Isohyetal maps of daily maximum rainfall for different return periods for the Colombian Caribbean Region
In Colombia, daily maximum multiannual series are one of the main inputs for design streamflow calculation, which requires performing a rainfall frequency analysis that involves several prior steps: (a) requesting the datasets, (b) waiting for the information, (c) reviewing the datasets received for...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2019
- Institución:
- Universidad Tecnológica de Bolívar
- Repositorio:
- Repositorio Institucional UTB
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.utb.edu.co:20.500.12585/8765
- Acceso en línea:
- https://hdl.handle.net/20.500.12585/8765
- Palabra clave:
- Design rainfall
IDEAM
Interpolation method
Isohyetal map
Stationary frequency analysis
Stormwater management
Rain
Rain gages
Design rainfalls
Frequency Analysis
IDEAM
Interpolation method
Storm-water managements
Interpolation
Frequency analysis
Interpolation
Kriging
Mapping method
Precipitation intensity
r Raingauge
Return period
Streamflow
Wastewater treatment
Caribbean Coast [Colombia]
Colombia
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
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dc.title.none.fl_str_mv |
Isohyetal maps of daily maximum rainfall for different return periods for the Colombian Caribbean Region |
title |
Isohyetal maps of daily maximum rainfall for different return periods for the Colombian Caribbean Region |
spellingShingle |
Isohyetal maps of daily maximum rainfall for different return periods for the Colombian Caribbean Region Design rainfall IDEAM Interpolation method Isohyetal map Stationary frequency analysis Stormwater management Rain Rain gages Design rainfalls Frequency Analysis IDEAM Interpolation method Storm-water managements Interpolation Frequency analysis Interpolation Kriging Mapping method Precipitation intensity r Raingauge Return period Streamflow Wastewater treatment Caribbean Coast [Colombia] Colombia |
title_short |
Isohyetal maps of daily maximum rainfall for different return periods for the Colombian Caribbean Region |
title_full |
Isohyetal maps of daily maximum rainfall for different return periods for the Colombian Caribbean Region |
title_fullStr |
Isohyetal maps of daily maximum rainfall for different return periods for the Colombian Caribbean Region |
title_full_unstemmed |
Isohyetal maps of daily maximum rainfall for different return periods for the Colombian Caribbean Region |
title_sort |
Isohyetal maps of daily maximum rainfall for different return periods for the Colombian Caribbean Region |
dc.subject.keywords.none.fl_str_mv |
Design rainfall IDEAM Interpolation method Isohyetal map Stationary frequency analysis Stormwater management Rain Rain gages Design rainfalls Frequency Analysis IDEAM Interpolation method Storm-water managements Interpolation Frequency analysis Interpolation Kriging Mapping method Precipitation intensity r Raingauge Return period Streamflow Wastewater treatment Caribbean Coast [Colombia] Colombia |
topic |
Design rainfall IDEAM Interpolation method Isohyetal map Stationary frequency analysis Stormwater management Rain Rain gages Design rainfalls Frequency Analysis IDEAM Interpolation method Storm-water managements Interpolation Frequency analysis Interpolation Kriging Mapping method Precipitation intensity r Raingauge Return period Streamflow Wastewater treatment Caribbean Coast [Colombia] Colombia |
description |
In Colombia, daily maximum multiannual series are one of the main inputs for design streamflow calculation, which requires performing a rainfall frequency analysis that involves several prior steps: (a) requesting the datasets, (b) waiting for the information, (c) reviewing the datasets received for missing or data different from the requested variable, and (d) requesting the information once again if it is not correct. To tackle these setbacks, 318 rain gauges located in the Colombian Caribbean region were used to first evaluate whether or not the Gumbel distribution was indeed the most suitable by performing frequency analyses using three different distributions (Gumbel, Generalized Extreme Value (GEV), and Log-Pearson 3 (LP3)); secondly, to generate daily maximum isohyetal maps for return periods of 2, 5, 10, 20, 25, 50, and 100 years; and, lastly, to evaluate which interpolation method (IDW, spline, and ordinary kriging) works best in areas with a varying density of data points. GEV was most suitable in 47.2% of the rain gauges, while Gumbel, in spite of being widely used in Colombia, was only suitable in 34.3% of the cases. Regarding the interpolation method, better isohyetals were obtained with the IDW method. In general, the areal maximum daily rainfall estimated showed good agreement when compared to the true values. © 2019 by the authors. |
publishDate |
2019 |
dc.date.accessioned.none.fl_str_mv |
2019-11-06T19:05:20Z |
dc.date.available.none.fl_str_mv |
2019-11-06T19:05:20Z |
dc.date.issued.none.fl_str_mv |
2019 |
dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_2df8fbb1 |
dc.type.driver.none.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.hasversion.none.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.spa.none.fl_str_mv |
Artículo |
status_str |
publishedVersion |
dc.identifier.citation.none.fl_str_mv |
Water (Switzerland); Vol. 11, Núm. 2 |
dc.identifier.issn.none.fl_str_mv |
2073-4441 |
dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12585/8765 |
dc.identifier.doi.none.fl_str_mv |
10.3390/w11020358 |
dc.identifier.instname.none.fl_str_mv |
Universidad Tecnológica de Bolívar |
dc.identifier.reponame.none.fl_str_mv |
Repositorio UTB |
identifier_str_mv |
Water (Switzerland); Vol. 11, Núm. 2 2073-4441 10.3390/w11020358 Universidad Tecnológica de Bolívar Repositorio UTB |
url |
https://hdl.handle.net/20.500.12585/8765 |
dc.language.iso.none.fl_str_mv |
eng |
language |
eng |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
dc.rights.uri.none.fl_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ |
dc.rights.accessrights.none.fl_str_mv |
info:eu-repo/semantics/openAccess |
dc.rights.cc.none.fl_str_mv |
Atribución-NoComercial 4.0 Internacional |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ Atribución-NoComercial 4.0 Internacional http://purl.org/coar/access_right/c_abf2 |
eu_rights_str_mv |
openAccess |
dc.format.medium.none.fl_str_mv |
Recurso electrónico |
dc.format.mimetype.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
MDPI AG |
publisher.none.fl_str_mv |
MDPI AG |
dc.source.none.fl_str_mv |
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Universidad Tecnológica de Bolívar |
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2019-11-06T19:05:20Z2019-11-06T19:05:20Z2019Water (Switzerland); Vol. 11, Núm. 22073-4441https://hdl.handle.net/20.500.12585/876510.3390/w11020358Universidad Tecnológica de BolívarRepositorio UTBIn Colombia, daily maximum multiannual series are one of the main inputs for design streamflow calculation, which requires performing a rainfall frequency analysis that involves several prior steps: (a) requesting the datasets, (b) waiting for the information, (c) reviewing the datasets received for missing or data different from the requested variable, and (d) requesting the information once again if it is not correct. To tackle these setbacks, 318 rain gauges located in the Colombian Caribbean region were used to first evaluate whether or not the Gumbel distribution was indeed the most suitable by performing frequency analyses using three different distributions (Gumbel, Generalized Extreme Value (GEV), and Log-Pearson 3 (LP3)); secondly, to generate daily maximum isohyetal maps for return periods of 2, 5, 10, 20, 25, 50, and 100 years; and, lastly, to evaluate which interpolation method (IDW, spline, and ordinary kriging) works best in areas with a varying density of data points. GEV was most suitable in 47.2% of the rain gauges, while Gumbel, in spite of being widely used in Colombia, was only suitable in 34.3% of the cases. Regarding the interpolation method, better isohyetals were obtained with the IDW method. In general, the areal maximum daily rainfall estimated showed good agreement when compared to the true values. © 2019 by the authors.Recurso electrónicoapplication/pdfengMDPI AGhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessAtribución-NoComercial 4.0 Internacionalhttp://purl.org/coar/access_right/c_abf2https://www2.scopus.com/inward/record.uri?eid=2-s2.0-85065059855&doi=10.3390%2fw11020358&partnerID=40&md5=c1657920edd3340b22d4e9d55d1257d0Scopus 57208078895Scopus 57208551562Scopus 57193337460Scopus 55817731200Scopus 36618177700Scopus 54383095000Isohyetal maps of daily maximum rainfall for different return periods for the Colombian Caribbean Regioninfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_2df8fbb1Design rainfallIDEAMInterpolation methodIsohyetal mapStationary frequency analysisStormwater managementRainRain gagesDesign rainfallsFrequency AnalysisIDEAMInterpolation methodStorm-water managementsInterpolationFrequency analysisInterpolationKrigingMapping methodPrecipitation intensityr RaingaugeReturn periodStreamflowWastewater treatmentCaribbean Coast [Colombia]ColombiaGonzález-Álvarez Á.Viloria-Marimón, O.M.Coronado Hernández, Óscar EnriqueVélez-Pereira, A.M.Tesfagiorgis, K.Coronado Hernández, Jairo RafaelChow, V.T., Maidment, D.R., Mays, L.W., (1988) Applied Hydrology, 1st ed, pp. 350-376. , McGraw-Hill: New York, NY, USABedient, P.B., Huber, W.C., (2002) Hydrology and Floodplain Analysis, pp. 168-224. , Prentice-Hall: Upper Saddle River, NJ, USAVargas, M.R., Díaz-Granados, M., (1998) Colombian Regional Synthetic IDF Curves, , Master's Thesis, University of Los Andes, Bogotá, Colombia(2015) New Scenarios of Climate Change for Colombia 2011-2100 Scientific Tools for Department-Based Decision Making-National Emphasis: 3rd National Bulletin on Climate Change, , http://documentacion.ideam.gov.co/openbiblio/bvirtual/022964/documento_nacional_departamental.pdf, accessed on 7 September 2018Intensity-Duration-Frequency Curves (IDF), , http://www.ideam.gov.co/curvasidf, (accessed on 18 March 2018)(2017) Technical Guidelines for the Sector of Potable Water and Basic Sanitation (RAS), , http://www.minvivienda.gov.co/ResolucionesAgua/0330%20-%202017.pdf, accessed on 7 September 2018 Resolution 0330 of 8 June 2017Liu, Y., Zhang, W., Shao, Y., Zhang, K., A Comparison of Four Precipitation Distribution Models Used in Daily Stochastic Models (2011) Adv. Atmos. Sci, 28, pp. 809-820Chowdhury, A.F.M.K., Lockart, N., Willgoose, G., Kuczera, G., Kiem, A.S., Parana Manage, N., Development and evaluation of a stochastic daily rainfall model with long-term variability (2017) Hydrol. Earth Syst. Sci, 21, pp. 6541-6558Pizarro, R., Ingram, B., Gonzalez-Leiva, F., Valdés-Pineda, R., Sangüesa, C., Delgado, N., García-Chevesich, P., Valdés, J.B., WEBSEIDF: A Web-Based System for the Estimation of IDF Curves in Central Chile (2018) Hydrology, 5, p. 40. , https://www.mdpi.com/2306-5338/5/3/40(accessedon25January2019)Burgess, C.P., Taylor, M.A., Stephenson, T., Mandal, A., Frequency analysis, infilling and trends for extreme precipitation for Jamaica (1895-2100) (2015) J. Hydrol, 3, pp. 424-443Seo, Y., Hwang, J., Kim, B., Extreme Precipitation Frequency Analysis Using a Minimum Density Power Divergence Estimator (2017) Water, 9, p. 81Nguyen, V.-T.-B., Nguyen, T.-H., Statistical Modeling of Extreme Rainfall Processes (SMExRain): A Decision Support Tool for Extreme Rainfall Frequency Analyses (2016) In Proceedings of the 12th International Conference on Hydroinformatics, 154, pp. 624-630. , https://ac.els-cdn.com/S1877705816319506/1-s2.0-S1877705816319506-main.pdf?._tid=e587b0ac-b681-4a07-9b9f-28501d3ddf6&acdnat=1549752522_fca135a461dacf0f9e6e06a9eeef2e48, Incheon, Korea, 21-26 August (accesses on 8 February 2019)Ngoc Phien, H., Arbhabhirama, A., Sunchindah, A., Rainfall distribution in northeastern Thailand (2009) Hydrol. Sci. J, 25, pp. 167-182(1990) Maximum Precipitations for 1, 2, and 3 Days, , http://bibliotecadigital.ciren.cl/bitstream/handle/123456789/6582/DGA-HUMED32.pdf?.sequence=1&isAllowed=y, accessed on 25 January 2019(1999) State Secretary of Infrastructure and Transport, General Direction of Roads, , http://epsh.unizar.es/~()serreta/documentos/maximas_Lluvias.pdf, Daily Maximum Rainfall in Peninsular Spain. (accessed on 26 January 2019)Liaw, C.-H., Chiang, Y.-C., Dimensionless Analysis for Designing Domestic Rainwater Harvesting Systems at the Regional Level in Northern Taiwan (2014) Water, 6, pp. 3913-3933(1961) Department of Commerce (USDOC), , Technical Paper No. 40 (TP-40), Rainfall Frequency Atlas of the United States for Durations from 30 Minutes to 24 Hours and Return Periods from 1 to 100 Years;Weather Bureau Technical Papers: Washington, DC, USAJaramillo-Robledo, A., Lluvias máximas en 24 horas para la región Andina de Colombia (24-hour maximum rainfall for the Colombian Andean region) (2005) Cenicafé, 56, pp. 250-268Gutiérrez Jaraba, J., Pérez Márquez, F., Angulo Blanquicett, G., Chiriboga Gavidia, G., Valdés Cervantes, L., Determination of the Intensity-Duration-Frequency (IDF) Curves for the City of Cartagena de Indias for the period between 1970 and 2015 (2017) Proceedings of the Fifteenth LACCEI International Multi-Conference for Engineering, , Education, and Technology: Global Partnerships for Development and Engineering Education, Boca Raton, FL, USA, 19-21 JulyPulgarín Dávila, E.G., (2009) Regional Equations for the Estimation of the Intensity-Duration-Frequency Curves based on the Rainfall Scale Properties (Colombian Andean Region), , Master's Thesis, National University of Colombia, Bogotá, ColombiaAcosta Castellanos, P.M., Sierra Aponte, L.X., IDF construction methods' evaluation, from probability distributions and adjustment's parameters (2013) Revista Facultad Ingeniería, 22, pp. 25-33Becerra-Oviedo, J.A., Sánchez-Mazorca, L.F., Acosta-Castellanos, P.M., Díaz-Arévalo, J.L., Regionalization of IDF curves for the use of hydrometeorological models in the Western Sabana of Cundinamarca department (2015) Revista Ingeniería Región, 14, pp. 143-150Muñoz, B.J.E., Zamudio, H.E., Regionalización de Ecuaciones Para el Cálculo de Curvas de Intensidad, Duración y Frecuencia Mediante Mapas de Isolíneas en el Departamento de Boyacá (Regionalization of the Equations for the Calculation of the IDF Curves through Isohyetals Maps in the Department of Boyacá), , http://www.scielo.org.co/pdf/tecn/v22n58/0123-921X-tecn-22-58-31.pdf, (accessed on 25 January 2019)(2010) General Circulation of the Atmosphere in Colombia, , https://www.cioh.org.co/meteorologia/Climatologia/01-InfoGeneralClimatCaribeCol.pdf, accessed on 7 August 2018Poveda, G., Jaramillo, A., Gil, M.M., Quinceno, N., Mantilla, R.I., Seasonality in ENSO-related precipitation, river discharges, soil moisture, and vegetation index in Colombia (2001) Water Resour. Res, 37, pp. 2169-2178Waylen, P., Poveda, G., El Niño-Southern Oscillation and aspects of western South American hydro-climatology (2002) Hydrol. Process, 16, pp. 1247-1260Poveda, G., Álvarez, D.M., Rueda, O.A., 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 (2011) Clim. Dyn, 36, pp. 2233-2249Hoyos, N., Escobar, J., Restrepo, J.C., Arango, A.M., Ortiz, J.C., Impact of the 2010-2011 La Niña phenomenon in Colombia, South America: The human toll of an extreme weather event (2013) Appl. Geogr, 39, pp. 16-25Ramírez-Cerpa, E., Acosta-Coll, M., Vélez-Zapata, J., Analysis of the climatic conditions for short term precipitation in urban areas: A case study Barranquilla, Colombia (2017) Idesia, 32, pp. 87-94Schneider, L.E., McCuen, R.H., Statistical guidelines for curve number generation (2005) J. Irrig. Drain. Eng, 131, pp. 282-290Macvicar, T.H., (1981) Frequency Analysis of Rainfall Maximums for Central and South Florida, Technical Publication # 81-3, , South Florida Water Management District: West Palm Beach, FL, USAAli, A., Abtew, W., (1999) Regional Rainfall Frequency Analysis for Central and South Florida. Technical Publication WRE#380, , South Florida Water Management District: West Palm Beach, FL, USAPathak, C.S., (2001) Frequency Analysis of Rainfall Maximums for Central and South Florida, Technical Publication EMA # 390, , South Florida Water Management District: West Palm Beach, FL, USAObeysekera, J., Salas, J.D., Quantifying the uncertainty of design floods under nonstationary conditions (2014) J. Hydrol. Eng, 19, pp. 1438-1446Salas, J.D., Obeysekera, J., Vogel, R.M., Techniques for assessing water infrastructure for nonstationary extreme events: A review (2018) Hydrol. Sci. J, 63, pp. 325-352Faber, B., Current methods for hydrologic frequency analysis (2010) Proceedings of the Workshop on Nonstationarity, pp. 33-39. , Hydrologic Frequency Analysis, and Water Management, Colorado Water Institute Information Series No. 109, Boulder, CO, USA, 13-15 JanuaryHaan, C.T., (1977) Statistical Methods in Hydrology, pp. 97-158. , The Iowa State University Press: Ames, IA, USAMcCuen, R.H., (1993) Microcomputer Applications in Statistical Hydrology, pp. 58-69. , Prentice Hall: Englewood Cliffs, NJ, USASingh, V.P., (1988) Entropy-Based Parameter Estimation in Hydrology, , Kluwe Academic Dordrecht: London, UKChin, D.A., (2013) Water-Resources Engineering, 3rd ed, pp. 344-395. , Pearson: London, UKGumbel, E.J., The return period of flood flows (1941) Ann. Math. Stat, 2, pp. 163-190Gumbel, E.J., (1954) Statistical Theory of Extreme Values and Some Practical Applications: A Series of Lectures, , U.S. Dept. of Commerce, National Bureau of Standards Applied Mathematics Series 33U.S. Govt. Print. Office: Springfield, VA, USAJenkinson, A.F., The frequency distribution of the annual maximum (or minimum) values of meteorological elements (1955) Q. J. R. Meteorol. Soc, 81, pp. 158-171Frechet, M., Sur la loi de probabilité de l'ecart máximum (On the probability law of máximum values) (1927) Annales Societe Polonaise Mathematique, 6, pp. 93-116Weibull, W., A statistical theory of the strength of materials (1939) Proc. Ing. Vetensk Akad, 51, pp. 5-45Lazoglou, G., Anagnostopoulou, C., An Overview of Statistical Methods for Studying the Extreme Rainfalls in Mediterranean In Proceedings of the 2nd International Electronic Conference on Atmospheric Sciences, , http://sciforum.net/conference/ecas2017, Basel, Switzerland, 16-31 July 2017(accessed on 4 September 2018)Selaman, O.S., Said, S., Putuhena, F.J., Flood Frequency Analysis for Sarawak using Weibull, Gringorten and L-moments Formula (2007) J. Inst. Eng, 68, pp. 43-52Chikobvu, D., Chifurira, R., Modelling of Extreme Minimum Rainfall Using Generalised Extreme Value Distribution for Zimbabwe (2015) S. Afr. J. Sci, p. 111Millington, M., Das, S., Simonovic, S.P., (2011) The Comparison of GEV, Log-Pearson Type 3 and Gumbel Distributions in the Upper Thames River Watershed under Global Climate Models;Water Resources Research Report (Report # 077), , https://ir.lib.uwo.ca/cgi/viewcontent.cgi?.article=1039&context=wrrr, The University ofWestern Ontario, Department of Civil and Environmental Engineering: London, ON, Canada(accessed on 7 May 2018)Koutsoyiannis, D., Statistics of extremes and estimation of extreme rainfall: II Empirical investigation of long rainfall records (2004) J. Hydrol. Sci. J, 49, p. 610Alam, M.A., Emura, K., Farnham, C., Yuan, J., Best-Fit Probability Distributions and Return Periods for Maximum Monthly Rainfall in Bangladesh (2018) Climate, 6, p. 9. , http://www.mdpi.com/2225-1154/6/1/9, (accessed on 8 August 2018)(1960) Geological Survey (USGS). Flood-Frequency Analyses, Manual of Hydrology: Part 3, Flood-Flow Techniques, , https://pubs.usgs.gov/wsp/1543/report.pdf, U.S. Government Printing Office: Washington, DC, USA(accessed on 10 September 2017)(1965) Geological Survey (USGS). Theoretical Implications of under Fit Streams, Flood-Flow Techniques, , https://pubs.usgs.gov/pp/0452/report.pdf, U.S. Government Printing Office: Washington, DC, USA(accessed on 10 September 2017)Lumia, R., Freehafer, D.A., Smith, M.J., (2006) Magnitude and Frequency of Floods in New York: U.S, , https://pubs.usgs.gov/sir/2006/5112/SIR2006-5112.pdf, Geological Survey Scientific Investigations Report 2006-5112. (accessed on 10 September 2018)Webster, V.L., Stedinger, J., Log-Pearson Type 3 Distribution and Its Application in Flood Frequency Analysis I: Distribution Characteristics (2007) J. Hydrol. Eng, p. 12Greis, N.P., Flood frequency analysis: A review of 1979-1982 (1983) Rev. Geophys, 21, pp. 699-706Vogel, R.M., McMahon, T.A., Chiew, F.H.S., Floodflow frequency model selection in Australia (1993) J. Hydrol, 146, pp. 421-449Jam, P., Singh, V.J., Estimating parameters of EV 1 distribution for flood frequency analysis (1987) J. Am. Water Resour. Assoc, 23, pp. 59-71Ngoc Phien, H., A review of methods of parameter estimation for the extreme value type-1 distribution (1987) J. Hydrol, 90, pp. 251-268Fathi, K., Bagheri, S.F., Alizadeh, M., Alizadeh, M., A study of methods for estimating in the exponentiated Gumbel distribution (2017) J. Stat. Theory Appl, 16, pp. 81-95Sarangi, A., Cox, C.A., Madramootoo, C.A., Geostatistical Methods for Prediction of Spatial Variability of Rainfall in a Mountainous Region (2005) Trans. ASAE, 48, pp. 943-954. , http://digitool.library.mcgill.ca/webclient/StreamGate?.folder_id=0&dvs=1546993372127~()978, (accessed on 5 February 2018)Bhunia, G.S., Shit, P.K., Maiti, R., Comparison of GIS-based interpolation methods for spatial distribution of soil organic carbon (SOC) (2018) J. Saudi Soc. Agric. Sci, 17, pp. 114-126Boer, E.P.J., De Beursl, K.M., Hartkampz, A.D., Kriging and thin plate splines for mapping climate variables (2001) J. Appl. Genet, 3, pp. 146-154Gonzalez, A., Temimi, M., Khanbilvardi, R., Adjustment to the curve number (NRCS-CN) to account for the vegetation effect on hydrological processes (2015) Hydrol. Sci. J, 60, pp. 591-605Moriasi, D.N., Arnold, J.G., Van Liew, M.W., Bingner, R.L., Harmel, R.D., Veith, T.L., Model evaluation guidelines for systematic quantification of accuracy in watershed simulations (2007) Trans. ASABE, 50, pp. 885-900. , http://citeseerx.ist.psu.edu/viewdoc/download?.doi=10.1.1.532.2506&rep=rep1&type=pdf, (accessed on 20 October 2018)Gonzalez-Alvarez, A., Coronado-Hernández, O.E., Fuertes-Miquel, V.S., Ramos, H.M., Effect of the Non-Stationarity of Rainfall Events on the Design of Hydraulic Structures for RunoffManagement and Its Applications to a Case Study at Gordo Creek Watershed in Cartagena de Indias, Colombia (2018) Fluids, 3, p. 27Wang, D., Hagen, S.C.S., Alizad, K., Climate change impact and uncertainty analysis of extreme rainfall events in the Apalachicola River basin, Florida (2012) J. Hydrol, 480, pp. 125-135Li, J., Heap, A.D., (2008) A Review of Spatial Interpolation Methods for Environmental Scientists, , https://pdfs.semanticscholar.org/686c/29a81eab59d7f6b7e2c4b060b1184323122.pdf, Geoscience Australia: Canberra, ACT, Australia(accessed on 23 August 2018)Mitas, L., Mitasova, H., Spatial Interpolation (2005) In Geographic Information Systems: Principles, 1, pp. 481-492. , Techniques, Management and Applications, 2nd ed.;Wiley: Longley, PA, USAIkechukwu, M.N., Ebinne, E., Idorenyin, U., Raphael, N.I., Accuracy Assessment and Comparative Analysis of IDW, Spline and Kriging in Spatial Interpolation of Landform (Topography): An Experimental Study (2017) Earth Environ. Sci, 9, pp. 354-371Curtarelli, M., Leão, J., Ogashawara, I., Lorenzzetti, J., Stech, J., Assessment of Spatial Interpolation Methods to Map the Bathymetry of an Amazonian Hydroelectric Reservoir to Aid in Decision Making for Water Management (2015) Int. J. Geo-Inf, 4, pp. 220-235Simpson, G., Wu, Y.H., Accuracy and Effort of Interpolation and Sampling: Can GIS Help Lower Field Costs? (2014) Int. J. Geo-Inf, 3, pp. 1317-1333Di Piazza, A., Lo Conti, F., Viola, F., Eccel, E., Noto, L.V., Comparative Analysis of Spatial Interpolation Methods in the Mediterranean Area: Application to Temperature in Sicily (2015) Water, 7, pp. 1866-1888Phillips, D.L., Dolph, J., Marks, D., A comparison of geostatistical procedures for spatial analysis of precipitation in mountainous terrain (1992) Agric. For. Meteorol, 58, pp. 119-141Luo, W., Taylor, M.C., Parker, S.R., A comparison of spatial interpolation methods to estimate continuous wind speed surfaces using irregularly distributed data from England andWales (2008) Int. J. Clim, 28, pp. 947-959http://purl.org/coar/resource_type/c_6501ORIGINALDOI10_3390w11020358.pdfapplication/pdf8137592https://repositorio.utb.edu.co/bitstream/20.500.12585/8765/1/DOI10_3390w11020358.pdf6a0b0423ce547628d23cec21dfa2fa3bMD51TEXTDOI10_3390w11020358.pdf.txtDOI10_3390w11020358.pdf.txtExtracted texttext/plain82940https://repositorio.utb.edu.co/bitstream/20.500.12585/8765/4/DOI10_3390w11020358.pdf.txt520e417ad77bf323f714924504e26bd9MD54THUMBNAILDOI10_3390w11020358.pdf.jpgDOI10_3390w11020358.pdf.jpgGenerated Thumbnailimage/jpeg88223https://repositorio.utb.edu.co/bitstream/20.500.12585/8765/5/DOI10_3390w11020358.pdf.jpg58e4dc94f3b3a8448a72768b454529ddMD5520.500.12585/8765oai:repositorio.utb.edu.co:20.500.12585/87652023-05-26 10:50:43.868Repositorio Institucional UTBrepositorioutb@utb.edu.co |