Evaluación del modelo suelo-atmósfera-vegetación MESH en una cuenca tropical colombiana de relieve complejo con limitaciones de información

dc.contributor.advisorRodríguez Sandoval, Erasmo Alfredospa
dc.contributor.authorGuio González, Roger Stevenspa
dc.contributor.researchgroupGrupo de Investigación en Ingeniería de Recursos Hidrícos Girehspa
dc.date.accessioned2022-06-01T19:18:02Z
dc.date.available2022-06-01T19:18:02Z
dc.date.issued2022-06-01
dc.descriptionilustraciones, gráficas, mapas, tablasspa
dc.description.abstractImplementaciones previas de esquemas de interacción suelo-vegetación-atmósfera (SVAT), han mostrado las limitaciones de estos modelos en la simulación de flujos horizontales, en zonas con complejidad orográfica, escasez de información y localizadas en zonas tropicales. Particularmente en el caso colombiano estas dificultades se han presentado en el Alto Magdalena. Entender las razones, por las cuales se han presentado estas limitaciones es de especial interés por la importancia de estos modelos en el análisis acoplado de variables climáticas e hidrológicas. Por este motivo, en el presente trabajo se continuó con el análisis iniciado por Arboleda (2018), quien implementó el modelo MESH - el cual contiene un esquema SVAT- en la cuenca del río Coello (CRC) y posteriormente en toda la Macrocuenca Magdalena-Cauca (MCMC). Mediante la implementación de MESH se logró una adecuada estimación de los caudales, en las zonas media y baja de la MCMC, pero con resultados deficientes en el Alto Magdalena. Con el objetivo de entender las causas de la deficiencia mencionada, proponer ajustes para resolverlas y utilizando el modelo de la CRC (Arboleda, 2018), se hizo una evaluación de las variables del balance hídrico (precipitación, evapotranspiración y caudales) utilizando información como productos de reanálisis (MSWEP, ERA5, GLDAS, GLEAM), teledetección (MODIS16) y datos observados (IDEAM). Posteriormente se implementó un análisis de sensibilidad, para optimizar el proceso de calibración del modelo. A partir del análisis de sensibilidad, la evaluación del balance hídrico, y otros análisis complementarios, se propuso e implementó una estrategia metodológica en cuatro subcuencas del Alto Magdalena. Los resultados muestran que la propuesta mejora la simulación de caudales de acuerdo con la métrica NSE y la curva de duración de caudales. No obstante, el modelo sigue teniendo dificultades, especialmente en las cuencas del costado sur oriental del Alto Magdalena, en donde de acuerdo con los análisis realizados, la causa podría ser un rezago de hasta cuatro meses entre la precipitación y los caudales observados en su régimen mensual. Este rezago debería ser evaluado en futuras investigaciones. (Texto tomado de la fuente).spa
dc.description.abstractPrevious soil-vegetation-atmosphere interaction schemes (SVAT) implementations have shown their limitations in streamflow simulations in zones with orographic complexity, data-scarce, and located in tropical zones. Particularly in the Colombian case, these limitations have been in the upstream basins of the Magdalena River (Alto Magdalena). Understanding the reasons why these limitations have occurred is of special interest due to the importance of these models in the coupled analysis of climatic and hydrological variables. For this reason, in the present work, the analysis initiated by Arboleda (2018) was continued, who implemented the MESH model, which contains an SVAT scheme in the Coello River Basin (CRC) and later in the entire Magdalena-Cauca Macro-basin (MCMC). Through the implementation of MESH an adequate estimation of the streamflows was achieved in downstream and midstream basins of the MCMC, but with poor results in their upstream. So, in order understand the causes of the mentioned deficiency, using the CRC model (Arboleda, 2018), and propose changes to solve them, a water balance variables evaluation (precipitation, evapotranspiration, and streamflows) was made using information such as reanalysis products (MSWEP, ERA5, GLDAS, GLEAM), remote sensing (MODIS16), and observed data (IDEAM). Subsequently, a sensitivity analysis was implemented to optimize the model calibration process. Based on this analysis, the water balance evaluation, and other complementary analyses a methodological strategy was proposed and implemented in four sub-basins of the (Alto Magdalena). The results showed that this strategy improves the streamflow simulation, according to the NSE metric, and its flow duration curve. However, the model continues to have difficulties, especially on the southeast side of the Alto Magdalena, where according to the analysis carried out, the cause could be a lag of up to four months between the precipitation and the flows observed in its monthly regime. This lag should be evaluated in future research.eng
dc.description.degreelevelMaestríaspa
dc.description.degreenameMagíster en Ingeniería - Recursos Hidráulicosspa
dc.description.notesIncluye anexosspa
dc.description.researchareaHidrología e Hidrometeorologíaspa
dc.format.extent117 páginasspa
dc.format.mimetypeapplication/pdfspa
dc.identifier.instnameUniversidad Nacional de Colombiaspa
dc.identifier.reponameRepositorio Institucional Universidad Nacional de Colombiaspa
dc.identifier.repourlhttps://repositorio.unal.edu.co/spa
dc.identifier.urihttps://repositorio.unal.edu.co/handle/unal/81478
dc.language.isospaspa
dc.publisherUniversidad Nacional de Colombiaspa
dc.publisher.branchUniversidad Nacional de Colombia - Sede Bogotáspa
dc.publisher.departmentDepartamento de Ingeniería Civil y Agrícolaspa
dc.publisher.facultyFacultad de Ingenieríaspa
dc.publisher.placeBogotá, Colombiaspa
dc.publisher.programBogotá - Ingeniería - Maestría en Ingeniería - Recursos Hidráulicosspa
dc.relation.referencesAires, F.: Combining Datasets of Satellite-Retrieved Products. Part I: Methodology and Water Budget Closure, J. Hydrometeorol., 15(4), 1677–1691, doi:10.1175/jhm-d-13-0148.1, 2014.spa
dc.relation.referencesArboleda, P.: Determinando los efectos del cambio climático y del cambio en usos del suelo en la Macro Cuenca Magdalena Cauca utilizando el modelo de suelo- superficie e hidrológico MESH, Universidad Nacional de Colombia., 2018.spa
dc.relation.referencesBajracharya, A., Awoye, H., Stadnyk, T. y Asadzadeh, M.: Time Variant Sensitivity Analysis of Hydrological Model Parameters in a Cold Region Using Flow Signatures, Water, 12(4), 961, doi:10.3390/w12040961, 2020.spa
dc.relation.referencesBeck, H. E., Vergopolan, N., Pan, M., Levizzani, V., Van Dijk, A. I. J. M., Weedon, G. P., Brocca, L., Pappenberger, F., Huffman, G. J. y Wood, E. F.: Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling, Hydrol. Earth Syst. Sci., 21(12), 6201–6217, doi:10.5194/hess-21-6201-2017, 2017a.spa
dc.relation.referencesBeck, H. E., Van Dijk, A. I. J. M., Levizzani, V., Schellekens, J., Miralles, D. G., Martens, B. y De Roo, A.: MSWEP: 3-hourly 0.25° global gridded precipitation (1979-2015) by merging gauge, satellite, and reanalysis data, Hydrol. Earth Syst. Sci., 21(1), 589–615, doi:10.5194/hess-21-589-2017, 2017b.spa
dc.relation.referencesBeck, H. E., Wood, E. F., McVicar, T. R., Zambrano-Bigiarini, M., Alvarez-Garreton, C., Baez-Villanueva, O. M., Sheffield, J. y Karger, D. N.: Bias Correction of Global High-Resolution Precipitation Climatologies Using Streamflow Observations from 9372 Catchments, J. Clim., 33(4), 1299–1315, doi:10.1175/jcli-d-19-0332.1, 2020.spa
dc.relation.referencesBeven, K.: Rainfall-Runoff Modelling., 2012.spa
dc.relation.referencesBokulich, A. y Oreskes, N.: Models in the Geosciences, Springer Handb. Model. Sci., (Oreskes 2015), 891–911, 2017.spa
dc.relation.referencesBudyko, M. I.: Climate and Life, 18a ed., Academic press, New York, New York., 1974.spa
dc.relation.referencesCarmona, A. M., Poveda, G., Sivapalan, M., Vallejo-Bernal, S. M. y Bustamante, E.: A scaling approach to Budyko’s framework and the complementary relationship of evapotranspiration in humid environments: Case study of the Amazon River basin, Hydrol. Earth Syst. Sci., 20(2), 589–603, doi:10.5194/hess-20-589-2016, 2016.spa
dc.relation.referencesChavarría, S. B., Vargas, T. B., Fernando, J. y Villegas, S.: Decrease in total water storage in the Magdalena River basin in recent years inferred from GRACE data, EGU Gen. Assemly, 38(April), 1–2, doi:10.13140/RG.2.2.18751.41126/1, 2018.spa
dc.relation.referencesChen, X., Maignan, F., Viovy, N., Bastos, A., Goll, D., Wu, J., Liu, L., Yue, C., Peng, S., Yuan, W., da Conceição, A. C., O’Sullivan, M. y Ciais, P.: Novel Representation of Leaf Phenology Improves Simulation of Amazonian Evergreen Forest Photosynthesis in a Land Surface Model, J. Adv. Model. Earth Syst., 12(1), 1–17, doi:10.1029/2018MS001565, 2020.spa
dc.relation.referencesCORTOLIMA: CARACTERIZACIÓN CLIMATOLÓGICA DE LA SUBZONA HIDROGRÁFICA DEL RÍO COELLO., 2019a.spa
dc.relation.referencesCORTOLIMA: CARACTERIZACIÓN HIDROLÓGICA DE LA SUBZONA HIDROGRÁFICA DEL RÍO COELLO., 2019b.spa
dc.relation.referencesDavison, B., Pietroniro, A., Fortin, V., Leconte, R., Mamo, M. y Yau, M. K.: What is Missing from the Prescription of Hydrology for Land Surface Schemes?, J. Hydrometeorol., 17(7), 2013–2039, doi:10.1175/jhm-d-15-0172.1, 2016.spa
dc.relation.referencesDevia, G. K., Ganasri, B. P. y Dwarakish, G. S.: A Review on Hydrological Models, Aquat. Procedia, 4(Icwrcoe), 1001–1007, doi:10.1016/j.aqpro.2015.02.126, 2015.spa
dc.relation.referencesDias, L. C. P., Macedo, M. N., Costa, M. H., Coe, M. T. y Neill, C.: Effects of land cover change on evapotranspiration and streamflow of small catchments in the Upper Xingu River Basin, Central Brazil, J. Hydrol. Reg. Stud., 4(PB), 108–122, doi:10.1016/j.ejrh.2015.05.010, 2015.spa
dc.relation.referencesDickinson, E., Henderson-Sellers, A. y Kennedy, J.: Biosphere-atmosphere Transfer Scheme (BATS) Version 1e as Coupled to the NCAR Community Climate Model, NCAR Tech. Rep. NCAR/TN-3871STR, 72, doi:10.5065/D67W6959, 1993.spa
dc.relation.referencesDuque, N.: Estimación de campos de precipitación en cuencas hidrográficas colombianas con escasez de datos, combinando datos teledetectados y de estaciones en tierra, utilizando funciones de Kernel, , 216, doi:10.13140/RG.2.2.35859.94247, 2019.spa
dc.relation.referencesEk, M. B., Mitchell, K. E., Lin, Y., Rogers, E., Grunmann, P., Koren, V., Gayno, G. y Tarpley, J. D.: Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model, J. Geophys. Res. D Atmos., doi:10.1029/2002jd003296, 2003.spa
dc.relation.referencesElgamal, A., Reggiani, P. y Jonoski, A.: Impact analysis of satellite rainfall products on flow simulations in the Magdalena River Basin, Colombia, J. Hydrol. Reg. Stud., 9, 85–103, doi:10.1016/j.ejrh.2016.09.001, 2017.spa
dc.relation.referencesFerreira, P. M. de L., Paz, A. R. da y Bravo, J. M.: Objective functions used as performance metrics for hydrological models: state-of-the-art and critical analysis, Rbrh, 25, doi:10.1590/2318-0331.252020190155, 2020.spa
dc.relation.referencesFisher, R. A. y Koven, C. D.: Perspectives on the future of Land Surface Models and the challenges of representing complex terrestrial systems, J. Adv. Model. Earth Syst., doi:10.1029/2018ms001453, 2020.spa
dc.relation.referencesGüiza-Villa, N.: Estimación de los cambios en los índices asociados a la oferta y la demanda del recurso hídrico en la cuenca del río Coello bajo escenarios de cambio climático [Thesis]., , 199, 2019.spa
dc.relation.referencesHaghnegahdar, A. y Razavi, S.: Insights into sensitivity analysis of Earth and environmental systems models: On the impact of parameter perturbation scale, Environ. Model. Softw., 95, 115–131, doi:10.1016/j.envsoft.2017.03.031, 2017.spa
dc.relation.referencesHaghnegahdar, A., Razavi, S., Yassin, F. y Wheater, H.: Multicriteria sensitivity analysis as a diagnostic tool for understanding model behaviour and characterizing model uncertainty, Hydrol. Process., 31(25), 4462–4476, doi:10.1002/hyp.11358, 2017.spa
dc.relation.referencesHargreaves, G. H. y Samani, Z. A.: Estimating potential evapotranspiration., J. Irrig. Drain. Div. - ASCE, 1982.spa
dc.relation.referencesHersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S. y Thépaut, J. N.: The ERA5 global reanalysis, Q. J. R. Meteorol. Soc., 146(730), 1999–2049, doi:10.1002/qj.3803, 2020.spa
dc.relation.referencesHoltzman, N. M., Pavelsky, T. M., Cohen, J. S., Wrzesien, M. L. y Herman, J. D.: Tailoring WRF and Noah-MP to Improve Process Representation of Sierra Nevada Runoff: Diagnostic Evaluation and Applications, J. Adv. Model. Earth Syst., 12(3), 1–18, doi:10.1029/2019MS001832, 2020.spa
dc.relation.referencesHonek, D., Caletka, M. y Šulc Michalková, M.: Retrospective analysis of published hydrological researches: Models, trends and geographical aspects over the last two decades of hydrological modelling, Geogr. Cas., doi:10.31577/geogrcas.2018.70.4.16, 2018.spa
dc.relation.referencesJarvis, A., Reuter, H. I., Nelson, A. y Guevara, E.: Hole-filled seamless SRTM data V4, International Centre for Tropical Agriculture (CIAT), disponible en http://srtm.csi.cgiar.org., , (September 2017), 2008.spa
dc.relation.referencesKaune, A., Werner, M., López López, P., Rodríguez, E., Karimi, P. y De Fraiture, C.: Can global precipitation datasets benefit the estimation of the area to be cropped in irrigated agriculture?, Hydrol. Earth Syst. Sci., 23(5), 2351–2368, doi:10.5194/hess-23-2351-2019, 2019.spa
dc.relation.referencesKim, D., Kang, S. y Choi, M.: Land surface models evaluation for two different land-cover types: Cropland and forest, Terr. Atmos. Ocean. Sci., 27(1), 153–167, doi:10.3319/TAO.2015.09.14.02(Hy), 2016.spa
dc.relation.referencesKouwen, N.: WATFLOOD: a Micro-Computer Based Flood Forecasting System Based on Real-Time Weather Radar, Can. Water Resour. J., 13(1), 62–77, doi:10.4296/cwrj1301062, 1998.spa
dc.relation.referencesKouwen, N., Soulis, E. D., Pietroniro, A., Donald, J. y Harrington, R. A.: Grouped Response Units for Distributed Hydrologic Modeling, J. Water Resour. Plan. Manag., 119(3), 289–305, doi:10.1061/(asce)0733-9496(1993)119:3(289), 2006.spa
dc.relation.referencesKummerow, C., Simpson, J., Thiele, O., Barnes, W., Chang, A. T. C., Stocker, E., Adler, R. F., Hou, A., Kakar, R., Wentz, F., Ashcroft, P., Kozu, T., Hong, Y., Okamoto, K., Iguchi, T., Kuroiwa, H., Im, E., Haddad, Z., Huffman, G., Ferrier, B., Olson, W. S., Zipser, E., Smith, E. A., Wilheit, T. T., North, G., Krishnamurti, T. y Nakamura, K.: The status of the tropical rainfall measuring mission (TRMM) after two years in orbit, J. Appl. Meteorol., 39(12 PART 1), 1965–1982, doi:10.1175/1520-0450(2001)040<1965:tsottr>2.0.co;2, 2000.spa
dc.relation.referencesLindström, G., Johansson, B., Persson, M., Gardelin, M. y Bergström, S.: Development and test of the distributed HBV-96 hydrological model, J. Hydrol., doi:10.1016/S0022-1694(97)00041-3, 1997.spa
dc.relation.referencesLuo, Y., Arnold, J., Allen, P. y Chen, X.: Baseflow simulation using SWAT model in an inland river basin in Tianshan Mountains, Northwest China, Hydrol. Earth Syst. Sci., 16(4), 1259–1267, doi:10.5194/hess-16-1259-2012, 2012.spa
dc.relation.referencesMaccherone, B.: MODIS Web, MODIS Web, http://modis.gsfc.nasa.gov/data/dataprod/ [en línea] Available from: https://modis.gsfc.nasa.gov/data/dataprod/mod16.php (Consultado 24 mayo 2021), 2014.spa
dc.relation.referencesMacDonald, M.: Welcome to the Standalone MESH Wiki. [en línea] Available from: https://wiki.usask.ca/pages/viewpage.action?pageId=220332269 (Consultado 27 mayo 2021), 2019.spa
dc.relation.referencesMacDonald, M. K., Davison, B. J., Mekonnen, M. A. y Pietroniro, A.: Comparison of land surface scheme simulations with field observations versus atmospheric model output as forcing, Hydrol. Sci. J., 61(16), 2860–2871, doi:10.1080/02626667.2016.1177185, 2016.spa
dc.relation.referencesManabe, S.: Climate and the ocean circulation : I . The atmospheric circulation and the hydrology of the Earth ’ s surface . Mon Weather Rev EARTH ’ S, , 0493(JANUARY 1969), doi:10.1175/1520-0493(1969)09760, 1969.spa
dc.relation.referencesMancipe-Munoz, N. A., Buchberger, S. G., Suidan, M. T. y Lu, T.: Calibration of Rainfall-Runoff Model in Urban Watersheds for Stormwater Management Assessment, J. Water Resour. Plan. Manag., 140(6), 05014001, doi:10.1061/(asce)wr.1943-5452.0000382, 2014.spa
dc.relation.referencesMartens, B., Miralles, D. G., Lievens, H., Van Der Schalie, R., De Jeu, R. A. M., Fernández-Prieto, D., Beck, H. E., Dorigo, W. A. y Verhoest, N. E. C.: GLEAM v3: Satellite-based land evaporation and root-zone soil moisture, Geosci. Model Dev., 10(5), 1903–1925, doi:10.5194/gmd-10-1903-2017, 2017.spa
dc.relation.referencesMianabadi, A., Coenders-gerrits, M., Shirazi, P., Ghahraman, B. y Alizadeh, A.: A global Budyko model to partition evaporation into interception and transpiration, , 4983–5000, 2019.spa
dc.relation.referencesMunier, S., Aires, F., Schlaffer, S., Prigent, C., Papa, F., Maisongrande, P. y Pan, M.: Combining data sets of satellite-retrieved products for basin-scale water balance study: 2. Evaluation on the Mississippi basin and closure correction model, J. Geophys. Res., 119(21), 12,100-12,116, doi:10.1002/2014JD021953, 2014.spa
dc.relation.referencesMuñoz Sabater, J.: ERA5-Land hourly data from 1981 to present, Clim. Data Store, 1–10, doi:10.24381/cds.e2161bac, 2019.spa
dc.relation.referencesNash, J. E. y Sutcliffe, J. V.: River flow forecasting through conceptual models part I - A discussion of principles, J. Hydrol., doi:10.1016/0022-1694(70)90255-6, 1970.spa
dc.relation.referencesNewman, A. J., Mizukami, N., Clark, M. P., Wood, A. W., Nijssen, B. y Nearing, G.: Benchmarking of a physically based hydrologic model, J. Hydrometeorol., 18(8), 2215–2225, doi:10.1175/JHM-D-16-0284.1, 2017.spa
dc.relation.referencesNiu, G. Y., Yang, Z. L., Mitchell, K. E., Chen, F., Ek, M. B., Barlage, M., Kumar, A., Manning, K., Niyogi, D., Rosero, E., Tewari, M. y Xia, Y.: The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements, J. Geophys. Res. Atmos., 116(12), 1–19, doi:10.1029/2010JD015139, 2011.spa
dc.relation.referencesNoilhan, J. y Planton, S.: A simple parameterization of land surface processes for meteorological models, Mon. Weather Rev., doi:10.1175/1520-0493(1989)117<0536:ASPOLS>2.0.CO;2, 1989.spa
dc.relation.referencesPaca, V. H. da M., Espinoza-Dávalos, G. E., Hessels, T. M., Moreira, D. M., Comair, G. F. y Bastiaanssen, W. G. M.: The spatial variability of actual evapotranspiration across the Amazon River Basin based on remote sensing products validated with flux towers, Ecol. Process., 8(1), doi:10.1186/s13717-019-0158-8, 2019.spa
dc.relation.referencesPan, M. y Wood, E. F.: Data assimilation for estimating the terrestrial water budget using a constrained ensemble Kalman filter, J. Hydrometeorol., 7(3), 534–547, doi:10.1175/JHM495.1, 2006.spa
dc.relation.referencesPan, M., Sahoo, A. K., Troy, T. J., Vinukollu, R. K., Sheffield, J. y Wood, A. E. F.: Multisource estimation of long-term terrestrial water budget for major global river basins, J. Clim., 25(9), 3191–3206, doi:10.1175/JCLI-D-11-00300.1, 2012.spa
dc.relation.referencesPietroniro, A., Caldwell, R., Soulis, E. D., Fortin, V., Neal, C., Kouwen, N., Turcotte, R., Verseghy, D., Davison, B., Pietroniro, A., Pellerin, P. y Evora, N.: Development of the MESH modelling system for hydrological ensemble forecasting of the Laurentian Great Lakes at the regional scale, Hydrol. Earth Syst. Sci. Discuss., 11(4), 1279–1294, doi:10.5194/hessd-3-2473-2006, 2007.spa
dc.relation.referencesPrem, M., Saavedra, S. y Vargas, J. F.: End-of-conflict deforestation: Evidence from Colombia’s peace agreement, World Dev., 129(May), 1–37, doi:10.1016/j.worlddev.2019.104852, 2020.spa
dc.relation.referencesRazavi, S., Sheikholeslami, R., Gupta, H. V. y Haghnegahdar, A.: VARS-TOOL: A toolbox for comprehensive, efficient, and robust sensitivity and uncertainty analysis, Environ. Model. Softw., 112(October 2018), 95–107, doi:10.1016/j.envsoft.2018.10.005, 2019.spa
dc.relation.referencesRodell, M., Houser, P. R., Jambor, U., Gottschalck, J., Mitchell, K., Meng, C. J., Arsenault, K., Cosgrove, B., Radakovich, J., Bosilovich, M., Entin, J. K., Walker, J. P., Lohmann, D. y Toll, D.: The Global Land Data Assimilation System, Bull. Am. Meteorol. Soc., 85(3), 381–394, doi:10.1175/BAMS-85-3-381, 2004.spa
dc.relation.referencesRodríguez, E., Sánchez, I., Duque, N., Arboleda, P., Vega, C., Zamora, D., López, P., Kaune, A., Werner, M., García, C. y Burke, S.: Combined Use of Local and Global Hydro Meteorological Data with Hydrological Models for Water Resources Management in the Magdalena - Cauca Macro Basin – Colombia, Water Resour. Manag., doi:10.1007/s11269-019-02236-5, 2019.spa
dc.relation.referencesSaltelli, A., Aleksankina, K., Becker, W., Fennell, P., Ferretti, F., Holst, N., Li, S. y Wu, Q.: Why so many published sensitivity analyses are false: A systematic review of sensitivity analysis practices, Environ. Model. Softw., 114(January), 29–39, doi:10.1016/j.envsoft.2019.01.012, 2019.spa
dc.relation.referencesSánchez, I.: Evaluación del desempeño del esquema ISBA en la cuenca del río La Vieja-departamentos de Valle del Cauca, Risaralda y Quindío (Colombia), Universidad Nacional de Colombia., 2014.spa
dc.relation.referencesSellers, P. J., Los, S. O., Tucker, C. J., Justice, C. O., Dazlich, D. A., Collatz, G. J. y Randall, D. A.: A revised land surface parameterization (SiB2) for atmospheric GCMs. Part II: The generation of global fields of terrestrial biophysical parameters from satellite data, J. Clim., 9(4), 706–737, doi:10.1175/1520-0442(1996)009<0706:ARLSPF>2.0.CO;2, 1996.spa
dc.relation.referencesSellers, P. J., Dickinson, R. E., Randall, D. A., Betts, A. K., Hall, F. G., Berry, J. A., Collatz, G. J., Denning, A. S., Mooney, H. A., Nobre, C. A., Sato, N., Field, C. B. y Henderson-Sellers, A.: Modeling the exchanges of energy, water, and carbon between continents and the atmosphere, Science (80-. )., 275(5299), 502–509, doi:10.1126/science.275.5299.502, 1997.spa
dc.relation.referencesSheikholeslami, R. y Razavi, S.: Progressive Latin Hypercube Sampling: An efficient approach for robust sampling-based analysis of environmental models, Environ. Model. Softw., 93, 109–126, doi:10.1016/j.envsoft.2017.03.010, 2017.spa
dc.relation.referencesSoulis, E. D., Snelgrove, K. R., Kouwen, N., Seglenieks, F. y Verseghy, D. L.: Towards closing the vertical water balance in Canadian atmospheric models: Coupling of the land surface scheme class with the distributed hydrological model watflood, Atmos. - Ocean, 38(1), 251–269, doi:10.1080/07055900.2000.9649648, 2000.spa
dc.relation.referencesSposito, G.: Understanding the budyko equation, Water (Switzerland), 9(4), 1–14, doi:10.3390/w9040236, 2017.spa
dc.relation.referencesStrauch, M., Kumar, R., Eisner, S., Mulligan, M., Reinhardt, J., Santini, W., Vetter, T. y Friesen, J.: Adjustment of global precipitation data for enhanced hydrologic modeling of tropical Andean watersheds, Clim. Change, 141(3), 547–560, doi:10.1007/s10584-016-1706-1, 2017.spa
dc.relation.referencesTaylor, K. E.: Summarizing multiple aspects of model performance in a single diagram, J. Geophys. Res. Atmos., 106(D7), 7183–7192, doi:10.1029/2000JD900719, 2001.spa
dc.relation.referencesTowner, J., Cloke, H. L., Zsoter, E., Flamig, Z., Hoch, J. M., Bazo, J., De Perez, E. C. y Stephens, E. M.: Assessing the performance of global hydrological models for capturing peak river flows in the Amazon basin, Hydrol. Earth Syst. Sci., 23(7), 3057–3080, doi:10.5194/hess-23-3057-2019, 2019.spa
dc.relation.referencesVallejo-bernal, S. M., Carmona, A. M. y Poveda, G.: Evaluating Diverse Potential Evapotranspiration Methodologies and Databases for the Amazon River Basin, , (May) [en línea] Available from: www.elespectador.com. (Consultado 26 mayo 2021), 2018.spa
dc.relation.referencesVerseghy, D. L.: The Canadian land surface scheme (CLASS): Its history and future, Atmos. - Ocean, 38(1), 1–13, doi:10.1080/07055900.2000.9649637, 2000.spa
dc.relation.referencesVerseghy, D. L.: CLASS (version 3.4)– Technical documentation, , (January), 2009.spa
dc.relation.referencesWong, J. S., Zhang, X., Gharari, S., Shrestha, R. R., Wheater, H. S. y Famiglietti, J. S.: Assessing Water Balance Closure Using Multiple Data Assimilation and Remote Sensing-Based Datasets for Canada, J. Hydrometeorol., 1569–1589, doi:10.1175/jhm-d-20-0131.1, 2021.spa
dc.relation.referencesZhao, W. y Li, A.: A Review on Land Surface Processes Modelling over Complex Terrain, Adv. Meteorol., 2015, doi:10.1155/2015/607181, 2015.spa
dc.relation.referencesZulkafli, Z., Buytaert, W., Onof, C., Lavado, W. y Guyot, J. L.: A critical assessment of the JULES land surface model hydrology for humid tropical environments, Hydrol. Earth Syst. Sci., 17(3), 1113–1132, doi:10.5194/hess-17-1113-2013, 2013.spa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.licenseReconocimiento 4.0 Internacionalspa
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/spa
dc.subject.ddc550 - Ciencias de la tierra::551 - Geología, hidrología, meteorologíaspa
dc.subject.lembWater balance (hydrology)eng
dc.subject.lembBalance hídrico (Hidrología)spa
dc.subject.lembWatershedseng
dc.subject.lembCuencas hidrográficasspa
dc.subject.lembCorrientes de aguaspa
dc.subject.lembStreameng
dc.subject.proposalH-LSSeng
dc.subject.proposalEsquemasspa
dc.subject.proposalSVATspa
dc.subject.proposalMESHspa
dc.subject.proposalAnálisisspa
dc.subject.proposalCoellospa
dc.subject.proposalMESHeng
dc.subject.proposalCoelloeng
dc.subject.proposalModelospa
dc.subject.proposalSensibilidadspa
dc.subject.proposalComplejidadspa
dc.subject.proposalOrográficaspa
dc.subject.proposalEscasezspa
dc.subject.proposalDatosspa
dc.subject.proposalAlto Magdalenaspa
dc.subject.proposalCuencaspa
dc.subject.proposalRíospa
dc.subject.proposalModeleng
dc.subject.proposalSensitivityeng
dc.subject.proposalAnalysiseng
dc.subject.proposalOrographiceng
dc.subject.proposalComplexityeng
dc.subject.proposalDataeng
dc.subject.proposalScarcityeng
dc.subject.proposalRivereng
dc.subject.proposalBasineng
dc.titleEvaluación del modelo suelo-atmósfera-vegetación MESH en una cuenca tropical colombiana de relieve complejo con limitaciones de informaciónspa
dc.title.translatedEvaluation of the soil-atmosphere-vegetation MESH model in a Colombian tropical basin of complex relief with information limitationseng
dc.typeTrabajo de grado - Maestríaspa
dc.type.coarhttp://purl.org/coar/resource_type/c_bdccspa
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/masterThesisspa
dc.type.redcolhttp://purl.org/redcol/resource_type/TMspa
dc.type.versioninfo:eu-repo/semantics/acceptedVersionspa
dcterms.audience.professionaldevelopmentEstudiantesspa
dcterms.audience.professionaldevelopmentInvestigadoresspa
dcterms.audience.professionaldevelopmentPúblico generalspa
oaire.accessrightshttp://purl.org/coar/access_right/c_abf2spa

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