versioninfo:eu-repo/semantics/acceptedVersion

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