Aplicación de modelos hidrológicos
DOI:
https://doi.org/10.5377/elhigo.v12i2.15228Palabras clave:
Modelo hidrológico, VIC, SWAT, VELMA, WEAPResumen
Los modelos hidrológicos son herramientas esenciales para la planificación y gestión de los recursos hídricos y del medio ambiente. En las últimas décadas se han desarrollado diversos modelos hidrológicos, cada uno con características y parámetros específicos, con el objetivo de representar mejor la microfísica del ciclo hidrológico, aunque, algunos investigadores han encontrado que incluso el uso de técnicas complejas de modelamiento no garantiza una mejor evaluación, debido a la heterogeneidad del suelo y al cambio climático que desempeña un papel determinante en el comportamiento del régimen hidrológico. En este artículo, se presenta un breve resumen de once distintos modelos hidrológicos, ocho de libre acceso. Los modelos incluidos corresponden al modelo de capacidad de infiltración variable (VIC), TOPMODEL, HBV, MIKE SHE, herramienta de evaluación de suelos y aguas (SWAT), HSPF, VELMA, PIHM, KINEROS, WEAP y HEC-HMS. Considerando aspectos como la región de aplicación, escala espacial, datos de entrada y si la interfaz es amigable e intuitiva, se concluye que el modelo SWAT seguido de los modelos HEC-HMS y WEAP son los más versátiles y adecuados para ser aplicados en regiones como Nicaragua. Este estudio proporciona una guía a los modeladores para identificar el tipo de modelo hidrológico que podrían aplicar en una cuenca específica para resolver un problema determinado, así mismo, les permitirá determinar la viabilidad de uno con respecto al otro según la disponibilidad de datos de entrada que se requieran y los recursos disponibles tanto informáticos como financieros.
Descargas
586
Citas
Abbott, M., Bathurst, J., Cunge, J., O’Connell, P., & Rasmussen, J., (1986). An introduction to the European Hydrological System—Systeme Hydrologique Europeen ‘SHE’. 2: Structure of a physically based, distributed modelling system. J. Hydrol. 87, 61–77.
Abdelnour A., Stieglitz M., Pan F. & McKane R., (2011). Catchment hydrological responses to forest harvest amount and spatial pattern. Water Resources Research 47 (9), W09521. doi:10.1029/2010WR010165
Abdulkareem, J., Pradhan, B., Sulaiman, W., & Jamil, N. R. (2018). Review of studies on hydrological modelling in Malaysia. Modeling Earth Systems and Environment, 4(4), 1577–1605. https://doi.org/10.1007/s40808-018-0509-y
Addor, N., & Melsen, L., (2018). Legacy, Rather Than Adequacy, Drives the Selection of Hydrological Models. Water Resources Research, 55(1), 378–390. https://doi.org/10.1029/2018wr022958
Alcamo, J., (2009). Managing the global water system. In: Levin, S. (Ed.), Princeton guide of ecology. Princeton University Press, Princeton, NJ.
Arnold, J. G., Srinivasan, R., Muttiah, R., & Williams, J., (1998). LARGE AREA HYDROLOGIC MODELING AND ASSESSMENT PART I: MODEL DEVELOPMENT. Journal of the American Water Resources Association, 34(1), 73–89. https://doi.org/10.1111/j.1752-1688.1998.tb05961.x
Asghar, A., Iqbal, J., Amin, A., & Ribbe, L., (2019). Integrated hydrological modeling for assessment of water demand and supply under socio-economic and IPCC climate change scenarios using WEAP in Central Indus Basin. Journal of Water Supply: Research and Technology-Aqua, 68(2), 136–148. https://doi.org/10.2166/aqua.2019.106
Bai, P., Liu, X., Zhang, Y., & Liu, C., (2020). Assessing the impacts of vegetation greenness change on evapotranspiration and water yield in China. Water Resour. Res.
Banitt, M. (2010). SIMULATING A CENTURY OF HYDROGRAPHS -MARK TWAIN RESERVOIR. https://acwi.gov/sos/pubs/2ndJFIC/Contents/8E_Banitt_03_02_10.pdf
Bárdossy, A., (2007). Calibration of hydrological model parameters for ungauged catchments. Hydrology and Earth System Sciences, 11(2), 703–710. https://doi.org/10.5194/hess-11-703-2007
Bergström, S., & Forsman, A., (1973). DEVELOPMENT OF A CONCEPTUAL DETERMINISTIC RAINFALL-RUNOFF MODEL. Hydrology Research, 4(3), 147–170. https://doi.org/10.2166/nh.1973.0012
Bergström, S., (1976). Development and application of a conceptual runoff model for Scandinavian catchments. SMHI RHO 7. Norrköping. 134.
Beven, K. & Kirkby, M., (1979). A Physically Based Variable Contributing Area Model of Basin Hydrology. Hydrological Sciences Bulletin 24, 43-69.
Bicknell, B., Imhoff, J., Kittle, J., Donigian, A., & Johanson, R., (1993). Hydrological Simulation Program - FORTRAN (HSPF): User’s Manual for Release 10. EPA-600/R-93/174.
Carvajal, L., & Roldán, E., (2007). Calibración del Modelo Lluvia-Escorrentia agregado GR4J Aplicación: Cuenca del río Aburrá. 74, 73–87. http://www.scielo.org.co/pdf/dyna/v74n152/a07v74n152.pdf
Chow, V., Maidment, D., & Mays, L., (1988) Applied hydrology, pp 12–34
Cunderlik, J. & Simonovic, S., (2010). Hydrologic models for inverse climate change impact modeling. In: 18th Canadian Hydro-technical Conference, Manitoba, August 2007
Danish Hydraulic Institute (DHI)., (2022). MIKE SHE An Integrated Hydrological Modelling System- User Guide. Edición 2022.
Devi, G., Ganasri, B., & Dwarakish, G., (2015) A Review on hydrological models. In: International conference on water resources, coastal and ocean engineering (ICWRCOE), pp 1001–1007. https://doi.org/10.1016/j.aqpro.2015.02.126
Dirmeyer, P., (2011). The terrestrial segment of soil moisture-climate coupling. Geophysical Research Letters, 38(16), n/a-n/a. https://doi.org/10.1029/2011gl048268
Easton, Z., Fuka, D., White, E., Collick, A., Biruk Ashagre, B., McCartney, M., Awulachew, S., Ahmed, A. & Steenhuis, T., (2010). A multi basin SWAT model analysis of runoff and sedimentation in the Blue Nile, Ethiopia. Hydrology and earth system sciences 14, 1827-1841.
Jorquera, E., Weber, J., & Reyna, S. (2014). Revisión del estado del arte en la modelación hidrológica distribuida e integrada. https://www.researchgate.net/publication/266885248_Revision_del_estado_del_arte_en_la_modelacion_hidrologica_distribuida_e_integrada
Fang, X., Cleveland, T., Garcia, C., Thompson, D., & Malla, R., (2005). Literature Review on Timing Parameters for Hydrographs. Department of Civil Engineering, Lamar University, Beaumont, Texas, p. 77.
Feldman, A., (2000). Hydrologic Modeling System HEC-HMS, Technical Reference Manual. U.S. Army Corps of Engineers, Hydrologic Engineering Center, HEC, Davis, CA, USA.
Franchini M, Wendling J, Obled C & Todini E., (1996). Physical interpretation and sensitivity analysis of the TOPMODEL. Journal of Hydrology, 175(1-4): 293-338. doi: 10.1016/S0022-1694(96)80015-1
Freeman, M., Pringle, C., & Jackson, C., (2007). Hydrologic connectivity and the contribution of stream headwaters to ecological integrity at regional scales. JAWRA J. Am. Water Resour. Assoc. 43 (1), 5–14. https://doi.org/10.1111/j.1752- 1688.2007.00002.x
Gao, H., Tang, Q., Shi, X., Zhu, C., Bohn, T., Su, F., Sheffield, J., Pan, M., Lettenmaier, D., & Wood, E., (2010). Water Budget Record from Variable Infiltration Capacity (VIC) Model. In Algorithm Theoretical Basis Document for Terrestrial Water Cycle Data Records (in review).
Golmohammadi, G., Prasher, S., Madani, A., & Rudra, R., (2014). Evaluating Three Hydrological Distributed Watershed Models: MIKE-SHE, APEX, SWAT. Hydrology, 1(1), 20–39. https://doi.org/10.3390/hydrology1010020
Graeff, T., Zehe, E., Blume, T., Francke, T., & Schröder, B., (2012). Predicting event response in a nested catchment with generalized linear models and a distributed watershed model. Hydrological Processes, 26(24), 3749–3769. https://doi.org/10.1002/hyp.8463
Gupta, H., Beven, K., & Wagener, T., (2005). Model calibration and uncertainty estimation. In: Andersen M (ed.) Encyclopedia of Hydrological Sciences, pp. 2015--2031. New York, NY: Wiley.
Gupta, H., Kling, H., Yilmaz, K., & Martinez, G. (2009). Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling. Journal of Hydrology 377: 80—91.
Gupta, H., Wagener, T., & Liu, Y., (2008). Reconciling theory with observations: elements of a diagnostic approach to model evaluation. Hydrological Processes, 22(18), 3802–3813. https://doi.org/10.1002/hyp.6989
Halwatura D. & Najim M., (2013). Application of the HEC-HMS model for runoff simulation in a tropical catchment. Environmental Modelling & Software, Volume 46, Pages 155-162. ISSN 1364-8152, https://doi.org/10.1016/j.envsoft.2013.03.006
Harlin, J., (1991). Development of a Process Oriented Calibration Scheme for the HBV Hydrological Model. Hydrology Research, 22(1), 15–36. https://doi.org/10.2166/nh.1991.0002
Hassan, Z., Shamsudin, S., Harun, S., Malek, M. A., & Hamidon, N., (2015). Suitability of ANN applied as a hydrological model coupled with statistical downscaling model: a case study in the northern area of Peninsular Malaysia. Environmental Earth Sciences, 74(1), 463–477. https://doi.org/10.1007/s12665-015-4054-y
Hunukumbura, P., Weerakoon, S., & Herath, S., (2008). Runoff modeling in the upper Kotmale Basin. In: Hennayake, N., Rekha, N., Nawfhal, M., Alagan, R., Daskon, C. (Eds.), Traversing No Man’s Land, Interdisciplinary Essays in Honor of Professor Madduma Bandara. University of Peradeniya, Sri Lanka, pp. 169e184.
Immerzeel, W., Gaur, A., & Zwart, S., (2008). Integrating remote sensing and a process-based hydrological model to evaluate water use and productivity in a south Indian catchment. Agricultural Water Management, 95(1), 11–24. https://doi.org/10.1016/j.agwat.2007.08.006
Jaiswal, R., Ali, S., & Bharti, B., (2020). Comparative evaluation of conceptual and physical rainfall–runoff models. Applied Water Science, 10(1). https://doi.org/10.1007/s13201-019-1122-6
Jeziorska, J., & Niedzielski, T., (2018). Applicability of TOPMODEL in the mountainous catchments in the upper Nysa Kłodzka river basin (SW Poland). Acta Geophysica, 66(2), 203–222. https://doi.org/10.1007/S11600-018-0121-6/FIGURES/8
Khalid, K., Ali, M., Rahman, N., & Mispan. M., (2016). Application on one-at-a-time sensitivity analysis of semi-distributed hydrological model in tropical watershed. IACSIT Int J Eng Technol 8:132–136. https://doi.org/10.7763/IJET.2016.V8.872
Kristensen, K. & Jensen, S., (1975). A model of estimating actual evapotranspiration from potential evapotranspiration. Nordic Hydrology. 6, 170-188.
Kumar, M., Bhatt, G., & Duffy, C., (2009). An efficient domain decomposition framework for accurate representation of geodata in distributed hydrologic models. International Journal of Geographical Information Science. https://doi.org/10.1080/13658810802344143
Liang, X., Lettenmaier, D., Wood, E., & Burges, S., (1994). A simple hydrologically based model of land surface water and energy fluxes for general circulation models. Journal of Geophysical Research, 99(D7), 14415. https://doi.org/10.1029/94jd00483
Liu, Z., Wang, Y., Xu, Z., & Duan, Q., (2017). Conceptual Hydrological Models. Handbook of Hydrometeorological Ensemble Forecasting, 1–23. https://doi.org/10.1007/978-3-642-40457-3_22-1
Lohmann, D., Raschke, E., Nijssen, B., & Lettenmaier, D., (1998). Regional scale hydrology: I. Formulation of the VIC-2L model coupled to a routing model. Hydrological Sciences Journal. https://www.tandfonline.com/doi/abs/10.1080/02626669809492107
Marshall, S., (2013). Hydrology. Reference Module in Earth Systems and Environmental Sciences. https://doi.org/10.1016/b978-0-12-409548-9.05356-2
Martínez-Austira, P. & Patiño-Gómez, C., (2012). Efectos del cambio climático en la disponibilidad de agua en México. Ciencias del Agua, Vol. III, No. 1, pp. 5-20.
Maurer, E., (2011). VIC Hydrology Model Training Workshop-Part I: About the VIC Model, Presentation, url: http://www.engr.scu.edu/~emaurer/chile/vic_taller/01_vic_training_overview_processes.pdf
Mckane, R., Brookes, A., Djang, K., Stieglitz, M., Abdelnour, A., Halama, J., Pettus, P., & Phillips, D., (2014). VELMA Version 2.0 User Manual and Technical Documentation. https://www.epa.gov/sites/default/files/2016-01/documents/velma_2.0_user_manual.pdf
Jajarmizadeh, M., Harun, S. & Salarpour, M., (2012). A Review on Theoretical Consideration and Types of Models in Hydrology. Journal of Environmental Science and Technology 5(5): 249-261. ISSN 1994-7887 / DOI:10.3923/jest.2012.249.261
Moradkhani, H. & Sorooshian, S., (2008). General review of rainfall-runoff modeling: model calibration, data assimilation, and uncertainty analysis. Hydrological modeling and the water cycle, s.l.: Springer.
Nagdeve, M., Paul, P., Zhang, Y., & Singh, R., (2021). Continuous Contour Trench (CCT): understandings of hydrological processes after standardization of dimensions and development of a user-friendly software. Soil Tillage Res. 205 (C), 104792 https:// doi.org/10.1016/j.still.2020.104792.
Neitsch, S., Arnold, J., Kiniry, J. & Williams, J., (2011). Soil and water assessment tool theoretical documentation version 2009. College Station: Texas Water Resources Institute
Orth, R., Staudinger, M., Seneviratne, S., Seibert, J., & Zappa, M., (2015). Does model performance improve with complexity? A case study with three hydrological models. J. Hydrol. 523, 147–159. https://doi.org/10.1016/j.jhydrol.2015.01.044.
Pandi, D, Kothandaraman S., & Kuppusamy M., (2021). Hydrological models: a review. International Journal of Hydrology Science and Technology 2021 12:3, 223-242
Paul, P., Zhang, Y., Ma, N., Mishra, A., Panigrahy, N., & Singh, R., (2021). Selecting hydrological models for developing countries: Perspective of global, continental, and country scale models over catchment scale models. Journal of Hydrology 600 (2021) 126561. https://doi.org/10.1016/j.jhydrol.2021.126561
Qu, Y., (2005). "An integrated hydrologic model for multi-process simulation using semi-discrete finite volume approach." PhD diss., Pennsylvania State University. http://www.pihm.psu.edu/Downloads/Articles/qu_thesis.pdf
Qu, Y., & Duffy, C., (2007). “A semidiscrete finite volume formulation for multiprocess watershed simulation.” Water Resour. Res. 43 (8): W08419. https://doi.org/10.1029/2006WR005752.
Ray, K., (1975). Hydrology for engineers. McGraw Hill, Kogakusha
Refsgaard, J., & Storm, B., (1995). MIKE SHE. In: Singh, V.P. (Ed.), Computer Models of Watershed Hydrology.Water Resource Publications, CO, USA, 806-846.
Semmens, D., Goodrich, D., Unkrich, C., Smith, R., Woolhiser, D., & Miller, S., (2007). KINEROS2 and the AGWA modeling Framework. In H. Wheater, S. Sorooshian, & K. Sharma (Eds.), Hydrological Modelling in Arid and Semi-Arid Areas (International Hydrology Series, pp. 49-68). Cambridge: Cambridge University Press. doi:10.1017/CBO9780511535734.006
Shaw, E., Beven, K., Chappell, N., & Lamb, R., (2010). Hydrology in practice. CRC Press, New York
Shrestha, D., Kayastha, N., & Solomatine, D., (2009). Encapsulation of Monte-Carlo Uncertainty Analysis Results in a Predictive Machine Learning Model. Delft University of Technology.
Shu, L., Ullrich, P., & Duffy, C., (2019). A fast/automated watershed modeling workflow with the Penn State Integrated Hydrologic Model (PIHM): Essential data, simulation, applications and visualization. AGU Fall Meeting Abstracts, H53K1918. https://ui.adsabs.harvard.edu/abs/2019AGUFM.H53K1918S/abstract
Sieber, J., (2022). WEAP: Water Evaluation And Planning System. Weap21.org. https://www.weap21.org/index.asp?action=201
Singh, V., (1995). Computer models of watershed hydrology, vol 1130. Water Resources Publications, Highlands Ranch, CO
Singh, V. & Frevert, D., (Eds.), (2006). Watershed Models. Taylor and Francis group, 3- 14 pp
Solomatine, D. & Wagener, T., (2011). Hydrological Modeling. Vol. 2.16 (435-457). 2011 Elsevier B.V. All rights reserved.
Sorooshian, S., Sharma, K. & Wheater, H., (2008). Hydrological Modeling in Arid and Semi-Arid Areas, New York: Cambridge University Press.
Stockholm Environment Institute, (2020). WEAP. SEI. https://www.sei.org/projects-and-tools/tools/weap/
Straub, T., Melching, C., & Kocher, K., (2000). Equations for estimating Clark unithydrograph parameters for small rural watersheds in Illinois. In: Water-resources Investigations Report 00-4184. Illinois Department of Natural Resources, Office of Water Resources U.S. Geological Survey, Urbana, Illinois, pp. 4-6.
Tajbakhsh, S., Memarian, H., Sobhani, M. & Afshar, A., (2018). Kinematic runoff and erosion model efficiency assessment for hydrological simulation of semi-arid watersheds. Global Journal of Environmental Science and Management. 4. DOI: 10.22034/GJESM.2018.04.02.002
Tassew, B., Belete, M., & Miegel, K., (2019). Application of HEC-HMS Model for Flow Simulation in the Lake Tana Basin: The Case of Gilgel Abay Catchment, Upper Blue Nile Basin, Ethiopia. Hydrology, 6(1), 21. https://doi.org/10.3390/hydrology6010021
Tegegne, G., Park, D., & Kim, Y., (2017). Comparison of hydrological models for the assessment of water resources in a data-scarce region, the Upper Blue Nile River Basin. Journal of Hydrology: Regional Studies, 14, 49–66. https://doi.org/10.1016/j.ejrh.2017.10.002
Texas A&M University., (2012). SWAT | Soil & Water Assessment Tool. Tamu.edu. https://swat.tamu.edu/
U. S. Army Corps of Engineers, USACE, (2010). HEC-GeoHMS geospatial hydrologic modeling extension, Version 5.0 - User’s Manual. Davis, CA, pp 3-1.
U.S. EPA., (2022). Visualizing Ecosystem Land Management Assessments (VELMA) 2.1 Modeling Tool. U.S. Environmental Protection Agency, Washington, DC, https://cfpub.epa.gov/ncea/risk/recordisplay.cfm?deid=354355
University of Washington Computational Hydrology Group., (2018). Model Overview - VIC. VIC User Guide. https://vic.readthedocs.io/en/master/Overview/ModelOverview/
US Army Corps of Engineers, (2018). HEC-HMS. https://www.hec.usace.army.mil/software/hec-hms/
US EPA, (2015). Hydrological Simulation Program - FORTRAN (HSPF). US EPA. https://www.epa.gov/ceam/hydrological-simulation-program-fortran-hspf
USDA Agricultural Research Service, (2022). KINEROS2: A Kinematic Runoff and Erosion Model. https://www.tucson.ars.ag.gov/kineros/
Wagener, T. & Gupta, H., (2005) Model identification for hydrological forecasting under uncertainty. Stochastic Environmental Research and Risk Assessment 19: 378--387 (doi:10.1007/s00477-005-0006-5).
Wang, Y. & Yan, X., (2017). Climate change induced by Southern Hemisphere desertification. Phys. Chem. Earths, Parts A/B/C 102, 40–47. https://doi.org/10.1016/j.pce.2016.03.009
Woolhiser, D., Smith, R., & Goodrich, D., (1990). KINEROS, A Kinematic Runoff and Erosion Model: Documentation and User Manual. U.S. Department of Agriculture, Agricultural Research Service, ARS-77, 130 pp.
Yilma, H. & Moges, S., (2007). Application of semi-distributed conceptual hydrological model for flow forecasting on upland catchments of Blue Nile River Basin, a case study of Gilgel Abbay catchment. Catchment and Lake Research, 200.
Zhang, J., Ross, M., Trout, K., & Zhou, D., (2009). Calibration of the HSPF model with a new coupled FTABLE generation method. Progress in Natural Science, 19(12), 1747–1755. https://doi.org/10.1016/j.pnsc.2009.07.006
Zhang, J., Zhang, Y., Song, J., Cheng, L., Kumar Paul, P., Gan, R., Shi, X., Luo, Z., & Zhao, P., (2020). Large-scale baseflow index prediction using hydrological modelling, linear and multilevel regression approaches. J. Hydrol. 585, 124780. https://doi.org/10.1016/j.jhydrol.2020.124780
Zhang, P., Zhang, J., & Song, Y., (2019). Hydrological Simulation of Taizi River Basin with HSPF Model. IOP Conference Series: Earth and Environmental Science, 330(3), 032014. https://doi.org/10.1088/1755-1315/330/3/032014
Zhang, Y. & Chiew, F., (2009). Relative merits of different methods for runoff predictions in ungauged catchments. Water Resour. Res. 45 (W07412) https://doi.org/10.1029/2008WR007504
Descargas
Publicado
Cómo citar
Número
Sección
Licencia
Derechos de autor 2022 Universidad Nacional de Ingeniería
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-SinDerivadas 4.0.
Todo el material publicado en la revista se comparte bajo la Licencia Creative Commons Attribution-NonCommercial-NoDerivatives 4.0., se permite la copia y redistribución del material en cualquier medio o formato siempre y cuando se de crédito de forma explícita a la revista, el autor y la obra, se distribuya de forma gratuita y sin hacer modificaciones al contenido.