Estimación de la oferta hídrica para la planificación de cultivos en una cuenca hidrográfica de la Orinoquía colombiana
ilustraciones, graficas, mapas
- Autores:
-
Gallo Gordillo, Oscar Javier
- Tipo de recurso:
- Fecha de publicación:
- 2022
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/82003
- Palabra clave:
- 630 - Agricultura y tecnologías relacionadas::633 - Cultivos de campo y de plantación
Precipitación
Orinoquia
Uso del suelo
Precipitation
Soil moisture
Orinoquia
Land uses
Humedad del suelo
Recursos hídricos
Uso de la tierra
Soil moisture
Water resources
Land use
- Rights
- openAccess
- License
- Atribución-NoComercial-SinDerivadas 4.0 Internacional
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network_acronym_str |
UNACIONAL2 |
network_name_str |
Universidad Nacional de Colombia |
repository_id_str |
|
dc.title.spa.fl_str_mv |
Estimación de la oferta hídrica para la planificación de cultivos en una cuenca hidrográfica de la Orinoquía colombiana |
dc.title.translated.eng.fl_str_mv |
Estimation of water supply for crop planning in a hydrographic basin of the Colombian Orinoquía |
title |
Estimación de la oferta hídrica para la planificación de cultivos en una cuenca hidrográfica de la Orinoquía colombiana |
spellingShingle |
Estimación de la oferta hídrica para la planificación de cultivos en una cuenca hidrográfica de la Orinoquía colombiana 630 - Agricultura y tecnologías relacionadas::633 - Cultivos de campo y de plantación Precipitación Orinoquia Uso del suelo Precipitation Soil moisture Orinoquia Land uses Humedad del suelo Recursos hídricos Uso de la tierra Soil moisture Water resources Land use |
title_short |
Estimación de la oferta hídrica para la planificación de cultivos en una cuenca hidrográfica de la Orinoquía colombiana |
title_full |
Estimación de la oferta hídrica para la planificación de cultivos en una cuenca hidrográfica de la Orinoquía colombiana |
title_fullStr |
Estimación de la oferta hídrica para la planificación de cultivos en una cuenca hidrográfica de la Orinoquía colombiana |
title_full_unstemmed |
Estimación de la oferta hídrica para la planificación de cultivos en una cuenca hidrográfica de la Orinoquía colombiana |
title_sort |
Estimación de la oferta hídrica para la planificación de cultivos en una cuenca hidrográfica de la Orinoquía colombiana |
dc.creator.fl_str_mv |
Gallo Gordillo, Oscar Javier |
dc.contributor.advisor.none.fl_str_mv |
Loaiza Usuga, Juan Carlos Bernal Riobo, Jaime Humberto |
dc.contributor.author.none.fl_str_mv |
Gallo Gordillo, Oscar Javier |
dc.subject.ddc.spa.fl_str_mv |
630 - Agricultura y tecnologías relacionadas::633 - Cultivos de campo y de plantación |
topic |
630 - Agricultura y tecnologías relacionadas::633 - Cultivos de campo y de plantación Precipitación Orinoquia Uso del suelo Precipitation Soil moisture Orinoquia Land uses Humedad del suelo Recursos hídricos Uso de la tierra Soil moisture Water resources Land use |
dc.subject.proposal.spa.fl_str_mv |
Precipitación Orinoquia Uso del suelo Precipitation |
dc.subject.proposal.eng.fl_str_mv |
Soil moisture Orinoquia Land uses |
dc.subject.unesco.spa.fl_str_mv |
Humedad del suelo Recursos hídricos Uso de la tierra |
dc.subject.unesco.eng.fl_str_mv |
Soil moisture Water resources Land use |
description |
ilustraciones, graficas, mapas |
publishDate |
2022 |
dc.date.accessioned.none.fl_str_mv |
2022-08-22T21:45:00Z |
dc.date.available.none.fl_str_mv |
2022-08-22T21:45:00Z |
dc.date.issued.none.fl_str_mv |
2022-08-20 |
dc.type.spa.fl_str_mv |
Trabajo de grado - Maestría |
dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/masterThesis |
dc.type.version.spa.fl_str_mv |
info:eu-repo/semantics/acceptedVersion |
dc.type.content.spa.fl_str_mv |
Text |
dc.type.redcol.spa.fl_str_mv |
http://purl.org/redcol/resource_type/TM |
status_str |
acceptedVersion |
dc.identifier.uri.none.fl_str_mv |
https://repositorio.unal.edu.co/handle/unal/82003 |
dc.identifier.instname.spa.fl_str_mv |
Universidad Nacional de Colombia |
dc.identifier.reponame.spa.fl_str_mv |
Repositorio Institucional Universidad Nacional de Colombia |
dc.identifier.repourl.spa.fl_str_mv |
https://repositorio.unal.edu.co/ |
url |
https://repositorio.unal.edu.co/handle/unal/82003 https://repositorio.unal.edu.co/ |
identifier_str_mv |
Universidad Nacional de Colombia Repositorio Institucional Universidad Nacional de Colombia |
dc.language.iso.spa.fl_str_mv |
spa |
language |
spa |
dc.relation.indexed.spa.fl_str_mv |
RedCol LaReferencia |
dc.relation.references.spa.fl_str_mv |
AbdAllah, A. M., Mashaheet, A. M. and Burkey, K. O. (2021). Super absorbent polymers mitigate drought stress in corn (Zea mays L.) grown under rainfed conditions. Agricultural Water Management, 254(December 2020), 106946. https://doi.org/10.1016/j.agwat.2021.106946 Alan, A. T. M., Rahman, M. S. and Sadaat, A. H. M. (2014). Markov Chain Analysis of Weekly Rainfall Data for Predicting Agricultural Drought. In Computational Intelligence Techniques in Earth and Environmental Sciences (pp. 109–128). Allen, R. G., Pereira, L. S., Raes, D. and Smith, M. (1998). Evapotranspiración del cultivo, Guías para la determinación de los requerimientos de agua de los cultivos. FAO - Food and Agriculture Organization of the United Nations, 56 Almansa, E. F. (2006a). Manejo del recurso hídrico para el cultivo de la soya en la Orinoquia Colombiana. In Soya (Glycine max (L.) Merril) Alternativa para los sistemas de produccion para los sistemas de produccion de la Orinoquia colombiana. (p. 224). Almansa, E. F. (2006b). Requerimientos hídricos del cultivo de soya en la Altillanura (p. 2). https://repository.agrosavia.co/handle/20.500.12324/13777 Amézquita, E. (1999). Propiedades físicas de los suelos de los Llanos Orientales y sus requerimientos de labranza. PALMAS, 20(1), 145–174. http://hdl.handle.net/20.500.12324/15962 Amézquita, E., Indupalapati, R. I. M., Hoyos, P., Diego, M., Luis Fernando, C. and Jaime, B. (2007). Development of an arable layer: A key concept for better management of infertile tropical savanna soils. Amézquita, E., Rao, I. M., Rivera, M., Corrales, I. I. and Jaime H. Bernal. (2013). Sistemas Agropastoriles: Un Enfoque Integrado para el Manejo Sostenible de Oxisoles de los Llanos Orientales de Colombia. Arango, C., Dorado, J., Guzmán, D. and Ruíz, J. (2015). Variabilidad climática de la precipitación en Colombia asociada al ciclo el niño, la niña – oscilación del sur (ENSO) [Archivo PDF]. In IDEAM (pp. 103–111) Armenteras, D., Meza, M. C., González, T. M., Oliveras, I., Balch, J. K. and Retana, J. (2021). Fire threatens the diversity and structure of tropical gallery forests. Ecosphere, 12(1). https://doi.org/10.1002/ecs2.3347 Attanasio, A., Pasini, A. and Triacca, U. (2013). Granger Causality Analyses for Climatic Attribution. Atmospheric and Climate Sciences, 03(04), 515–522. https://doi.org/10.4236/acs.2013.34054 Barrios-Perez, C., Okada, K., Varón, G. G., Ramirez-Villegas, J., Rebolledo, M. C. and Prager, S. D. (2021). How does El Niño Southern Oscillation affect rice-producing environments in central Colombia? Agricultural and Forest Meteorology, 306(April). https://doi.org/10.1016/j.agrformet.2021.108443 Bera, B., Shit, P. K., Sengupta, N., Saha, S. and Bhattacharjee, S. (2021). Trends and variability of drought in the extended part of Chhota Nagpur plateau (Singbhum Protocontinent), India applying SPI and SPEI indices. Environmental Challenges, 5(September), 100310. https://doi.org/10.1016/j.envc.2021.100310 Bergstrom, S., Lindstrom, G., Johansson, B., Persson, M. and Gardelin, M. (1997). hydrological model. Journal of Hydrology, 201, 272–288. Beven, K. (2012). Rainfall-runoff modelling. In Fluid Mechanics, Hydraulics, Hydrology and Water Resources for Civil Engineers. https://doi.org/10.1201/9780429423116-33 Blöschl, G., Bierkens, M. F. P., Chambel, A., Cudennec, C., Destouni, G., Fiori, A., Kirchner, J. W., McDonnell, J. J., Savenije, H. H. G., Sivapalan, M., Stumpp, C., Toth, E., Volpi, E., Carr, G., Lupton, C., Salinas, J., Széles, B., Viglione, A., Aksoy, H., … Zhang, Y. (2019). Twenty-three unsolved problems in hydrology (UPH)–a community perspective. Hydrological Sciences Journal, 64(10), 1141–1158. https://doi.org/10.1080/02626667.2019.1620507 Bradford, J. B., Schlaepfer, D. R., Lauenroth, W. K., Palmquist, K. A., Chambers, J. C., Maestas, J. D. and Campbell, S. B. (2019). Climate-driven shifts in soil temperature and moisture regimes suggest opportunities to enhance assessments of dryland resilience and resistance. Frontiers in Ecology and Evolution, 7(SEP), 1–16. https://doi.org/10.3389/fevo.2019.00358 Breuer, L., Huisman, J. A., Willems, P., Bormann, H., Bronstert, A., Croke, B. F. W., Frede, H. G., Gräff, T., Hubrechts, L., Jakeman, A. J., Kite, G., Lanini, J., Leavesley, G., Lettenmaier, D. P., Lindström, G., Seibert, J., Sivapalan, M. and Viney, N. R. (2009). Assessing the impact of land use change on hydrology by ensemble modeling (LUCHEM). I: Model intercomparison with current land use. Advances in Water Resources, 32(2), 129–146. https://doi.org/10.1016/j.advwatres.2008.10.003 Bustamante, C. (2019). Gran Libro de la Orinoquia Colombiana. Instituto de Investigación de Recursos Biológicos Alexander von Humboldt - Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH. http://repository.humboldt.org.co/handle/20.500.11761/35408 Caicedo, S., Campuzano, L. F., Hernández, A. C., Alfonso, H., Olarte, T. P., Pulido, S. X. and Jaramillo, C. A. (2012). Modelo productivo para el cultivo de maíz y soya en la Altillanura colombiana (Paquete Tecnológico). Siembra, 1–37. http://www.siembra.gov.co/siembra/GestionInnovacion2.aspx Caicedo, S. and Tibocha, Y. (2020). Corpoica Iraca 10: variedad de soya para suelos mejorados de altillanura plana, y vegas y vegones del piedemonte llanero. Corporación Colombiana de Investigación Agropecuaria (AGROSAVIA). In Editorial AGROSAVIA (p. 20 paginas). Caplan, J. S., Giménez, D., Hirmas, D. R., Brunsell, N. A., Blair, J. M. and Knapp, A. K. (2019). Decadal-scale shifts in soil hydraulic properties as induced by altered precipitation. Science Advances, 5(9), 1–10. https://doi.org/10.1126/sciadv.aau6635 CEPAL, DNP and BID. (2012). Valoración de daños y pérdidas. Ola invernal en Colombia, 2010-2011. [Archivo PDF] (p. 240). http://hdl.handle.net/11362/37958 Chapagain, R., Remenyi, T. A., Harris, R. M. B., Mohammed, C. L., Huth, N., Wallach, D., Rezaei, E. E. and Ojeda, J. J. (2022). Decomposing crop model uncertainty: A systematic review. Field Crops Research, 279(November 2021), 108448. https://doi.org/10.1016/j.fcr.2022.108448 Chen, Z. and Grasby, S. E. (2009). Impact of decadal and century-scale oscillations on hydroclimate trend analyses. Journal of Hydrology, 365(1–2), 122–133. https://doi.org/10.1016/j.jhydrol.2008.11.031 Chica, H., Peña Quiñones, A. J., Giraldo Jiménez, J. F., Obando Bonilla, D. and Riaño Herrera, N. M. (2014). SueMulador: Herramienta para la Simulación de Datos Faltantes en Series Climáticas Diarias de Zonas Ecuatoriales. Revista Facultad Nacional de Agronomía Medellín, 67(2), 7365–7373. https://doi.org/10.15446/rfnam.v67n2.44179 Chica Ramirez, H. A., Gómez Gil, L. F., Bravo Bastidas, J. J., Carbonell González, J. A. and Peña Quiñones, A. J. (2021). Site-specific intra-annual rainfall patterns: a tool for agricultural planning in the Colombian sugarcane production zone. Theoretical and Applied Climatology, 146(1–2), 543–554. https://doi.org/10.1007/s00704-021-03755-1 Choquet, P., Gabrielle, B., Chalhoub, M., Michelin, J., Sauzet, O., Scammacca, O., Garnier, P., Baveye, P. C. and Montagne, D. (2021). Comparison of empirical and process-based modelling to quantify soil-supported ecosystem services on the Saclay plateau (France). Ecosystem Services, 50(June). https://doi.org/10.1016/j.ecoser.2021.101332 Chow, V., Maidment, D. and Mays, L. (1994). Hidrología aplicada. In Hidrologia aplicada (p. 575 pp). http://bases.bireme.br/cgi-bin/wxislind.exe/iah/online/?IsisScript=iah/iah.xis&src=google&base=REPIDISCA&lang=p&nextAction=lnk&exprSearch=158911&indexSearch=ID%5Cnhttp://www.sidalc.net/cgi-bin/wxis.exe/?IsisScript=BINAI.xis&method=post&formato=2&cantidad= CIAT and CORMACARENA. (2017). Plan Regional Integral de Cambio Climático para la Orinoquía. Centro Internacional de Agricultura Tropical (CIAT), Cali, Colombia., No. 438. 438. CIAT, CORMACARENA, Corporinoquia and Ecopetrol. (2027). Plan Regional Integral de Cambio Climático para la Orinoquía - Resumen ejecutivo Cartilla. In Centro Internacional de Agricultura Tropical (CIAT) (Vol. 53, Issue 9). https://www.cambridge.org/core/product/identifier/CBO9781107415324A009/type/book_part Cook, B. G. and Schultze-Kraft, R. (2015). Botanical name changes - Nuisance or a quest for precision? Tropical Grasslands-Forrajes Tropicales, 3(1), 34–40. https://doi.org/10.17138/TGFT(3)34-40 Córdoba-Machado, S., Palomino-Lemus, R., Gámiz-Fortis, S. R., Castro-Díez, Y. and Esteban-Parra, M. J. (2015). Assessing the impact of El Niño Modoki on seasonal precipitation in Colombia. Global and Planetary Change, 124, 41–61. https://doi.org/10.1016/j.gloplacha.2014.11.003 CORMACARENA. (2018). Plan de ordenamiento y manejo de la cuenca hidrografica Rio Negro. In Corporación Para El Desarrollo Sostenible del Área Manejo Especial la Macarena. Consorcio POMCA Río Negro 2018 (Vol. 10, Issue 1, pp. 279–288). http://dx.doi.org/10.1053/j.gastro.2014.05.023%0Ahttps://doi.org/10.1016/j.gie.2018.04.013%0Ahttp://www.ncbi.nlm.nih.gov/pubmed/29451164%0Ahttp://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC5838726%250Ahttp://dx.doi.org/10.1016/j.gie.2013.07.022 Cornelissen, T., Diekkrüger, B. and Giertz, S. (2013). A comparison of hydrological models for assessing the impact of land use and climate change on discharge in a tropical catchment. Journal of Hydrology, 498, 221–236. https://doi.org/10.1016/j.jhydrol.2013.06.016 Crow, W. T., Berg, A. A., Cosh, M. H., Loew, A., Mohanty, B. P., Panciera, R., De Rosnay, P., Ryu, D. and Walker, J. P. (2012). Upscaling sparse ground-based soil moisture observations for the validation of coarse-resolution satellite soil moisture products. Reviews of Geophysics, 50(2), 1–20. https://doi.org/10.1029/2011RG000372 Cui, X. (2020). Climate change and adaptation in agriculture: Evidence from US cropping patterns. Journal of Environmental Economics and Management, 101, 102306. https://doi.org/10.1016/j.jeem.2020.102306 da Silva, E. H. F. M., Gonçalves, A. O., Pereira, R. A., Fattori Júnior, I. M., Sobenko, L. R. and Marin, F. R. (2019). Soybean irrigation requirements and canopy-atmosphere coupling in Southern Brazil. Agricultural Water Management, 218(October 2018), 1–7. https://doi.org/10.1016/j.agwat.2019.03.003 Dastane, N. G. (1978). Effective rainfall in irrigated agriculture. FAO Irrigation and Drainage Engineering, 4(1), 25. de la Casa, A. C., Ovando, G. G. and Díaz, G. J. (2021). ENSO influence on corn and soybean yields as a base of an early warning system for agriculture in Córdoba, Argentina. European Journal of Agronomy, 129(June). https://doi.org/10.1016/j.eja.2021.126340 de Oliveira-Júnior, J. F., Mendes, D., Washington Luiz, F. C. F., da Silva Junior, C. A., de Gois, G., da Rosa Ferraz Jardim, A. M., Vinícius da Silva, M., Bastos Lyra, G., Teodoro, P. E., Gomes Pimentel, L. C., Lima, M., de Barros Sant, D. and Pereira Rogelio, J. (2021). Fire foci in South America: Impact and causes, fire hazard and future scenarios José. Journal of South American Earth Sciences, 1446(89), 2669. https://doi.org/10.1016/j.jsames.2021.103623 Delerce, S., Dorado, H., Grillon, A., Rebolledo, M. C., Prager, S. D., Patiño, V. H., Varón, G. G. and Jiménez, D. (2016). Assessing weather-yield relationships in rice at local scale using data mining approaches. PLoS ONE, 11(8). https://doi.org/10.1371/journal.pone.0161620 Devia, G. K., Ganasri, B. P. and Dwarakish, G. S. (2015). A Review on Hydrological Models. Aquatic Procedia, 4(Icwrcoe), 1001–1007. https://doi.org/10.1016/j.aqpro.2015.02.126 Doeffinger, T. and Hall, J. W. (2021). Assessing water security across scales: A case study of the United States. Applied Geography, 134(June), 102500. https://doi.org/10.1016/j.apgeog.2021.102500 Dogan, E. (2019). Effect of supplemental irrigation on vetch yield components. Agricultural Water Management, 213(August 2018), 978–982. https://doi.org/10.1016/j.agwat.2018.12.013 Dunkerley, D. (2010). Effects of rainfall intensity fluctuations on infiltration and runoff: rainfall simulation on dryland soils, Fowlers Gap, Australia. Okt 2005 Abrufbar Uber Httpwww Tldp OrgLDPabsabsguide Pdf Zugriff 1112 2005, 2274(November 2008), 2267–2274. https://doi.org/10.1002/hyp Dunkerley, D. (2015). Intra-event intermittency of rainfall: an analysis of the metrics of rain and no-rain periods. Hydrological Processes, 29(15), 3294–3305. https://doi.org/10.1002/hyp.10454 Dutta, P. and Sarma, A. K. (2021). Hydrological modeling as a tool for water resources management of the data-scarce brahmaputra basin. Journal of Water and Climate Change, 12(1), 152–165. https://doi.org/10.2166/wcc.2020.186 Easterbrook, D. J. (2011). Evidence-Based Climate Science. In New York. Easterbrook, D. J. (2016). Evidence-Based Climate Science: Data Opposing CO2 Emissions as the Primary Source of Global Warming: Second Edition. In Evidence-Based Climate Science: Data Opposing CO2 Emissions as the Primary Source of Global Warming: Second Edition. Egerer, S., Cotera, R. V., Celliers, L. and Costa, M. M. (2021). A leverage points analysis of a qualitative system dynamics model for climate change adaptation in agriculture. Agricultural Systems, 189(February 2020). https://doi.org/10.1016/j.agsy.2021.103052 Espinel, C., Rios, H., Palacino, J. and Arevalo, E. (2020). INFORME LANGOSTA LLANERA ( Rhammatocerus schistocercoides ) EN EL Contexto En Colombia se reporta la langosta llanera Rhammatocerus schistocercoides ( Rehn , 1906 ) es “ autóctona de la Orinoquía colombo-venezolana . Desde junio estados no voladores ( nin. ICA. Esquivel, A., Llanos-Herrera, L., Agudelo, D., Prager, S. D., Fernandes, K., Rojas, A., Valencia, J. J. and Ramirez-Villegas, J. (2018). Predictability of seasonal precipitation across major crop growing areas in Colombia. Climate Services, 12(September), 36–47. https://doi.org/10.1016/j.cliser.2018.09.001 FAO. (2015). AQUASTAT - Sistema mundial de información de la FAO sobre el agua en la agricultura. https://www.fao.org/aquastat/statistics/query/results.html%0A FAO. (2018). Progresos en el nivel de estrés hídrico: valores de referencia mundiales para el indicador 6.4.2 de los ODS. Roma. FAO y ONU-Agua. 58 pp. Licencia: CC BY-NC-SA 3.0 IGO February, E. C. and Higgins, S. I. (2010). The distribution of tree and grass roots in savannas in relation to soil nitrogen and water. South African Journal of Botany, 76(3), 517–523. https://doi.org/10.1016/j.sajb.2010.04.001 Felipe, A. and Montoya, H. (2016). Cambio Climático Y Variabilidad Espacio – Temporal De La Precipitación En Colombia Climate Change and Space-Time Variability of the Precipitation in Colombia As Alterações Climáticas E a Variabilidade Espaço – Temporal Da Chuva Tempo Na Colômbia. Revista EIA, 12(574), 131–150. Feng, S., Hao, Z., Zhang, X. and Hao, F. (2021). Changes in climate-crop yield relationships affect risks of crop yield reduction. Agricultural and Forest Meteorology, 304–305(19), 108401. https://doi.org/10.1016/j.agrformet.2021.108401 Fontanilla-Díaz, C. A., Preckel, P. V., Lowenberg-DeBoer, J., Sanders, J. and Peña-Lévano, L. M. (2021). Identifying profitable activities on the frontier: The Altillanura of Colombia. Agricultural Systems, 192(May). https://doi.org/10.1016/j.agsy.2021.103199 Gallo, O., Bernal, J., Baquero, J., Botero, R. and Gómez, J. (2013). Effect of Three Systems of Incorporation of Dolomite Limestone in the Colombian Flat Plains. Suelos Ecuatoriales Sociedad Colombiana de La Ciencia Del Suelo, 43(1), 24–28. Galvis, J. H., Amézquita Collazos, E. and Madero M., E. (2007). Evaluación del efecto de la intensidad de labranza en la formación de costra superficial de un oxisol de sabana en los Llanos Orientales de Colombia : II. Caracterización física en superficie = Evaluation of harrowing intensity on surface crusting on an o. Acta Agronómica (Colombia), 57(2008), 56(4):191-194. http://www.revistas.unal.edu.co/index.php/acta_agronomica/article/viewFile/1030/1504 Galvis Quintero, J. H., Anaya, O. C., Bernal Riobo, J. H. and Baquero, J. E. (2018). Evaluación de la estabilidad estructural y espacio poroso en un Oxisol de sabana de los Llanos Orientales de Colombia. Journal of Physical Therapy Science, 9(1), 1–11. http://dx.doi.org/10.1016/j.neuropsychologia.2015.07.010%0Ahttp://dx.doi.org/10.1016/j.visres.2014.07.001%0Ahttps://doi.org/10.1016/j.humov.2018.08.006%0Ahttp://www.ncbi.nlm.nih.gov/pubmed/24582474%0Ahttps://doi.org/10.1016/j.gaitpost.2018.12.007%0Ahttps: Gao, F., Wang, Y., Chen, X. and Yang, W. (2020). Trend analysis of rainfall time series in Shanxi province, Northern China (1957-2019). Water (Switzerland), 12(9), 1–22. https://doi.org/10.3390/W12092335 Guo, D., Thomas, J., Lazaro, A. B., Matwewe, F. and Johnson, F. (2021). Modelling the influence of short-term climate variability on drinking water quality in tropical developing countries: A case study in Tanzania. Science of the Total Environment, 763, 142932. https://doi.org/10.1016/j.scitotenv.2020.142932 Gupta, V. and Jain, M. K. (2021). Unravelling the teleconnections between ENSO and dry/wet conditions over India using nonlinear Granger causality. Atmospheric Research, 247(July 2020), 105168. https://doi.org/10.1016/j.atmosres.2020.105168 Guzman, C. D., Hoyos-Villada, F., Da Silva, M., Zimale, F. A., Chirinda, N., Botero, C., Morales Vargas, A., Rivera, B., Moreno, P. and Steenhuis, T. S. (2019). Variability of soil surface characteristics in a mountainous watershed in Valle del Cauca, Colombia: Implications for runoff, erosion, and conservation. Journal of Hydrology, 576(June), 273–286. https://doi.org/10.1016/j.jhydrol.2019.06.002 Hajimirzajan, A., Vahdat, M., Sadegheih, A., Shadkam, E. and Bilali, H. El. (2021). An integrated strategic framework for large-scale crop planning: sustainable climate-smart crop planning and agri-food supply chain management. Sustainable Production and Consumption, 26, 709–732. https://doi.org/10.1016/j.spc.2020.12.016 Hamed, K. H. (2008). Trend detection in hydrologic data: The Mann-Kendall trend test under the scaling hypothesis. Journal of Hydrology, 349(3–4), 350–363. https://doi.org/10.1016/j.jhydrol.2007.11.009 Hao, Y., Hao, Z., Feng, S., Zhang, X. and Hao, F. (2020). Response of vegetation to El Niño-Southern Oscillation (ENSO) via compound dry and hot events in southern Africa. Global and Planetary Change, 195(19), 103358. https://doi.org/10.1016/j.gloplacha.2020.103358 He, Z., Zhao, W., Liu, H. and Chang, X. (2012). The response of soil moisture to rainfall event size in subalpine grassland and meadows in a semi-arid mountain range: A case study in northwestern China’s Qilian Mountains. Journal of Hydrology, 420–421, 183–190. https://doi.org/10.1016/j.jhydrol.2011.11.056 Hébert-Dufresne, L., Pellegrini, A. F. A., Bhat, U., Redner, S., Pacala, S. W. and Berdahl, A. M. (2018). Edge fires drive the shape and stability of tropical forests. Ecology Letters, 21(6), 794–803. https://doi.org/10.1111/ele.12942 Hillel, D. (1998). Environmental Soil Physics: Fundamentals, Applications, and Environmental Considerations. Academic Press, Waltham. Hoyos, N., Escobar, J., Restrepo, J. C., Arango, A. M. and Ortiz, J. C. (2013). Impact of the 2010-2011 La Niña phenomenon in Colombia, South America: The human toll of an extreme weather event. Applied Geography, 39(September 2011), 16–25. https://doi.org/10.1016/j.apgeog.2012.11.018 Huertas, H. D., Rangel, J. A. and Parra, A. S. (2018). Chemical characterization of soil fertility in production systems of a flat High Plateau, Meta, Colombia. Revista Luna Azul, 46(46), 54–69. https://doi.org/10.17151/luaz.2018.46.5 Ibrahim, M. A. and Johansson, M. (2021). Attitudes to climate change adaptation in agriculture – A case study of Öland, Sweden. Journal of Rural Studies, 86(March), 1–15. https://doi.org/10.1016/j.jrurstud.2021.05.024 ICA. (2011). Resolucion 2705.pdf (p. 2). https://www.ica.gov.co/getattachment/513310fc-449e-4330-a0bc-5e226eb1e9a1/Cultivo-del-Arroz.aspx IDEAM. (2005). Atlas Climatológico de Colombia. Instituto De Hidrología, Meteorología Y Estudios Ambientales - Ideam, 78. IDEAM. (2012). Sequía meteorológica y sequía agícola en Colombia: incidencia y tendencias. 49. http://www.ideam.gov.co/documents/21021/21138/Sequias+Incidencias+y+Tendencias.pdf/3e72c86c-cf4a-42f9-95f1-07e7cf88861a IDEAM. (2013). Zonificación y codificación de uniades hidrográficas e hidrogeológicas de Colombia. Publicación Aprobada Por El Comité de Comunicaciones y Publicaciones Del IDEAM, 47. http://documentacion.ideam.gov.co/openbiblio/bvirtual/022655/MEMORIASMAPAZONIFICACIONHIDROGRAFICA.pdf IDEAM. (2015). Mapa de Coberturas de la Tierra Metodología Corine Land Cover Adaptada para Colombia Escala 1:100.000 (Período 2010 - 2012) (p. 117). http://documentacion.ideam.gov.co/openbiblio/bvirtual/023236/IEARN_segunda_parte_ecosistemas_2014.pdf IDEAM. (2016). Conocer: El primer paso para adaptarse. Guía básica de conceptos sobre el cambio climático. In Tercera Comunicación Nacional de Cambio Climático. http://documentacion.ideam.gov.co/openbiblio/bvirtual/023631/ABC.pdf IDEAM. (2017a). Atlas climatologico de Colombia [PDF]. Instituto de Hidrología, Meteorología y Estudios Ambientales. http://documentacion.ideam.gov.co/openbiblio/bvirtual/023777/CLIMA.pdf IDEAM. (2017b). Diseñode la Red Hidrometeorológica Nacional. 1–16. http://sgi.ideam.gov.co/documents/412030/561097/M-GDI-H-G001+GUÍA+DISEÑO+DE+LA+RED+HIDROMETEOROLÓGICA+NACIONAL.pdf/9da0e118-58cc-43eb-87e0-8c6316dc691c?version=1.0#:~:text=El IDEAM opera una red,satelital o vía celular%2C GPRS. IDEAM. (2018). Protocolo de Modelacion Hidrológica e Hidráulica. In Instituto de Hidrología, Meteorología y Estudios Ambientales – IDEAM. http://documentacion.ideam.gov.co/openbiblio/bvirtual/023833/Protocolo_Modelacion_HH.pdfc IDEAM. (2019a). DHIME - Manual de Usuario Consulta y Descarga de datos hidrometeorológicos - IDEAM. Manual, 53. IDEAM. (2019b). Estudio Nacional del Agua 2018. Bogotá: Ideam: 452 pp. http://www.andi.com.co/Uploads/ENA_2018-comprimido.pdf IDEAM and UNAL. (2018). Variabilidad climática y el cambio climático en Colombia [Archivo PDF]. In Instituto de Hidrología, Meteorología y Estudios Ambientales – IDEAM Universidad Nacional de Colombia – UNAL (p. 28). http://documentacion.ideam.gov.co/openbiblio/bvirtual/023778/variabilidad.pdf IGAC. (1973). Reconocimiento semidetallado de suelos del C.I La Libertad (Departamento del Meta) Intituto Geografico Agustin Codazzi. IGAC. (2004). Estudio general de suelos y zonificación de tierras del departamento de Meta. Instituto Geografico Agustin Codazzi, 9067. IGAC. (2017). Instructivo: Etapa de campo para leventamiento de suelos, Grupo interno de trabajo de levantamiento de suelos y aplicaciones agrologicas [PDF]. http://igacnet2.igac.gov.co/intranet/UserFiles/File/DOCUMENTOS SGI 2021/GAG/PC-GAG-05/IN-GAG-PC05-09 Etapa de campo para levantamientos de suelos.pdf IGAC. (2018). Sistema de clasificacion geomorfologica aplicado a los levantamientos de suelos, Instituto Geográfico Agustín Codazzi. Subdirección de Agrología. IPCC. (2007). Cambio climático 2007: Informe de síntesis. Contribución de los Grupos de trabajo I, II y III al Cuarto Informe de evaluación del Grupo Intergubernamental de Expertos sobre el Cambio Climático [Equipo de redacción principal: Pachauri, R.K. y Reisinger, A. In Proceedings of the Mediterranean Electrotechnical Conference - MELECON. https://doi.org/10.1109/MELCON.2008.4618473 IPCC. (2014). Cambio climático 2014: Informe de Síntesis. In Contribución de los Grupos de trabajo I,II y III al Quinto Informe de Evaluación del Grupo Intergubernamental de Expertos sobre el Cambio Climático [Equipo principal de redacción, R.K. Pachauri y L.A. Meyer (eds.)]. IPCC, Ginebra, Suiza. https://www.ipcc.ch/site/assets/uploads/2018/02/SYR_AR5_FINAL_full_es.pdf IPCC. (2018). Glosario [Matthews J.B.R. (ed.)]. En: Calentamiento global de 1,5 °C, Informe especial del IPCC sobre los impactos del calentamiento global de 1,5 oC con respecto a los niveles preindustriales y las trayectorias correspondientes que deberían seguir las em. https://www.ipcc.ch/site/assets/uploads/sites/2/2019/10/SR15_Glossary_spanish.pdf IPCC. (2020). El cambio climático y la tierra. In Grupo Intergubernamental de Expertos sobre el Cambio Climático. https://www.ipcc.ch/site/assets/uploads/sites/4/2020/06/SRCCL_SPM_es.pdf Jia, Y. (2011). Coupling crop growth and hydrologic models to predict crop yield with spatial analysis technologies. Journal of Applied Remote Sensing, 5(1), 053537. https://doi.org/10.1117/1.3609844 Kamble, P. S., Maniyar, V. G. and Jadhav, J. D. (2010). Crop coefficients (Kc) of soybean [Glycine max (L.) Merrill]. Asian Journal of Environmental Science, 5(2), 131–135. Krinitskiy, M., Grashchenkov, K., Tilinina, N. and Gulev, S. (2021). Tracking of atmospheric phenomena with artificial neural networks: A supervised approach. Procedia Computer Science, 186, 403–410. https://doi.org/10.1016/j.procs.2021.04.209 Kundzewicz, Z. W., Huang, J., Pinskwar, I., Su, B., Szwed, M. and Jiang, T. (2020). Climate variability and floods in China - A review. Earth-Science Reviews, 211(February), 103434. https://doi.org/10.1016/j.earscirev.2020.103434 Lafitte, H. R. (1994). Guia de campo: Identificación de problemas en la producción de maíz tropical [PDF]. CIMMYT, 122. https://repository.cimmyt.org/bitstream/handle/10883/727/43157.pdf?sequence=1&isAllowed=y Lal, R. and Shukla, M. K. (2005). Principles of soil physics, The Ohio State University Columbus, Ohio, U.S.A. In Mercel Dekker, INC. New York, Basel (Vol. 4, Issue March). https://dewagumay.files.wordpress.com/2011/12/principles-of-soil-physics.pdf Leon, G., Arcila, A., Pulido, L. A. and Kondo, T. (2018). Capítulo 25 Contenido Cambio climático y control biológico de insectos : visión y perspectiva de la situación Chapter 25 Climate change and biological control of insects : current situation and perspectives. In Control biológico de fitopatógenos, insectos y ácaros (Issue October, p. 572). Lesk, C., Rowhani, P. and Ramankutty, N. (2016). Influence of extreme weather disasters on global crop production. Nature, 529(7584), 84–87. https://doi.org/10.1038/nature16467 Li, F., Li, W., Li, F., Long, Y., Guo, S., Li, X., Lin, C. and Li, J. (2022). Global projections of future wilderness decline under multiple IPCC Special Report on Emissions Scenarios. Resources, Conservation and Recycling, 177(June 2021), 105983. https://doi.org/10.1016/j.resconrec.2021.105983 Li, X., Zhang, K., Gu, P., Feng, H., Yin, Y., Chen, W. and Cheng, B. (2021). Changes in precipitation extremes in the Yangtze River Basin during 1960–2019 and the association with global warming, ENSO, and local effects. Science of the Total Environment, 760, 144244. https://doi.org/10.1016/j.scitotenv.2020.144244 Limami, A. M., Diab, H. and Lothier, J. (2014). Nitrogen metabolism in plants under low oxygen stress. Planta, 239(3), 531–541. https://doi.org/10.1007/s00425-013-2015-9 Liu, J., Liang, Y., Gao, G., Dunkerley, D. and Fu, B. (2022). Quantifying the effects of rainfall intensity fluctuation on runoff and soil loss: From indicators to models. Journal of Hydrology, 607(February 2021), 127494. https://doi.org/10.1016/j.jhydrol.2022.127494 Loaiza, J. and Pauwels, V. (2008). Utilizacion de sensores de humedad para la determinacion del contenido de humedad del suelo (Ecuaciones de Calibración). Suelos Ecuatoriales Sociedad Colombiana de La Ciencia Del Suelo, 38(1), 24–33. Loaiza, J., Poch, R. and Pauwels, V. (2010). Evaluation of soil water moisture regime prediction methods in the mountain region of Catalan Pre-Pyrenees. Suelos Ecuatoriales Sociedad Colombiana de La Ciencia Del Suelo, 40(1), 38–50. López, J. J., Goñi, M., San Martín, I. and Erro, J. (2019). Análisis regional de frecuencias de las precipitaciones diarias extremas en Navarra. Elaboración de los mapas de cuantiles. Ingeniería Del Agua, 23(1), 33. https://doi.org/10.4995/ia.2019.10058 Lozano, E. (2014). Compilación de la cuenca de los Llanos Orientales. Servicio Geológico Colombiano, 1(Diciembre), 5–9. Lu, B., Li, H., Wu, J., Zhang, T., Liu, J., Liu, B., Chen, Y. and Baishan, J. (2019). Impact of El Niño and Southern Oscillation on the summer precipitation over Northwest China. Atmospheric Science Letters, 20(8), 1–8. https://doi.org/10.1002/asl.928 Ma, Y. jun, Li, X. yan, Guo, L. and Lin, H. (2017). Hydropedology: Interactions between pedologic and hydrologic processes across spatiotemporal scales. Earth-Science Reviews, 171(19), 181–195. https://doi.org/10.1016/j.earscirev.2017.05.014 Manfreda, S. and Rodríguez-Iturbe, I. (2006). On the spatial and temporal sampling of soil moisture fields. Water Resources Research, 42(5), 2757–2760. https://doi.org/10.1029/2005WR004548 Martineli, A., Leonel, P., Fabíola, N. and Giarola, B. (2020). Rhizosphere Evaluation of the soil aggregation induced by the plant roots in an Oxisol by turbidimetry and water percolation. Rhizosphere, 16(October), 100265. https://doi.org/10.1016/j.rhisph.2020.100265 McGraw, M. C. and Barnes, E. A. (2018). Memory matters: A case for granger causality in climate variability studies. Journal of Climate, 31(8), 3289–3300. https://doi.org/10.1175/JCLI-D-17-0334.1 Meran, G., Siehlow, M. and Hirschhausen, C. von. (2021). The Economics of War. In New Perspectives Quarterly (Vol. 18, Issue 4, pp. 48–50). https://doi.org/10.1111/0893-7850.00441 Meshesha, T. W. and Khare, D. (2019). Towards integrated water resources management considering hydro-climatological scenarios: an option for sustainable development. Environmental Systems Research, 8(1). https://doi.org/10.1186/s40068-019-0134-4 Mesri, M., Ghilane, A. and Bachari, N. E. I. (2013). An approach to spatio-temporal analysis for climatic data. Revue Des Energies Renouvelables, 16, 413–424. Milella, P., Bisantino, T., Gentile, F., Iacobellis, V. and Trisorio Liuzzi, G. (2012). Diagnostic analysis of distributed input and parameter datasets in Mediterranean basin streamflow modeling. Journal of Hydrology, 472–473, 262–276. https://doi.org/10.1016/j.jhydrol.2012.09.039 MINAMBIENTE. (2010). Política Nacional para la Gestión Integral del Recurso Hídrico. Bogotá, D.C.: Colombia [PDF]. Ministerio de Ambiente, Vivienda y Desarrollo Territorial, 124. https://www.minambiente.gov.co/wp-content/uploads/2021/10/Politica-nacional-Gestion-integral-de-recurso-Hidrico-web.pdf MINAMBIENTE. (2014). Guía Técnica para la formulación de los Planes de Ordenamiento y Manejo de Cuencas Hidrograficas POMCAS [PDF]. Ministerio de Medio Ambiente y Desarrollo Sostenible, 104. https://repositorio.gestiondelriesgo.gov.co/bitstream/handle/20.500.11762/22585/1-Guia_Tecnica_pomcas-MinAmbiente-2014.pdf?sequence=1&isAllowed=y Munar, A. M., Cavalcanti, J. R., Bravo, J. M., Fan, F. M., Motta-Marques, D. da and Fragoso, C. R. (2018). Coupling large-scale hydrological and hydrodynamic modeling: Toward a better comprehension of watershed-shallow lake processes. Journal of Hydrology, 564(March), 424–441. https://doi.org/10.1016/j.jhydrol.2018.07.045 Norel, M., Kałczyński, M., Pińskwar, I., Krawiec, K. and Kundzewicz, Z. W. (2021). Climate variability indices—a guided tour. Geosciences (Switzerland), 11(3), 1–27. https://doi.org/10.3390/geosciences11030128 OMM. (2008). Guía de prácticas hidrológicas. Volumen II. Gestión de recursos hídricos y aplicación de prácticas hidrológicas. https://library.wmo.int/index.php?lvl=notice_display&id=9404#.X10SsWgzbDc OMM. (2011). Guía de Prácticas Hidrológicas Volumen I. In World Meteorological Organization, No. 168. http://www.wmo.int/pages/prog/hwrp/publications/guide/spanish/168_Vol_I_es.pdf OMM. (2014). El Niño/Oscilación del Sur. Organización Meteorológica Mundial Tiempo-Clima-Agua, N°1145, 12. https://library.wmo.int/doc_num.php?explnum_id=7889 Orduz, J. and Fischer, G. (2007). Balance hídrico e influencia del estrés hídrico en la inducción y desarrollo floral de la mandarina ‘Arrayana’ en el piedemonte llanero de Colombia. Agronomía Colombiana, 25(2), 255–263. Orozco Jamioy, D. D., Menjivar Flores, J. C. and Rubiano Sanabria, Y. (2015). Indicadores químicos de calidad de suelos en sistemas productivos del Piedemonte de los Llanos Orientales de. Acta Agronomica, 64, 302–307. Panagos, P., Standardi, G., Borrelli, P., Lugato, E., Montanarella, L. and Bosello, F. (2018). Cost of agricultural productivity loss due to soil erosion in the European Union: From direct cost evaluation approaches to the use of macroeconomic models. Land Degradation and Development, 29(3), 471–484. https://doi.org/10.1002/ldr.2879 Paoletti, J. M. and Shortridge, J. E. (2020). Improved representation of uncertainty in farm-level financial cost-benefit analyses of supplemental irrigation in humid regions. Agricultural Water Management, 239(June 2019), 106245. https://doi.org/10.1016/j.agwat.2020.106245 Pardo, O., Torres, H., Trujillo, G. and Trujillo, J. (2020). Impactos del cambio climatico sobre los rendiemientos del Arroz (Oryza sativa L) en la zona llanos, Colombia [PDF]. AGLALA ISSN 2215-7360, 11(2), 94–106. https://revistas.curn.edu.co/index.php/aglala/article/view/1698 Peña, A., Jaramillo R, Á. and Paternina Q, M. J. (2011). Detecting low frequency cycles in rainfall series from Colombian coffee-growing area by using descriptive methods. Earth Sciences Research Journal, 15(2), 109–114. Perez, R. A. (1992). Pasto Humidicola. Bolétin Técnico, 181, 14. http://ciat-library.ciat.cgiar.org/Articulos_Ciat/Digital/ICA_000041C.2_Pasto_humidicola_Brachiaria_humidicola_Rendle_Schweickt.pdf Pla Sentis, I. (2016). Nuevos enfoques para el manejo y conservacion de suelos y agua en sistemas agricolas y medio ambientales. Suelos Ecuatoriales Sociedad Colombiana de La Ciencia Del Suelo, 46(1 y 2), 101–111. Poveda, G., Álvarez, D. M. and Rueda, Ó. A. (2011). Hydro-climatic variability over the Andes of Colombia associated with ENSO: A review of climatic processes and their impact on one of the Earth’s most important biodiversity hotspots. Climate Dynamics, 36(11–12), 2233–2249. https://doi.org/10.1007/s00382-010-0931-y Poveda, G., Espinoza, J. C., Zuluaga, M. D., Solman, S. A., Garreaud, R. and van Oevelen, P. J. (2020). High Impact Weather Events in the Andes. Frontiers in Earth Science, 8(May), 1–32. https://doi.org/10.3389/feart.2020.00162 Praveen, B., Talukdar, S., Shahfahad, Mahato, S., Mondal, J., Sharma, P., Islam, A. R. M. T. and Rahman, A. (2020). Analyzing trend and forecasting of rainfall changes in India using non-parametrical and machine learning approaches. Scientific Reports, 10(1), 1–21. https://doi.org/10.1038/s41598-020-67228-7 Pringle, G. (2017). Maize production: Managing critical plant growth stages. https://www.farmersweekly.co.za/crops/field-crops/maize-production-managing-critical-plant-growth-stages/ Rahman, A., Kuddus, M. A., Ip, R. H. L. and Bewong, M. (2021). A review of covid‐19 modelling strategies in three countries to develop a research framework for regional areas. Viruses, 13(11), 1–23. https://doi.org/10.3390/v13112185 Ramirez C., C., Vélez U., J. J. and Peña Q., A. J. (2018). Analizando índices climáticos para predecir la lluvia mensual en una región agrícola de los andes del norte (Caldas, Colombia). Investigaciones Geográficas, 55, 111. https://doi.org/10.5354/0719-5370.2018.48460 Ramírez, N. E., Munar, D., van der Hilst, F., Espinosa, J. C., Ocampo-Duran, Á., Ruíz-Delgado, J., Molina-López, D. L., Wicke, B., Garcia-Nunez, J. A. and Faaij, A. P. C. (2021). Ghg balance of agricultural intensification & bioenergy production in the orinoquia region, colombia. Land, 10(3), 1–30. https://doi.org/10.3390/land10030289 Randall, M., Montgomery, J. and Lewis, A. (2022). Robust temporal optimisation for a crop planning problem under climate change uncertainty. Operations Research Perspectives, 9(October 2021), 100219. https://doi.org/10.1016/j.orp.2021.100219 Ray, D. K., Gerber, J. S., Macdonald, G. K. and West, P. C. (2015). Climate variation explains a third of global crop yield variability. Nature Communications, 6, 1–9. https://doi.org/10.1038/ncomms6989 Refsgaard, J. C. and Knudsen, J. (1996). Operational validation and intercomparison of different types of hydrological models. Water Resources Research, 32(7), 2189–2202. https://doi.org/10.1029/96WR00896 Rial, A., Lasso, C. A. and Colonnello, G. (2016). Clasificación de los paisajes de la Orinoquia. Colombia y Venezuela. XI. Humedales de La Orinoquia (Colombia- Venezuela). Serie Editorial Recursos Hidrobiológicos y Pesqueros Continentales de Colombia, January 2014, 35–49. Ricaurte, J., Idupalapati, R. and Menjivar, J. C. (2007). Estrategias de enraizamiento de genotipos Brachiaria en suelos acidos y de baja fertilidad en Colombia. Acta Agronomica, 56(3), 107–115. Rincón, Á., Flórez, H., Ballesteros, H. and León, L. M. (2018). Effects of fertilization of Brachiaria humidicola cv. Llanero on pasture productivity in the foothills region of the Llanos Orientales, Colombia. Tropical Grasslands-Forrajes Tropicales, 6(3), 158–168. https://doi.org/10.17138/TGFT(6)158-168 Robinson, D. A., Jones, S. B., Lebron, I., Reinsch, S., Domínguez, M. T., Smith, A. R., Jones, D. L., Marshall, M. R. and Emmett, B. A. (2016). Experimental evidence for drought induced alternative stable states of soil moisture. Scientific Reports, 6(September 2015), 1–6. https://doi.org/10.1038/srep20018 Rodriguez, N. S., Lavelle, P., Pulido, S. X., Gutierrez, A., Bernal, J. H., Arguello, O., Botero, C., Gomez, Y., Hurtado, M. del P., Loaiza, S. P. and Rodriguez, E. (2013). Construcción de indicadores de ecoeficiencia para la altillanura plana en los municipios de Puerto López y Puerto Gaitán, departamento del Meta. Villavicencio (Colombia). CORPOICA, 40. Sánchez Ortega, J. M. (2021). Evaluación del transporte de humedad atmosférica desde el océano Atlántico hacia las cuencas del Orinoco y el norte del Amazonas durante el año 2010 mediante el modelo WRF-Tracers [Tesis de Ingenieria Ambiental]. In Universidad de Antioquia. https://bibliotecadigital.udea.edu.co/bitstream/10495/19697/1/SanchezJuan_2021_EvalucionTransporteHumedad.pdf Sarkar, S., Zhu, X., Melnykov, V. and Ingrassia, S. (2020). On parsimonious models for modeling matrix data. Computational Statistics and Data Analysis, 142, 106822. https://doi.org/10.1016/j.csda.2019.106822 Seibert, J. and Vis, M. J. P. (2012). Teaching hydrological modeling with a user-friendly catchment-runoff-model software package. 3315–3325. https://doi.org/10.5194/hess-16-3315-2012 Sen, P. K. (1968). Estimates of the Regression Coefficient Based on Kendall’s Tau. Journal of the American Statistical Association, 63(324), 1379–1389. https://doi.org/10.1080/01621459.1968.10480934 Seneviratne, S. I., Corti, T., Davin, E. L., Hirschi, M., Jaeger, E. B., Lehner, I., Orlowsky, B. and Teuling, A. J. (2010). Investigating soil moisture-climate interactions in a changing climate: A review. Earth-Science Reviews, 99(3–4), 125–161. https://doi.org/10.1016/j.earscirev.2010.02.004 Sharifi, A., Mirabbasi, R., Ali Nasr-Esfahani, M., Torabi Haghighi, A. and Fatahi Nafchi, R. (2021). Quantify the impacts of anthropogenic changes and climate variability on runoff changes in central plateau of Iran using nine methods. Journal of Hydrology, 603(PC), 127045. https://doi.org/10.1016/j.jhydrol.2021.127045 Sheikh Goodarzi, M., Jabbarian Amiri, B., Azarnivand, H. and Waltner, I. (2021). Watershed hydrological modelling in data scarce regions; integrating ecohydrology and regionalization for the southern Caspian Sea basin, Iran. Heliyon, 7(4), e06833. https://doi.org/10.1016/j.heliyon.2021.e06833 Shiklomanov, I. A. (2000). Appraisal and Assessment of world water resources. Water International, 25(1), 11–32. https://doi.org/10.1080/02508060008686794 Shiklomanov, I. A. and Rodda, J. C. (2004). World water resources at the beginning of the twenty-first century. Choice Reviews Online, 41(07), 41-4063-41–4063. https://doi.org/10.5860/choice.41-4063 Solomatine, D. P. and Wagener, T. (2011). Hydrological Modeling. Treatise on Water Science, 2, 435–457. https://doi.org/10.1016/B978-0-444-53199-5.00044-0 Stephens, E. C., Jones, A. D. and Parsons, D. (2018). Agricultural systems research and global food security in the 21st century: An overview and roadmap for future opportunities. Agricultural Systems, 163, 1–6. https://doi.org/10.1016/j.agsy.2017.01.011 Sun, H., Shen, Y., Yu, Q., Flerchinger, G. N., Zhang, Y., Liu, C. and Zhang, X. (2010). Effect of precipitation change on water balance and WUE of the winter wheat-summer maize rotation in the North China Plain. Agricultural Water Management, 97(8), 1139–1145. https://doi.org/10.1016/j.agwat.2009.06.004 Sun, X., Renard, B., Thyer, M., Westra, S. and Lang, M. (2015). A global analysis of the asymmetric effect of ENSO on extreme precipitation. Journal of Hydrology, 530, 51–65. https://doi.org/10.1016/j.jhydrol.2015.09.016 Tao, F., Rötterb, R., Palosuo, T., Díaz, C. G. H., -Ambrona, C, Mínguez, M. I., C, Mikhail, Semenov, A., D, Kersebaum, K. C., E, Nendel, C., E, Specka, X., E, Hoffmann, H., F, … A, J. (2016). Contribution of crop model structure, parameters and climate projections to uncertaint y in climate change impact assessments. In International Journal of Laboratory Hematology (Vol. 38, Issue 1). https://doi.org/10.1111/ijlh.12426 Tapiero, A., Caicedo, S., Baquero, J., Ospina, Y., Guimaraes, E. and Chatel, M. (2012). Arroz Corpoica Llanura 11. Tardieu, F., Draye, X. and Javaux, M. (2017). Root Water Uptake and Ideotypes of the Root System: Whole-Plant Controls Matter. Vadose Zone Journal, 16(9), vzj2017.05.0107. https://doi.org/10.2136/vzj2017.05.0107 Thomas, W., Angarita, H. and Delgado, J. (2015). Hacia una gestión integral de la Cuenca y planicies inundables del Magdalena-Cauca. Foro Público: Para Dónde va El Río Magdalena -Foro Nacional Ambiental, 22. Tian, Q., Lu, J. and Chen, X. (2022). A novel comprehensive agricultural drought index reflecting time lag of soil moisture to meteorology: A case study in the Yangtze River basin, China. Catena, 209(P1), 105804. https://doi.org/10.1016/j.catena.2021.105804 Trnka, M., Vizina, A., Hanel, M., Balek, J., Fischer, M., St, P., Hlavinka, P., Semer, D., Zahradní, P., Skal, P., Monika, B., Eitzinger, J., Dubrovský, M. and Petr, M. (2022). Increasing available water capacity as a factor for increasing drought resilience or potential conflict over water resources under present and future climate conditions. 264(August 2020). Urrea, V., Ochoa, A. and Mesa, O. (2019). Seasonality of Rainfall in Colombia. Water Resources Research, 55(5), 4149–4162. https://doi.org/10.1029/2018WR023316 USDA. (2014). Keys to soil taxonomy. United States Department of Agriculture Natural Resources Conservation Service, 12, 410. http://www.nrcs.usda.gov/Internet/FSE_DOCUMENTS/nrcs142p2_051546.pdf Van Loon, A. F. (2015). Hydrological drought explained. WIREs Water, 2(4), 359–392. https://doi.org/10.1002/wat2.1085 Van Nguyen, L., Takahashi, R., Githiri, S. M., Rodriguez, T. O., Tsutsumi, N., Kajihara, S., Sayama, T., Ishimoto, M., Harada, K., Suematsu, K., Abiko, T. and Mochizuki, T. (2017). Mapping quantitative trait loci for root development under hypoxia conditions in soybean (Glycine max L. Merr.). Theoretical and Applied Genetics, 130(4), 743–755. https://doi.org/10.1007/s00122-016-2847-3 Velasco, H., Silva, A., Veenhuizen, R., Pérez, S., Prieto, M., Anaya, M., León, B., Cabas, N., Porto, E. and Morales, R. (2000). Manual de captacion y aprobechamiento de agua lluvia experiencias en America Latina serie: Zonas Áridas y Semiáridas. Organización de Las Naciones Unidas Para La Agricultura y La Alimentación FAO, No13, 194 Velásquez F, S. and Jaramillo R, A. (2009). Redistribución de la lluvia en diferentes coberturas vegetales de la zona cafetera central de Colombia. Cenicafé, 60(2), 148–160. http://www.cenicafe.org/es/publications/arc060(02)148-160.pdf Von der Heydt, A. S., Ashwin, P., Camp, C. D., Crucifix, M., Dijkstra, H. A., Ditlevsen, P. and Lenton, T. M. (2021). Quantification and interpretation of the climate variability record. Global and Planetary Change, 197(May 2020), 103399. https://doi.org/10.1016/j.gloplacha.2020.103399 Wallach, D., Thorburn, P., Asseng, S., Challinor, A. J., Ewert, F., Jones, J. W., Rotter, R. and Ruane, A. (2016). Estimating model prediction error: Should you treat predictions as fixed or random? Environmental Modelling and Software, 84, 529–539. https://doi.org/10.1016/j.envsoft.2016.07.010 Wang, C. (2018). A review of ENSO theories. National Science Review, 5(6), 813–825. https://doi.org/10.1093/nsr/nwy104 Wang, C. and Fiedler, P. C. (2006). ENSO variability and the eastern tropical Pacific: A review. Progress in Oceanography, 69(2–4), 239–266. https://doi.org/10.1016/j.pocean.2006.03.004 Wang, Y., You, W., Fan, J., Jin, M., Wei, X. and Wang, Q. (2018). Effects of subsequent rainfall events with different intensities on runoff and erosion in a coarse soil. Catena, 170(June), 100–107. https://doi.org/10.1016/j.catena.2018.06.008 Yan, Y., Mao, K., Shen, X., Cao, M., Xu, T., Guo, Z. and Bao, Q. (2021). Evaluation of the influence of ENSO on tropical vegetation in long time series using a new indicator. Ecological Indicators, 129, 107872. https://doi.org/10.1016/j.ecolind.2021.107872 Yang, X., Magnusson, J., Huang, S., Beldring, S. and Xu, C. Y. (2020). Dependence of regionalization methods on the complexity of hydrological models in multiple climatic regions. Journal of Hydrology, 582, 124357. https://doi.org/10.1016/j.jhydrol.2019.124357 Yeh, S. W., Cai, W., Min, S. K., McPhaden, M. J., Dommenget, D., Dewitte, B., Collins, M., Ashok, K., An, S. Il, Yim, B. Y. and Kug, J. S. (2018). ENSO Atmospheric Teleconnections and Their Response to Greenhouse Gas Forcing. Reviews of Geophysics, 56(1), 185–206. https://doi.org/10.1002/2017RG000568 Yue, S. and Wang, C. Y. (2002). Applicability of prewhitening to eliminate the influence of serial correlation on the Mann-Kendall test. Water Resources Research, 38(6), 4-1-4–7. https://doi.org/10.1029/2001wr000861 Zhao, C., Jia, X., Shao, M. and Zhu, Y. (2021). Regional variations in plant-available soil water storage and related driving factors in the middle reaches of the Yellow River Basin, China. Agricultural Water Management, 257(June), 107131. https://doi.org/10.1016/j.agwat.2021.107131 Zounemat, M., Batelaan, O., Fadaee, M. and Hinkelmann, R. (2021). Ensemble machine learning paradigms in hydrology: A review. Journal of Hydrology, 598(March), 126266. https://doi.org/10.1016/j.jhydrol.2021.126266 |
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Universidad Nacional de Colombia |
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Atribución-NoComercial-SinDerivadas 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Loaiza Usuga, Juan Carlosdba4c827d8b0596a7b2495dfa02b7a6fBernal Riobo, Jaime Humberto2c90bfcf4e9f6fa9fa09ef188a9d83c8Gallo Gordillo, Oscar Javierc6ce29bc8db1532aced8263198339fc62022-08-22T21:45:00Z2022-08-22T21:45:00Z2022-08-20https://repositorio.unal.edu.co/handle/unal/82003Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustraciones, graficas, mapasLas variaciones de rendimiento en los sistemas agrícolas para la región Orinoquia asociados a eventos extremos de precipitación, hacen necesario el estudio de la oferta hídrica para los cultivos. Para lo cual se instrumentó una cuenca hidrográfica con equipos para la medición de humedad de suelo, caudales, precipitación y evapotranspiración, e identifico propiedades fisicoquímicas del suelo que determinan de dinámica del agua. La cuenca se identifica como caño Quenane, ubicada en el piedemonte de la cordillera oriental colombiana. Adicionalmente se analizó las condiciones de variabilidad climática en la oferta hídrica. Con la información generada en la instrumentación se calibro el modelo hidrológico HBV. Los resultados identifican poca cantidad de agua aprovechable dadas en el suelo, generando que la humedad del suelo se aproxime frecuentemente a valores de punto de marchitez permanente. Se evidencio un cambio en la distribución de las precipitaciones con una disminución del número de días lluviosos al año, especialmente en el segundo semestre, que junto con relieves bien drenados estaría favoreciendo condiciones de suelos secos, identificados como Usticos, indicando limitaciones agrícolas. El modelo hidrológico HBV, tuvo un desempeño no satisfactorio para estimar caudal, puesto que subestima los datos medidos en la temporada lluviosa y sobreestima en la temporada seca. Sin embargo, los contenidos de agua en el suelo simulados presentan una aproximación a los valores medidos en el horizonte superficial, lo que indica una alternativa de aplicación en el monitoreo de la oferta hídrica disponible para las plantas. (Texto tomado de la fuente)Yield variations in agricultural systems for the Orinoquia region associated with extreme precipitation events make it necessary to study the water supply for crops. For which a hydrographic basin was instrumented with equipment for the measurement of soil humidity, flows, precipitation, and evapotranspiration, and identified physicochemical properties of the soil that determine water dynamics. The basin is identified as Caño Quenane, located in the foothills of the Colombian Eastern Cordillera. Additionally, the conditions of climatic variability in the water supply were analyzed. With the information generated in the instrumentation, the HBV hydrological model was calibrated. The results identify little amount of usable water given in the soil, causing soil moisture to frequently approach permanent wilting point values. A change in the distribution of rainfall was evidenced with a decrease in the number of rainy days per year, especially in the second semester, which together with well-drained reliefs would be favoring dry soil conditions, identified as Ustic, indicating agricultural limitations. The HBV hydrological model had an unsatisfactory performance to estimate flow, since it underestimates the data measured in the rainy season and overestimates in the dry season. However, the simulated soil water contents present an approximation to the values measured in the Ap horizon, which indicates an alternative application in monitoring the available water supply for plants.Corporación colombiana de Investigación Agropecuaria - AgrosaviaMaestríaMagíster en Ciencias AgrariasSuelos y Aguasxv, 123 páginasapplication/pdfspaUniversidad Nacional de ColombiaBogotá - Ciencias Agrarias - Maestría en Ciencias AgrariasEscuela de posgradosFacultad de Ciencias AgrariasBogotá, ColombiaUniversidad Nacional de Colombia - Sede Bogotá630 - Agricultura y tecnologías relacionadas::633 - Cultivos de campo y de plantaciónPrecipitaciónOrinoquiaUso del sueloPrecipitationSoil moistureOrinoquiaLand usesHumedad del sueloRecursos hídricosUso de la tierraSoil moistureWater resourcesLand useEstimación de la oferta hídrica para la planificación de cultivos en una cuenca hidrográfica de la Orinoquía colombianaEstimation of water supply for crop planning in a hydrographic basin of the Colombian OrinoquíaTrabajo de grado - Maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionTexthttp://purl.org/redcol/resource_type/TMRedColLaReferenciaAbdAllah, A. M., Mashaheet, A. M. and Burkey, K. O. (2021). Super absorbent polymers mitigate drought stress in corn (Zea mays L.) grown under rainfed conditions. Agricultural Water Management, 254(December 2020), 106946. https://doi.org/10.1016/j.agwat.2021.106946Alan, A. T. M., Rahman, M. S. and Sadaat, A. H. M. (2014). Markov Chain Analysis of Weekly Rainfall Data for Predicting Agricultural Drought. In Computational Intelligence Techniques in Earth and Environmental Sciences (pp. 109–128).Allen, R. G., Pereira, L. S., Raes, D. and Smith, M. (1998). Evapotranspiración del cultivo, Guías para la determinación de los requerimientos de agua de los cultivos. FAO - Food and Agriculture Organization of the United Nations, 56Almansa, E. F. (2006a). Manejo del recurso hídrico para el cultivo de la soya en la Orinoquia Colombiana. In Soya (Glycine max (L.) Merril) Alternativa para los sistemas de produccion para los sistemas de produccion de la Orinoquia colombiana. (p. 224).Almansa, E. F. (2006b). Requerimientos hídricos del cultivo de soya en la Altillanura (p. 2). https://repository.agrosavia.co/handle/20.500.12324/13777Amézquita, E. (1999). Propiedades físicas de los suelos de los Llanos Orientales y sus requerimientos de labranza. PALMAS, 20(1), 145–174. http://hdl.handle.net/20.500.12324/15962Amézquita, E., Indupalapati, R. I. M., Hoyos, P., Diego, M., Luis Fernando, C. and Jaime, B. (2007). Development of an arable layer: A key concept for better management of infertile tropical savanna soils.Amézquita, E., Rao, I. M., Rivera, M., Corrales, I. I. and Jaime H. Bernal. (2013). Sistemas Agropastoriles: Un Enfoque Integrado para el Manejo Sostenible de Oxisoles de los Llanos Orientales de Colombia.Arango, C., Dorado, J., Guzmán, D. and Ruíz, J. (2015). Variabilidad climática de la precipitación en Colombia asociada al ciclo el niño, la niña – oscilación del sur (ENSO) [Archivo PDF]. In IDEAM (pp. 103–111)Armenteras, D., Meza, M. C., González, T. M., Oliveras, I., Balch, J. K. and Retana, J. (2021). Fire threatens the diversity and structure of tropical gallery forests. Ecosphere, 12(1). https://doi.org/10.1002/ecs2.3347Attanasio, A., Pasini, A. and Triacca, U. (2013). Granger Causality Analyses for Climatic Attribution. Atmospheric and Climate Sciences, 03(04), 515–522. https://doi.org/10.4236/acs.2013.34054Barrios-Perez, C., Okada, K., Varón, G. G., Ramirez-Villegas, J., Rebolledo, M. C. and Prager, S. D. (2021). How does El Niño Southern Oscillation affect rice-producing environments in central Colombia? Agricultural and Forest Meteorology, 306(April). https://doi.org/10.1016/j.agrformet.2021.108443Bera, B., Shit, P. K., Sengupta, N., Saha, S. and Bhattacharjee, S. (2021). Trends and variability of drought in the extended part of Chhota Nagpur plateau (Singbhum Protocontinent), India applying SPI and SPEI indices. Environmental Challenges, 5(September), 100310. https://doi.org/10.1016/j.envc.2021.100310Bergstrom, S., Lindstrom, G., Johansson, B., Persson, M. and Gardelin, M. (1997). hydrological model. Journal of Hydrology, 201, 272–288.Beven, K. (2012). Rainfall-runoff modelling. In Fluid Mechanics, Hydraulics, Hydrology and Water Resources for Civil Engineers. https://doi.org/10.1201/9780429423116-33Blöschl, G., Bierkens, M. F. P., Chambel, A., Cudennec, C., Destouni, G., Fiori, A., Kirchner, J. W., McDonnell, J. J., Savenije, H. H. G., Sivapalan, M., Stumpp, C., Toth, E., Volpi, E., Carr, G., Lupton, C., Salinas, J., Széles, B., Viglione, A., Aksoy, H., … Zhang, Y. (2019). Twenty-three unsolved problems in hydrology (UPH)–a community perspective. Hydrological Sciences Journal, 64(10), 1141–1158. https://doi.org/10.1080/02626667.2019.1620507Bradford, J. B., Schlaepfer, D. R., Lauenroth, W. K., Palmquist, K. A., Chambers, J. C., Maestas, J. D. and Campbell, S. B. (2019). Climate-driven shifts in soil temperature and moisture regimes suggest opportunities to enhance assessments of dryland resilience and resistance. Frontiers in Ecology and Evolution, 7(SEP), 1–16. https://doi.org/10.3389/fevo.2019.00358Breuer, L., Huisman, J. A., Willems, P., Bormann, H., Bronstert, A., Croke, B. F. W., Frede, H. G., Gräff, T., Hubrechts, L., Jakeman, A. J., Kite, G., Lanini, J., Leavesley, G., Lettenmaier, D. P., Lindström, G., Seibert, J., Sivapalan, M. and Viney, N. R. (2009). Assessing the impact of land use change on hydrology by ensemble modeling (LUCHEM). I: Model intercomparison with current land use. Advances in Water Resources, 32(2), 129–146. https://doi.org/10.1016/j.advwatres.2008.10.003Bustamante, C. (2019). Gran Libro de la Orinoquia Colombiana. Instituto de Investigación de Recursos Biológicos Alexander von Humboldt - Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH. http://repository.humboldt.org.co/handle/20.500.11761/35408Caicedo, S., Campuzano, L. F., Hernández, A. C., Alfonso, H., Olarte, T. P., Pulido, S. X. and Jaramillo, C. A. (2012). Modelo productivo para el cultivo de maíz y soya en la Altillanura colombiana (Paquete Tecnológico). Siembra, 1–37. http://www.siembra.gov.co/siembra/GestionInnovacion2.aspxCaicedo, S. and Tibocha, Y. (2020). Corpoica Iraca 10: variedad de soya para suelos mejorados de altillanura plana, y vegas y vegones del piedemonte llanero. Corporación Colombiana de Investigación Agropecuaria (AGROSAVIA). In Editorial AGROSAVIA (p. 20 paginas).Caplan, J. S., Giménez, D., Hirmas, D. R., Brunsell, N. A., Blair, J. M. and Knapp, A. K. (2019). Decadal-scale shifts in soil hydraulic properties as induced by altered precipitation. Science Advances, 5(9), 1–10. https://doi.org/10.1126/sciadv.aau6635CEPAL, DNP and BID. (2012). Valoración de daños y pérdidas. Ola invernal en Colombia, 2010-2011. [Archivo PDF] (p. 240). http://hdl.handle.net/11362/37958Chapagain, R., Remenyi, T. A., Harris, R. M. B., Mohammed, C. L., Huth, N., Wallach, D., Rezaei, E. E. and Ojeda, J. J. (2022). Decomposing crop model uncertainty: A systematic review. Field Crops Research, 279(November 2021), 108448. https://doi.org/10.1016/j.fcr.2022.108448Chen, Z. and Grasby, S. E. (2009). Impact of decadal and century-scale oscillations on hydroclimate trend analyses. Journal of Hydrology, 365(1–2), 122–133. https://doi.org/10.1016/j.jhydrol.2008.11.031Chica, H., Peña Quiñones, A. J., Giraldo Jiménez, J. F., Obando Bonilla, D. and Riaño Herrera, N. M. (2014). SueMulador: Herramienta para la Simulación de Datos Faltantes en Series Climáticas Diarias de Zonas Ecuatoriales. Revista Facultad Nacional de Agronomía Medellín, 67(2), 7365–7373. https://doi.org/10.15446/rfnam.v67n2.44179Chica Ramirez, H. A., Gómez Gil, L. F., Bravo Bastidas, J. J., Carbonell González, J. A. and Peña Quiñones, A. J. (2021). Site-specific intra-annual rainfall patterns: a tool for agricultural planning in the Colombian sugarcane production zone. Theoretical and Applied Climatology, 146(1–2), 543–554. https://doi.org/10.1007/s00704-021-03755-1Choquet, P., Gabrielle, B., Chalhoub, M., Michelin, J., Sauzet, O., Scammacca, O., Garnier, P., Baveye, P. C. and Montagne, D. (2021). Comparison of empirical and process-based modelling to quantify soil-supported ecosystem services on the Saclay plateau (France). Ecosystem Services, 50(June). https://doi.org/10.1016/j.ecoser.2021.101332Chow, V., Maidment, D. and Mays, L. (1994). Hidrología aplicada. In Hidrologia aplicada (p. 575 pp). http://bases.bireme.br/cgi-bin/wxislind.exe/iah/online/?IsisScript=iah/iah.xis&src=google&base=REPIDISCA&lang=p&nextAction=lnk&exprSearch=158911&indexSearch=ID%5Cnhttp://www.sidalc.net/cgi-bin/wxis.exe/?IsisScript=BINAI.xis&method=post&formato=2&cantidad=CIAT and CORMACARENA. (2017). Plan Regional Integral de Cambio Climático para la Orinoquía. Centro Internacional de Agricultura Tropical (CIAT), Cali, Colombia., No. 438.438. CIAT, CORMACARENA, Corporinoquia and Ecopetrol. (2027). Plan Regional Integral de Cambio Climático para la Orinoquía - Resumen ejecutivo Cartilla. In Centro Internacional de Agricultura Tropical (CIAT) (Vol. 53, Issue 9). https://www.cambridge.org/core/product/identifier/CBO9781107415324A009/type/book_partCook, B. G. and Schultze-Kraft, R. (2015). Botanical name changes - Nuisance or a quest for precision? Tropical Grasslands-Forrajes Tropicales, 3(1), 34–40. https://doi.org/10.17138/TGFT(3)34-40Córdoba-Machado, S., Palomino-Lemus, R., Gámiz-Fortis, S. R., Castro-Díez, Y. and Esteban-Parra, M. J. (2015). Assessing the impact of El Niño Modoki on seasonal precipitation in Colombia. Global and Planetary Change, 124, 41–61. https://doi.org/10.1016/j.gloplacha.2014.11.003CORMACARENA. (2018). Plan de ordenamiento y manejo de la cuenca hidrografica Rio Negro. In Corporación Para El Desarrollo Sostenible del Área Manejo Especial la Macarena. Consorcio POMCA Río Negro 2018 (Vol. 10, Issue 1, pp. 279–288). http://dx.doi.org/10.1053/j.gastro.2014.05.023%0Ahttps://doi.org/10.1016/j.gie.2018.04.013%0Ahttp://www.ncbi.nlm.nih.gov/pubmed/29451164%0Ahttp://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC5838726%250Ahttp://dx.doi.org/10.1016/j.gie.2013.07.022Cornelissen, T., Diekkrüger, B. and Giertz, S. (2013). A comparison of hydrological models for assessing the impact of land use and climate change on discharge in a tropical catchment. Journal of Hydrology, 498, 221–236. https://doi.org/10.1016/j.jhydrol.2013.06.016Crow, W. T., Berg, A. A., Cosh, M. H., Loew, A., Mohanty, B. P., Panciera, R., De Rosnay, P., Ryu, D. and Walker, J. P. (2012). Upscaling sparse ground-based soil moisture observations for the validation of coarse-resolution satellite soil moisture products. Reviews of Geophysics, 50(2), 1–20. https://doi.org/10.1029/2011RG000372Cui, X. (2020). Climate change and adaptation in agriculture: Evidence from US cropping patterns. Journal of Environmental Economics and Management, 101, 102306. https://doi.org/10.1016/j.jeem.2020.102306da Silva, E. H. F. M., Gonçalves, A. O., Pereira, R. A., Fattori Júnior, I. M., Sobenko, L. R. and Marin, F. R. (2019). Soybean irrigation requirements and canopy-atmosphere coupling in Southern Brazil. Agricultural Water Management, 218(October 2018), 1–7. https://doi.org/10.1016/j.agwat.2019.03.003Dastane, N. G. (1978). Effective rainfall in irrigated agriculture. FAO Irrigation and Drainage Engineering, 4(1), 25.de la Casa, A. C., Ovando, G. G. and Díaz, G. J. (2021). ENSO influence on corn and soybean yields as a base of an early warning system for agriculture in Córdoba, Argentina. European Journal of Agronomy, 129(June). https://doi.org/10.1016/j.eja.2021.126340de Oliveira-Júnior, J. F., Mendes, D., Washington Luiz, F. C. F., da Silva Junior, C. A., de Gois, G., da Rosa Ferraz Jardim, A. M., Vinícius da Silva, M., Bastos Lyra, G., Teodoro, P. E., Gomes Pimentel, L. C., Lima, M., de Barros Sant, D. and Pereira Rogelio, J. (2021). Fire foci in South America: Impact and causes, fire hazard and future scenarios José. Journal of South American Earth Sciences, 1446(89), 2669. https://doi.org/10.1016/j.jsames.2021.103623Delerce, S., Dorado, H., Grillon, A., Rebolledo, M. C., Prager, S. D., Patiño, V. H., Varón, G. G. and Jiménez, D. (2016). Assessing weather-yield relationships in rice at local scale using data mining approaches. PLoS ONE, 11(8). https://doi.org/10.1371/journal.pone.0161620Devia, G. K., Ganasri, B. P. and Dwarakish, G. S. (2015). A Review on Hydrological Models. Aquatic Procedia, 4(Icwrcoe), 1001–1007. https://doi.org/10.1016/j.aqpro.2015.02.126Doeffinger, T. and Hall, J. W. (2021). Assessing water security across scales: A case study of the United States. Applied Geography, 134(June), 102500. https://doi.org/10.1016/j.apgeog.2021.102500Dogan, E. (2019). Effect of supplemental irrigation on vetch yield components. Agricultural Water Management, 213(August 2018), 978–982. https://doi.org/10.1016/j.agwat.2018.12.013Dunkerley, D. (2010). Effects of rainfall intensity fluctuations on infiltration and runoff: rainfall simulation on dryland soils, Fowlers Gap, Australia. Okt 2005 Abrufbar Uber Httpwww Tldp OrgLDPabsabsguide Pdf Zugriff 1112 2005, 2274(November 2008), 2267–2274. https://doi.org/10.1002/hypDunkerley, D. (2015). Intra-event intermittency of rainfall: an analysis of the metrics of rain and no-rain periods. Hydrological Processes, 29(15), 3294–3305. https://doi.org/10.1002/hyp.10454Dutta, P. and Sarma, A. K. (2021). Hydrological modeling as a tool for water resources management of the data-scarce brahmaputra basin. Journal of Water and Climate Change, 12(1), 152–165. https://doi.org/10.2166/wcc.2020.186Easterbrook, D. J. (2011). Evidence-Based Climate Science. In New York.Easterbrook, D. J. (2016). Evidence-Based Climate Science: Data Opposing CO2 Emissions as the Primary Source of Global Warming: Second Edition. In Evidence-Based Climate Science: Data Opposing CO2 Emissions as the Primary Source of Global Warming: Second Edition.Egerer, S., Cotera, R. V., Celliers, L. and Costa, M. M. (2021). A leverage points analysis of a qualitative system dynamics model for climate change adaptation in agriculture. Agricultural Systems, 189(February 2020). https://doi.org/10.1016/j.agsy.2021.103052Espinel, C., Rios, H., Palacino, J. and Arevalo, E. (2020). INFORME LANGOSTA LLANERA ( Rhammatocerus schistocercoides ) EN EL Contexto En Colombia se reporta la langosta llanera Rhammatocerus schistocercoides ( Rehn , 1906 ) es “ autóctona de la Orinoquía colombo-venezolana . Desde junio estados no voladores ( nin. ICA.Esquivel, A., Llanos-Herrera, L., Agudelo, D., Prager, S. D., Fernandes, K., Rojas, A., Valencia, J. J. and Ramirez-Villegas, J. (2018). Predictability of seasonal precipitation across major crop growing areas in Colombia. Climate Services, 12(September), 36–47. https://doi.org/10.1016/j.cliser.2018.09.001FAO. (2015). AQUASTAT - Sistema mundial de información de la FAO sobre el agua en la agricultura. https://www.fao.org/aquastat/statistics/query/results.html%0AFAO. (2018). Progresos en el nivel de estrés hídrico: valores de referencia mundiales para el indicador 6.4.2 de los ODS. Roma. FAO y ONU-Agua. 58 pp. Licencia: CC BY-NC-SA 3.0 IGOFebruary, E. C. and Higgins, S. I. (2010). The distribution of tree and grass roots in savannas in relation to soil nitrogen and water. South African Journal of Botany, 76(3), 517–523. https://doi.org/10.1016/j.sajb.2010.04.001Felipe, A. and Montoya, H. (2016). Cambio Climático Y Variabilidad Espacio – Temporal De La Precipitación En Colombia Climate Change and Space-Time Variability of the Precipitation in Colombia As Alterações Climáticas E a Variabilidade Espaço – Temporal Da Chuva Tempo Na Colômbia. Revista EIA, 12(574), 131–150.Feng, S., Hao, Z., Zhang, X. and Hao, F. (2021). Changes in climate-crop yield relationships affect risks of crop yield reduction. Agricultural and Forest Meteorology, 304–305(19), 108401. https://doi.org/10.1016/j.agrformet.2021.108401Fontanilla-Díaz, C. A., Preckel, P. V., Lowenberg-DeBoer, J., Sanders, J. and Peña-Lévano, L. M. (2021). Identifying profitable activities on the frontier: The Altillanura of Colombia. Agricultural Systems, 192(May). https://doi.org/10.1016/j.agsy.2021.103199Gallo, O., Bernal, J., Baquero, J., Botero, R. and Gómez, J. (2013). Effect of Three Systems of Incorporation of Dolomite Limestone in the Colombian Flat Plains. Suelos Ecuatoriales Sociedad Colombiana de La Ciencia Del Suelo, 43(1), 24–28.Galvis, J. H., Amézquita Collazos, E. and Madero M., E. (2007). Evaluación del efecto de la intensidad de labranza en la formación de costra superficial de un oxisol de sabana en los Llanos Orientales de Colombia : II. Caracterización física en superficie = Evaluation of harrowing intensity on surface crusting on an o. Acta Agronómica (Colombia), 57(2008), 56(4):191-194. http://www.revistas.unal.edu.co/index.php/acta_agronomica/article/viewFile/1030/1504Galvis Quintero, J. H., Anaya, O. C., Bernal Riobo, J. H. and Baquero, J. E. (2018). Evaluación de la estabilidad estructural y espacio poroso en un Oxisol de sabana de los Llanos Orientales de Colombia. Journal of Physical Therapy Science, 9(1), 1–11. http://dx.doi.org/10.1016/j.neuropsychologia.2015.07.010%0Ahttp://dx.doi.org/10.1016/j.visres.2014.07.001%0Ahttps://doi.org/10.1016/j.humov.2018.08.006%0Ahttp://www.ncbi.nlm.nih.gov/pubmed/24582474%0Ahttps://doi.org/10.1016/j.gaitpost.2018.12.007%0Ahttps:Gao, F., Wang, Y., Chen, X. and Yang, W. (2020). Trend analysis of rainfall time series in Shanxi province, Northern China (1957-2019). Water (Switzerland), 12(9), 1–22. https://doi.org/10.3390/W12092335Guo, D., Thomas, J., Lazaro, A. B., Matwewe, F. and Johnson, F. (2021). Modelling the influence of short-term climate variability on drinking water quality in tropical developing countries: A case study in Tanzania. Science of the Total Environment, 763, 142932. https://doi.org/10.1016/j.scitotenv.2020.142932Gupta, V. and Jain, M. K. (2021). Unravelling the teleconnections between ENSO and dry/wet conditions over India using nonlinear Granger causality. Atmospheric Research, 247(July 2020), 105168. https://doi.org/10.1016/j.atmosres.2020.105168Guzman, C. D., Hoyos-Villada, F., Da Silva, M., Zimale, F. A., Chirinda, N., Botero, C., Morales Vargas, A., Rivera, B., Moreno, P. and Steenhuis, T. S. (2019). Variability of soil surface characteristics in a mountainous watershed in Valle del Cauca, Colombia: Implications for runoff, erosion, and conservation. Journal of Hydrology, 576(June), 273–286. https://doi.org/10.1016/j.jhydrol.2019.06.002Hajimirzajan, A., Vahdat, M., Sadegheih, A., Shadkam, E. and Bilali, H. El. (2021). An integrated strategic framework for large-scale crop planning: sustainable climate-smart crop planning and agri-food supply chain management. Sustainable Production and Consumption, 26, 709–732. https://doi.org/10.1016/j.spc.2020.12.016Hamed, K. H. (2008). Trend detection in hydrologic data: The Mann-Kendall trend test under the scaling hypothesis. Journal of Hydrology, 349(3–4), 350–363. https://doi.org/10.1016/j.jhydrol.2007.11.009Hao, Y., Hao, Z., Feng, S., Zhang, X. and Hao, F. (2020). Response of vegetation to El Niño-Southern Oscillation (ENSO) via compound dry and hot events in southern Africa. Global and Planetary Change, 195(19), 103358. https://doi.org/10.1016/j.gloplacha.2020.103358He, Z., Zhao, W., Liu, H. and Chang, X. (2012). The response of soil moisture to rainfall event size in subalpine grassland and meadows in a semi-arid mountain range: A case study in northwestern China’s Qilian Mountains. Journal of Hydrology, 420–421, 183–190. https://doi.org/10.1016/j.jhydrol.2011.11.056Hébert-Dufresne, L., Pellegrini, A. F. A., Bhat, U., Redner, S., Pacala, S. W. and Berdahl, A. M. (2018). Edge fires drive the shape and stability of tropical forests. Ecology Letters, 21(6), 794–803. https://doi.org/10.1111/ele.12942Hillel, D. (1998). Environmental Soil Physics: Fundamentals, Applications, and Environmental Considerations. Academic Press, Waltham.Hoyos, N., Escobar, J., Restrepo, J. C., Arango, A. M. and Ortiz, J. C. (2013). Impact of the 2010-2011 La Niña phenomenon in Colombia, South America: The human toll of an extreme weather event. Applied Geography, 39(September 2011), 16–25. https://doi.org/10.1016/j.apgeog.2012.11.018Huertas, H. D., Rangel, J. A. and Parra, A. S. (2018). Chemical characterization of soil fertility in production systems of a flat High Plateau, Meta, Colombia. Revista Luna Azul, 46(46), 54–69. https://doi.org/10.17151/luaz.2018.46.5Ibrahim, M. A. and Johansson, M. (2021). Attitudes to climate change adaptation in agriculture – A case study of Öland, Sweden. Journal of Rural Studies, 86(March), 1–15. https://doi.org/10.1016/j.jrurstud.2021.05.024ICA. (2011). Resolucion 2705.pdf (p. 2). https://www.ica.gov.co/getattachment/513310fc-449e-4330-a0bc-5e226eb1e9a1/Cultivo-del-Arroz.aspxIDEAM. (2005). Atlas Climatológico de Colombia. Instituto De Hidrología, Meteorología Y Estudios Ambientales - Ideam, 78.IDEAM. (2012). Sequía meteorológica y sequía agícola en Colombia: incidencia y tendencias. 49. http://www.ideam.gov.co/documents/21021/21138/Sequias+Incidencias+y+Tendencias.pdf/3e72c86c-cf4a-42f9-95f1-07e7cf88861aIDEAM. (2013). Zonificación y codificación de uniades hidrográficas e hidrogeológicas de Colombia. Publicación Aprobada Por El Comité de Comunicaciones y Publicaciones Del IDEAM, 47. http://documentacion.ideam.gov.co/openbiblio/bvirtual/022655/MEMORIASMAPAZONIFICACIONHIDROGRAFICA.pdfIDEAM. (2015). Mapa de Coberturas de la Tierra Metodología Corine Land Cover Adaptada para Colombia Escala 1:100.000 (Período 2010 - 2012) (p. 117). http://documentacion.ideam.gov.co/openbiblio/bvirtual/023236/IEARN_segunda_parte_ecosistemas_2014.pdfIDEAM. (2016). Conocer: El primer paso para adaptarse. Guía básica de conceptos sobre el cambio climático. In Tercera Comunicación Nacional de Cambio Climático. http://documentacion.ideam.gov.co/openbiblio/bvirtual/023631/ABC.pdfIDEAM. (2017a). Atlas climatologico de Colombia [PDF]. Instituto de Hidrología, Meteorología y Estudios Ambientales. http://documentacion.ideam.gov.co/openbiblio/bvirtual/023777/CLIMA.pdfIDEAM. (2017b). Diseñode la Red Hidrometeorológica Nacional. 1–16. http://sgi.ideam.gov.co/documents/412030/561097/M-GDI-H-G001+GUÍA+DISEÑO+DE+LA+RED+HIDROMETEOROLÓGICA+NACIONAL.pdf/9da0e118-58cc-43eb-87e0-8c6316dc691c?version=1.0#:~:text=El IDEAM opera una red,satelital o vía celular%2C GPRS.IDEAM. (2018). Protocolo de Modelacion Hidrológica e Hidráulica. In Instituto de Hidrología, Meteorología y Estudios Ambientales – IDEAM. http://documentacion.ideam.gov.co/openbiblio/bvirtual/023833/Protocolo_Modelacion_HH.pdfcIDEAM. (2019a). DHIME - Manual de Usuario Consulta y Descarga de datos hidrometeorológicos - IDEAM. Manual, 53.IDEAM. (2019b). Estudio Nacional del Agua 2018. Bogotá: Ideam: 452 pp. http://www.andi.com.co/Uploads/ENA_2018-comprimido.pdfIDEAM and UNAL. (2018). Variabilidad climática y el cambio climático en Colombia [Archivo PDF]. In Instituto de Hidrología, Meteorología y Estudios Ambientales – IDEAM Universidad Nacional de Colombia – UNAL (p. 28). http://documentacion.ideam.gov.co/openbiblio/bvirtual/023778/variabilidad.pdfIGAC. (1973). Reconocimiento semidetallado de suelos del C.I La Libertad (Departamento del Meta) Intituto Geografico Agustin Codazzi.IGAC. (2004). Estudio general de suelos y zonificación de tierras del departamento de Meta. Instituto Geografico Agustin Codazzi, 9067.IGAC. (2017). Instructivo: Etapa de campo para leventamiento de suelos, Grupo interno de trabajo de levantamiento de suelos y aplicaciones agrologicas [PDF]. http://igacnet2.igac.gov.co/intranet/UserFiles/File/DOCUMENTOS SGI 2021/GAG/PC-GAG-05/IN-GAG-PC05-09 Etapa de campo para levantamientos de suelos.pdfIGAC. (2018). Sistema de clasificacion geomorfologica aplicado a los levantamientos de suelos, Instituto Geográfico Agustín Codazzi. Subdirección de Agrología.IPCC. (2007). Cambio climático 2007: Informe de síntesis. Contribución de los Grupos de trabajo I, II y III al Cuarto Informe de evaluación del Grupo Intergubernamental de Expertos sobre el Cambio Climático [Equipo de redacción principal: Pachauri, R.K. y Reisinger, A. In Proceedings of the Mediterranean Electrotechnical Conference - MELECON. https://doi.org/10.1109/MELCON.2008.4618473IPCC. (2014). Cambio climático 2014: Informe de Síntesis. In Contribución de los Grupos de trabajo I,II y III al Quinto Informe de Evaluación del Grupo Intergubernamental de Expertos sobre el Cambio Climático [Equipo principal de redacción, R.K. Pachauri y L.A. Meyer (eds.)]. IPCC, Ginebra, Suiza. https://www.ipcc.ch/site/assets/uploads/2018/02/SYR_AR5_FINAL_full_es.pdfIPCC. (2018). Glosario [Matthews J.B.R. (ed.)]. En: Calentamiento global de 1,5 °C, Informe especial del IPCC sobre los impactos del calentamiento global de 1,5 oC con respecto a los niveles preindustriales y las trayectorias correspondientes que deberían seguir las em. https://www.ipcc.ch/site/assets/uploads/sites/2/2019/10/SR15_Glossary_spanish.pdfIPCC. (2020). El cambio climático y la tierra. In Grupo Intergubernamental de Expertos sobre el Cambio Climático. https://www.ipcc.ch/site/assets/uploads/sites/4/2020/06/SRCCL_SPM_es.pdfJia, Y. (2011). Coupling crop growth and hydrologic models to predict crop yield with spatial analysis technologies. Journal of Applied Remote Sensing, 5(1), 053537. https://doi.org/10.1117/1.3609844Kamble, P. S., Maniyar, V. G. and Jadhav, J. D. (2010). Crop coefficients (Kc) of soybean [Glycine max (L.) Merrill]. Asian Journal of Environmental Science, 5(2), 131–135.Krinitskiy, M., Grashchenkov, K., Tilinina, N. and Gulev, S. (2021). Tracking of atmospheric phenomena with artificial neural networks: A supervised approach. Procedia Computer Science, 186, 403–410. https://doi.org/10.1016/j.procs.2021.04.209Kundzewicz, Z. W., Huang, J., Pinskwar, I., Su, B., Szwed, M. and Jiang, T. (2020). Climate variability and floods in China - A review. Earth-Science Reviews, 211(February), 103434. https://doi.org/10.1016/j.earscirev.2020.103434Lafitte, H. R. (1994). Guia de campo: Identificación de problemas en la producción de maíz tropical [PDF]. CIMMYT, 122. https://repository.cimmyt.org/bitstream/handle/10883/727/43157.pdf?sequence=1&isAllowed=yLal, R. and Shukla, M. K. (2005). Principles of soil physics, The Ohio State University Columbus, Ohio, U.S.A. In Mercel Dekker, INC. New York, Basel (Vol. 4, Issue March). https://dewagumay.files.wordpress.com/2011/12/principles-of-soil-physics.pdfLeon, G., Arcila, A., Pulido, L. A. and Kondo, T. (2018). Capítulo 25 Contenido Cambio climático y control biológico de insectos : visión y perspectiva de la situación Chapter 25 Climate change and biological control of insects : current situation and perspectives. In Control biológico de fitopatógenos, insectos y ácaros (Issue October, p. 572).Lesk, C., Rowhani, P. and Ramankutty, N. (2016). Influence of extreme weather disasters on global crop production. Nature, 529(7584), 84–87. https://doi.org/10.1038/nature16467Li, F., Li, W., Li, F., Long, Y., Guo, S., Li, X., Lin, C. and Li, J. (2022). Global projections of future wilderness decline under multiple IPCC Special Report on Emissions Scenarios. Resources, Conservation and Recycling, 177(June 2021), 105983. https://doi.org/10.1016/j.resconrec.2021.105983Li, X., Zhang, K., Gu, P., Feng, H., Yin, Y., Chen, W. and Cheng, B. (2021). Changes in precipitation extremes in the Yangtze River Basin during 1960–2019 and the association with global warming, ENSO, and local effects. Science of the Total Environment, 760, 144244. https://doi.org/10.1016/j.scitotenv.2020.144244Limami, A. M., Diab, H. and Lothier, J. (2014). Nitrogen metabolism in plants under low oxygen stress. Planta, 239(3), 531–541. https://doi.org/10.1007/s00425-013-2015-9Liu, J., Liang, Y., Gao, G., Dunkerley, D. and Fu, B. (2022). Quantifying the effects of rainfall intensity fluctuation on runoff and soil loss: From indicators to models. Journal of Hydrology, 607(February 2021), 127494. https://doi.org/10.1016/j.jhydrol.2022.127494Loaiza, J. and Pauwels, V. (2008). Utilizacion de sensores de humedad para la determinacion del contenido de humedad del suelo (Ecuaciones de Calibración). Suelos Ecuatoriales Sociedad Colombiana de La Ciencia Del Suelo, 38(1), 24–33.Loaiza, J., Poch, R. and Pauwels, V. (2010). Evaluation of soil water moisture regime prediction methods in the mountain region of Catalan Pre-Pyrenees. Suelos Ecuatoriales Sociedad Colombiana de La Ciencia Del Suelo, 40(1), 38–50.López, J. J., Goñi, M., San Martín, I. and Erro, J. (2019). Análisis regional de frecuencias de las precipitaciones diarias extremas en Navarra. Elaboración de los mapas de cuantiles. Ingeniería Del Agua, 23(1), 33. https://doi.org/10.4995/ia.2019.10058Lozano, E. (2014). Compilación de la cuenca de los Llanos Orientales. Servicio Geológico Colombiano, 1(Diciembre), 5–9.Lu, B., Li, H., Wu, J., Zhang, T., Liu, J., Liu, B., Chen, Y. and Baishan, J. (2019). Impact of El Niño and Southern Oscillation on the summer precipitation over Northwest China. Atmospheric Science Letters, 20(8), 1–8. https://doi.org/10.1002/asl.928Ma, Y. jun, Li, X. yan, Guo, L. and Lin, H. (2017). Hydropedology: Interactions between pedologic and hydrologic processes across spatiotemporal scales. Earth-Science Reviews, 171(19), 181–195. https://doi.org/10.1016/j.earscirev.2017.05.014Manfreda, S. and Rodríguez-Iturbe, I. (2006). On the spatial and temporal sampling of soil moisture fields. Water Resources Research, 42(5), 2757–2760. https://doi.org/10.1029/2005WR004548Martineli, A., Leonel, P., Fabíola, N. and Giarola, B. (2020). Rhizosphere Evaluation of the soil aggregation induced by the plant roots in an Oxisol by turbidimetry and water percolation. Rhizosphere, 16(October), 100265. https://doi.org/10.1016/j.rhisph.2020.100265McGraw, M. C. and Barnes, E. A. (2018). Memory matters: A case for granger causality in climate variability studies. Journal of Climate, 31(8), 3289–3300. https://doi.org/10.1175/JCLI-D-17-0334.1Meran, G., Siehlow, M. and Hirschhausen, C. von. (2021). The Economics of War. In New Perspectives Quarterly (Vol. 18, Issue 4, pp. 48–50). https://doi.org/10.1111/0893-7850.00441Meshesha, T. W. and Khare, D. (2019). Towards integrated water resources management considering hydro-climatological scenarios: an option for sustainable development. Environmental Systems Research, 8(1). https://doi.org/10.1186/s40068-019-0134-4Mesri, M., Ghilane, A. and Bachari, N. E. I. (2013). An approach to spatio-temporal analysis for climatic data. Revue Des Energies Renouvelables, 16, 413–424.Milella, P., Bisantino, T., Gentile, F., Iacobellis, V. and Trisorio Liuzzi, G. (2012). Diagnostic analysis of distributed input and parameter datasets in Mediterranean basin streamflow modeling. Journal of Hydrology, 472–473, 262–276. https://doi.org/10.1016/j.jhydrol.2012.09.039MINAMBIENTE. (2010). Política Nacional para la Gestión Integral del Recurso Hídrico. Bogotá, D.C.: Colombia [PDF]. Ministerio de Ambiente, Vivienda y Desarrollo Territorial, 124. https://www.minambiente.gov.co/wp-content/uploads/2021/10/Politica-nacional-Gestion-integral-de-recurso-Hidrico-web.pdfMINAMBIENTE. (2014). Guía Técnica para la formulación de los Planes de Ordenamiento y Manejo de Cuencas Hidrograficas POMCAS [PDF]. Ministerio de Medio Ambiente y Desarrollo Sostenible, 104. https://repositorio.gestiondelriesgo.gov.co/bitstream/handle/20.500.11762/22585/1-Guia_Tecnica_pomcas-MinAmbiente-2014.pdf?sequence=1&isAllowed=yMunar, A. M., Cavalcanti, J. R., Bravo, J. M., Fan, F. M., Motta-Marques, D. da and Fragoso, C. R. (2018). Coupling large-scale hydrological and hydrodynamic modeling: Toward a better comprehension of watershed-shallow lake processes. Journal of Hydrology, 564(March), 424–441. https://doi.org/10.1016/j.jhydrol.2018.07.045Norel, M., Kałczyński, M., Pińskwar, I., Krawiec, K. and Kundzewicz, Z. W. (2021). Climate variability indices—a guided tour. Geosciences (Switzerland), 11(3), 1–27. https://doi.org/10.3390/geosciences11030128OMM. (2008). Guía de prácticas hidrológicas. Volumen II. Gestión de recursos hídricos y aplicación de prácticas hidrológicas. https://library.wmo.int/index.php?lvl=notice_display&id=9404#.X10SsWgzbDcOMM. (2011). Guía de Prácticas Hidrológicas Volumen I. In World Meteorological Organization, No. 168. http://www.wmo.int/pages/prog/hwrp/publications/guide/spanish/168_Vol_I_es.pdfOMM. (2014). El Niño/Oscilación del Sur. Organización Meteorológica Mundial Tiempo-Clima-Agua, N°1145, 12. https://library.wmo.int/doc_num.php?explnum_id=7889Orduz, J. and Fischer, G. (2007). Balance hídrico e influencia del estrés hídrico en la inducción y desarrollo floral de la mandarina ‘Arrayana’ en el piedemonte llanero de Colombia. Agronomía Colombiana, 25(2), 255–263.Orozco Jamioy, D. D., Menjivar Flores, J. C. and Rubiano Sanabria, Y. (2015). Indicadores químicos de calidad de suelos en sistemas productivos del Piedemonte de los Llanos Orientales de. Acta Agronomica, 64, 302–307.Panagos, P., Standardi, G., Borrelli, P., Lugato, E., Montanarella, L. and Bosello, F. (2018). Cost of agricultural productivity loss due to soil erosion in the European Union: From direct cost evaluation approaches to the use of macroeconomic models. Land Degradation and Development, 29(3), 471–484. https://doi.org/10.1002/ldr.2879Paoletti, J. M. and Shortridge, J. E. (2020). Improved representation of uncertainty in farm-level financial cost-benefit analyses of supplemental irrigation in humid regions. Agricultural Water Management, 239(June 2019), 106245. https://doi.org/10.1016/j.agwat.2020.106245Pardo, O., Torres, H., Trujillo, G. and Trujillo, J. (2020). Impactos del cambio climatico sobre los rendiemientos del Arroz (Oryza sativa L) en la zona llanos, Colombia [PDF]. AGLALA ISSN 2215-7360, 11(2), 94–106. https://revistas.curn.edu.co/index.php/aglala/article/view/1698Peña, A., Jaramillo R, Á. and Paternina Q, M. J. (2011). Detecting low frequency cycles in rainfall series from Colombian coffee-growing area by using descriptive methods. Earth Sciences Research Journal, 15(2), 109–114.Perez, R. A. (1992). Pasto Humidicola. Bolétin Técnico, 181, 14. http://ciat-library.ciat.cgiar.org/Articulos_Ciat/Digital/ICA_000041C.2_Pasto_humidicola_Brachiaria_humidicola_Rendle_Schweickt.pdfPla Sentis, I. (2016). Nuevos enfoques para el manejo y conservacion de suelos y agua en sistemas agricolas y medio ambientales. Suelos Ecuatoriales Sociedad Colombiana de La Ciencia Del Suelo, 46(1 y 2), 101–111.Poveda, G., Álvarez, D. M. and Rueda, Ó. A. (2011). Hydro-climatic variability over the Andes of Colombia associated with ENSO: A review of climatic processes and their impact on one of the Earth’s most important biodiversity hotspots. Climate Dynamics, 36(11–12), 2233–2249. https://doi.org/10.1007/s00382-010-0931-yPoveda, G., Espinoza, J. C., Zuluaga, M. D., Solman, S. A., Garreaud, R. and van Oevelen, P. J. (2020). High Impact Weather Events in the Andes. Frontiers in Earth Science, 8(May), 1–32. https://doi.org/10.3389/feart.2020.00162Praveen, B., Talukdar, S., Shahfahad, Mahato, S., Mondal, J., Sharma, P., Islam, A. R. M. T. and Rahman, A. (2020). Analyzing trend and forecasting of rainfall changes in India using non-parametrical and machine learning approaches. Scientific Reports, 10(1), 1–21. https://doi.org/10.1038/s41598-020-67228-7Pringle, G. (2017). Maize production: Managing critical plant growth stages. https://www.farmersweekly.co.za/crops/field-crops/maize-production-managing-critical-plant-growth-stages/Rahman, A., Kuddus, M. A., Ip, R. H. L. and Bewong, M. (2021). A review of covid‐19 modelling strategies in three countries to develop a research framework for regional areas. Viruses, 13(11), 1–23. https://doi.org/10.3390/v13112185Ramirez C., C., Vélez U., J. J. and Peña Q., A. J. (2018). Analizando índices climáticos para predecir la lluvia mensual en una región agrícola de los andes del norte (Caldas, Colombia). Investigaciones Geográficas, 55, 111. https://doi.org/10.5354/0719-5370.2018.48460Ramírez, N. E., Munar, D., van der Hilst, F., Espinosa, J. C., Ocampo-Duran, Á., Ruíz-Delgado, J., Molina-López, D. L., Wicke, B., Garcia-Nunez, J. A. and Faaij, A. P. C. (2021). Ghg balance of agricultural intensification & bioenergy production in the orinoquia region, colombia. Land, 10(3), 1–30. https://doi.org/10.3390/land10030289Randall, M., Montgomery, J. and Lewis, A. (2022). Robust temporal optimisation for a crop planning problem under climate change uncertainty. Operations Research Perspectives, 9(October 2021), 100219. https://doi.org/10.1016/j.orp.2021.100219Ray, D. K., Gerber, J. S., Macdonald, G. K. and West, P. C. (2015). Climate variation explains a third of global crop yield variability. Nature Communications, 6, 1–9. https://doi.org/10.1038/ncomms6989Refsgaard, J. C. and Knudsen, J. (1996). Operational validation and intercomparison of different types of hydrological models. Water Resources Research, 32(7), 2189–2202. https://doi.org/10.1029/96WR00896Rial, A., Lasso, C. A. and Colonnello, G. (2016). Clasificación de los paisajes de la Orinoquia. Colombia y Venezuela. XI. Humedales de La Orinoquia (Colombia- Venezuela). Serie Editorial Recursos Hidrobiológicos y Pesqueros Continentales de Colombia, January 2014, 35–49.Ricaurte, J., Idupalapati, R. and Menjivar, J. C. (2007). Estrategias de enraizamiento de genotipos Brachiaria en suelos acidos y de baja fertilidad en Colombia. Acta Agronomica, 56(3), 107–115.Rincón, Á., Flórez, H., Ballesteros, H. and León, L. M. (2018). Effects of fertilization of Brachiaria humidicola cv. Llanero on pasture productivity in the foothills region of the Llanos Orientales, Colombia. Tropical Grasslands-Forrajes Tropicales, 6(3), 158–168. https://doi.org/10.17138/TGFT(6)158-168Robinson, D. A., Jones, S. B., Lebron, I., Reinsch, S., Domínguez, M. T., Smith, A. R., Jones, D. L., Marshall, M. R. and Emmett, B. A. (2016). Experimental evidence for drought induced alternative stable states of soil moisture. Scientific Reports, 6(September 2015), 1–6. https://doi.org/10.1038/srep20018Rodriguez, N. S., Lavelle, P., Pulido, S. X., Gutierrez, A., Bernal, J. H., Arguello, O., Botero, C., Gomez, Y., Hurtado, M. del P., Loaiza, S. P. and Rodriguez, E. (2013). Construcción de indicadores de ecoeficiencia para la altillanura plana en los municipios de Puerto López y Puerto Gaitán, departamento del Meta. Villavicencio (Colombia). CORPOICA, 40.Sánchez Ortega, J. M. (2021). Evaluación del transporte de humedad atmosférica desde el océano Atlántico hacia las cuencas del Orinoco y el norte del Amazonas durante el año 2010 mediante el modelo WRF-Tracers [Tesis de Ingenieria Ambiental]. In Universidad de Antioquia. https://bibliotecadigital.udea.edu.co/bitstream/10495/19697/1/SanchezJuan_2021_EvalucionTransporteHumedad.pdfSarkar, S., Zhu, X., Melnykov, V. and Ingrassia, S. (2020). On parsimonious models for modeling matrix data. Computational Statistics and Data Analysis, 142, 106822. https://doi.org/10.1016/j.csda.2019.106822Seibert, J. and Vis, M. J. P. (2012). Teaching hydrological modeling with a user-friendly catchment-runoff-model software package. 3315–3325. https://doi.org/10.5194/hess-16-3315-2012Sen, P. K. (1968). Estimates of the Regression Coefficient Based on Kendall’s Tau. Journal of the American Statistical Association, 63(324), 1379–1389. https://doi.org/10.1080/01621459.1968.10480934Seneviratne, S. I., Corti, T., Davin, E. L., Hirschi, M., Jaeger, E. B., Lehner, I., Orlowsky, B. and Teuling, A. J. (2010). Investigating soil moisture-climate interactions in a changing climate: A review. Earth-Science Reviews, 99(3–4), 125–161. https://doi.org/10.1016/j.earscirev.2010.02.004Sharifi, A., Mirabbasi, R., Ali Nasr-Esfahani, M., Torabi Haghighi, A. and Fatahi Nafchi, R. (2021). Quantify the impacts of anthropogenic changes and climate variability on runoff changes in central plateau of Iran using nine methods. Journal of Hydrology, 603(PC), 127045. https://doi.org/10.1016/j.jhydrol.2021.127045Sheikh Goodarzi, M., Jabbarian Amiri, B., Azarnivand, H. and Waltner, I. (2021). Watershed hydrological modelling in data scarce regions; integrating ecohydrology and regionalization for the southern Caspian Sea basin, Iran. Heliyon, 7(4), e06833. https://doi.org/10.1016/j.heliyon.2021.e06833Shiklomanov, I. A. (2000). Appraisal and Assessment of world water resources. Water International, 25(1), 11–32. https://doi.org/10.1080/02508060008686794Shiklomanov, I. A. and Rodda, J. C. (2004). World water resources at the beginning of the twenty-first century. Choice Reviews Online, 41(07), 41-4063-41–4063. https://doi.org/10.5860/choice.41-4063Solomatine, D. P. and Wagener, T. (2011). Hydrological Modeling. Treatise on Water Science, 2, 435–457. https://doi.org/10.1016/B978-0-444-53199-5.00044-0Stephens, E. C., Jones, A. D. and Parsons, D. (2018). Agricultural systems research and global food security in the 21st century: An overview and roadmap for future opportunities. Agricultural Systems, 163, 1–6. https://doi.org/10.1016/j.agsy.2017.01.011Sun, H., Shen, Y., Yu, Q., Flerchinger, G. N., Zhang, Y., Liu, C. and Zhang, X. (2010). Effect of precipitation change on water balance and WUE of the winter wheat-summer maize rotation in the North China Plain. Agricultural Water Management, 97(8), 1139–1145. https://doi.org/10.1016/j.agwat.2009.06.004Sun, X., Renard, B., Thyer, M., Westra, S. and Lang, M. (2015). A global analysis of the asymmetric effect of ENSO on extreme precipitation. Journal of Hydrology, 530, 51–65. https://doi.org/10.1016/j.jhydrol.2015.09.016Tao, F., Rötterb, R., Palosuo, T., Díaz, C. G. H., -Ambrona, C, Mínguez, M. I., C, Mikhail, Semenov, A., D, Kersebaum, K. C., E, Nendel, C., E, Specka, X., E, Hoffmann, H., F, … A, J. (2016). Contribution of crop model structure, parameters and climate projections to uncertaint y in climate change impact assessments. In International Journal of Laboratory Hematology (Vol. 38, Issue 1). https://doi.org/10.1111/ijlh.12426Tapiero, A., Caicedo, S., Baquero, J., Ospina, Y., Guimaraes, E. and Chatel, M. (2012). Arroz Corpoica Llanura 11.Tardieu, F., Draye, X. and Javaux, M. (2017). Root Water Uptake and Ideotypes of the Root System: Whole-Plant Controls Matter. Vadose Zone Journal, 16(9), vzj2017.05.0107. https://doi.org/10.2136/vzj2017.05.0107Thomas, W., Angarita, H. and Delgado, J. (2015). Hacia una gestión integral de la Cuenca y planicies inundables del Magdalena-Cauca. Foro Público: Para Dónde va El Río Magdalena -Foro Nacional Ambiental, 22.Tian, Q., Lu, J. and Chen, X. (2022). A novel comprehensive agricultural drought index reflecting time lag of soil moisture to meteorology: A case study in the Yangtze River basin, China. Catena, 209(P1), 105804. https://doi.org/10.1016/j.catena.2021.105804Trnka, M., Vizina, A., Hanel, M., Balek, J., Fischer, M., St, P., Hlavinka, P., Semer, D., Zahradní, P., Skal, P., Monika, B., Eitzinger, J., Dubrovský, M. and Petr, M. (2022). Increasing available water capacity as a factor for increasing drought resilience or potential conflict over water resources under present and future climate conditions. 264(August 2020).Urrea, V., Ochoa, A. and Mesa, O. (2019). Seasonality of Rainfall in Colombia. Water Resources Research, 55(5), 4149–4162. https://doi.org/10.1029/2018WR023316USDA. (2014). Keys to soil taxonomy. United States Department of Agriculture Natural Resources Conservation Service, 12, 410. http://www.nrcs.usda.gov/Internet/FSE_DOCUMENTS/nrcs142p2_051546.pdfVan Loon, A. F. (2015). Hydrological drought explained. WIREs Water, 2(4), 359–392. https://doi.org/10.1002/wat2.1085Van Nguyen, L., Takahashi, R., Githiri, S. M., Rodriguez, T. O., Tsutsumi, N., Kajihara, S., Sayama, T., Ishimoto, M., Harada, K., Suematsu, K., Abiko, T. and Mochizuki, T. (2017). Mapping quantitative trait loci for root development under hypoxia conditions in soybean (Glycine max L. Merr.). Theoretical and Applied Genetics, 130(4), 743–755. https://doi.org/10.1007/s00122-016-2847-3Velasco, H., Silva, A., Veenhuizen, R., Pérez, S., Prieto, M., Anaya, M., León, B., Cabas, N., Porto, E. and Morales, R. (2000). Manual de captacion y aprobechamiento de agua lluvia experiencias en America Latina serie: Zonas Áridas y Semiáridas. Organización de Las Naciones Unidas Para La Agricultura y La Alimentación FAO, No13, 194Velásquez F, S. and Jaramillo R, A. (2009). Redistribución de la lluvia en diferentes coberturas vegetales de la zona cafetera central de Colombia. Cenicafé, 60(2), 148–160. http://www.cenicafe.org/es/publications/arc060(02)148-160.pdfVon der Heydt, A. S., Ashwin, P., Camp, C. D., Crucifix, M., Dijkstra, H. A., Ditlevsen, P. and Lenton, T. M. (2021). Quantification and interpretation of the climate variability record. Global and Planetary Change, 197(May 2020), 103399. https://doi.org/10.1016/j.gloplacha.2020.103399Wallach, D., Thorburn, P., Asseng, S., Challinor, A. J., Ewert, F., Jones, J. W., Rotter, R. and Ruane, A. (2016). Estimating model prediction error: Should you treat predictions as fixed or random? Environmental Modelling and Software, 84, 529–539. https://doi.org/10.1016/j.envsoft.2016.07.010Wang, C. (2018). A review of ENSO theories. National Science Review, 5(6), 813–825. https://doi.org/10.1093/nsr/nwy104Wang, C. and Fiedler, P. C. (2006). ENSO variability and the eastern tropical Pacific: A review. Progress in Oceanography, 69(2–4), 239–266. https://doi.org/10.1016/j.pocean.2006.03.004Wang, Y., You, W., Fan, J., Jin, M., Wei, X. and Wang, Q. (2018). Effects of subsequent rainfall events with different intensities on runoff and erosion in a coarse soil. Catena, 170(June), 100–107. https://doi.org/10.1016/j.catena.2018.06.008Yan, Y., Mao, K., Shen, X., Cao, M., Xu, T., Guo, Z. and Bao, Q. (2021). Evaluation of the influence of ENSO on tropical vegetation in long time series using a new indicator. Ecological Indicators, 129, 107872. https://doi.org/10.1016/j.ecolind.2021.107872Yang, X., Magnusson, J., Huang, S., Beldring, S. and Xu, C. Y. (2020). Dependence of regionalization methods on the complexity of hydrological models in multiple climatic regions. Journal of Hydrology, 582, 124357. https://doi.org/10.1016/j.jhydrol.2019.124357Yeh, S. W., Cai, W., Min, S. K., McPhaden, M. J., Dommenget, D., Dewitte, B., Collins, M., Ashok, K., An, S. Il, Yim, B. Y. and Kug, J. S. (2018). ENSO Atmospheric Teleconnections and Their Response to Greenhouse Gas Forcing. Reviews of Geophysics, 56(1), 185–206. https://doi.org/10.1002/2017RG000568Yue, S. and Wang, C. Y. (2002). Applicability of prewhitening to eliminate the influence of serial correlation on the Mann-Kendall test. Water Resources Research, 38(6), 4-1-4–7. https://doi.org/10.1029/2001wr000861Zhao, C., Jia, X., Shao, M. and Zhu, Y. (2021). Regional variations in plant-available soil water storage and related driving factors in the middle reaches of the Yellow River Basin, China. Agricultural Water Management, 257(June), 107131. https://doi.org/10.1016/j.agwat.2021.107131Zounemat, M., Batelaan, O., Fadaee, M. and Hinkelmann, R. (2021). Ensemble machine learning paradigms in hydrology: A review. Journal of Hydrology, 598(March), 126266. https://doi.org/10.1016/j.jhydrol.2021.126266AGROSAVIAEstudiantesInvestigadoresMaestrosMedios de comunicaciónProveedores de ayuda financiera para estudiantesPúblico generalReceptores de fondos federales y solicitantesResponsables políticosORIGINAL1121837331.2022.pdf1121837331.2022.pdfTesis de Maestría en Ciencias agrarias, Linea de investigación en Suelos y Aguasapplication/pdf4948052https://repositorio.unal.edu.co/bitstream/unal/82003/1/1121837331.2022.pdf3ef692e889a9ee6f17682cb6d73d3fbbMD51LICENSElicense.txtlicense.txttext/plain; charset=utf-84074https://repositorio.unal.edu.co/bitstream/unal/82003/2/license.txt8153f7789df02f0a4c9e079953658ab2MD52THUMBNAIL1121837331.2022.pdf.jpg1121837331.2022.pdf.jpgGenerated Thumbnailimage/jpeg4912https://repositorio.unal.edu.co/bitstream/unal/82003/3/1121837331.2022.pdf.jpgbb188046f161085a78e0317bb3e303b9MD53unal/82003oai:repositorio.unal.edu.co:unal/820032024-08-09 23:19:41.652Repositorio Institucional 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