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Oferta hídrica superficial del humedal el Gallinazo
| dc.contributor.author | SALDANA ESCORCIA, ROSSEMBER | |
| dc.contributor.author | OTALVAREZ HERRERA, ROSANA | |
| dc.contributor.author | HERRERA GALVIZ, JUAN DAVID | |
| dc.coverage.spatial | Colombia | en_US |
| dc.date.accessioned | 2026-02-23T15:53:45Z | |
| dc.date.available | 2026-02-23T15:53:45Z | |
| dc.date.issued | 2023 | |
| dc.identifier.issn | 2145-6453 | en_US |
| dc.identifier.uri | https://repositorioinstitucional.ufpso.edu.co/xmlui/handle/20.500.14167/6097 | |
| dc.description.abstract | Contextualización: los humedales se encuentran en deterioro a causa, princi-palmente, de las actividades humanas que provocan procesos de degradación de estos, por los cambios en el uso de los suelos. Esto ocasiona conflictos en-tre quienes viven cerca al humedal y tiene consecuencias en el suministro de los recursos para las poblaciones ale-dañas. En especial, las actividades hu-manas afectan al recurso hídrico, lo que limita los servicios ecosistémicos que los humedales prestan.Vacío de conocimiento: información inexistente sobre la disponibilidad del recurso hídrico en la zona del humed-al, la cual serviría para una gobernan-za del agua eficiente e inclusiva en la zona, que contribuya en la formulación de políticas públicas para la gestión in-tegral del recurso hídrico, y maximice así el bienestar social y económico en el municipio. Para lograr los objetivos mencionados se hace necesario la de-terminación de dicha disponibilidad, con el fin de conservar los ecosistemas de humedal con importancia regional.Propósito: este trabajo estimó la ofer-ta hídrica superficial [neta] disponible, mediante el método lluvia-escorrentía, en el humedal El Gallinazo, ubicado en Aguachica (Cesar–Colombia), como aporte para la gestión integral del re-curso hídrico.Metodología: se identificó de la cober-tura vegetal de la zona por medio de la metodología «Corine Land Cover» adaptada para Colombia y se deter-minó el grupo hidrológico mediante la textura del suelo; con estos dos insu-mos se determinó, a través de tablas, el número de curvas. La investigación incluyó el cálculo de la precipitación media anual, empleando el método de interpolación de Kriging, con ayu-da del software ArcGIS y la evaluación de los datos meteorológicos extraídos de estaciones del IDEAM [Instituto de Hidrología, Meteorología y Estudios Ambientales] para determinar la pre-cipitación efectiva de la zona. Además, se utilizó el método lluvia-escorrentía en función del número de curvas [SCS-CN] y se examinó la resolución 865 de 2004 (Ministerio de Ambiente Vivienda y Desarrollo Territorial, 2004) para esta-blecer la oferta hídrica neta disponible del humedal El Gallinazo.Resultados y conclusiones: la zona po-see dos tipos de coberturas vegetales, tres grupos hidrológicos de suelo y un CN promedio de 59,29, demostrando un potencial de escorrentía modera-damente alto y una capacidad de in-filtración moderada; la oferta hídrica m3. El comportamiento de la disponib-ilidad del agua depende de las activi-dades antrópicas desarrolladas dentro y fuera del humedal, así como del régi-men de precipitación. | en_US |
| dc.language.iso | eng | en_US |
| dc.relation | https://hemeroteca.unad.edu.co/index.php/riaa/article/view/5959 | en_US |
| dc.title | Oferta hídrica superficial del humedal el Gallinazo | en_US |
| dc.title.translated | Surface water supply of the Gallinazo wetland | en_US |
| dc.contributor.cvlac | 0000116197 | en_US |
| dc.contributor.cvlac | 0000116200 | en_US |
| dc.contributor.cvlac | 0001541907 | en_US |
| dc.contributor.googlescholar | dHFj0ycAAAAJ&hl | en_US |
| dc.contributor.googlescholar | uzH7pZcAAAAJ&hl | en_US |
| dc.contributor.orcid | 0000-0002-5290-7072 | en_US |
| dc.contributor.orcid | 0000-0002-7636-5853 | en_US |
| dc.contributor.researchgate | Rossember-Saldana-Escorcia | en_US |
| dc.contributor.researchgate | Rosana-Herrera | en_US |
| dc.contributor.researchgate | Juan-Herrera-Galviz | en_US |
| dc.contributor.scopus | 57212698376 | en_US |
| dc.description.abstractenglish | Context: Wetlands are deteriorating primarily due to human activities that cause degradation processes through changes in land use. This leads to conflicts among those living near the wetland and has consequences for the supply of resources to neighboring populations. In particular, human activities affect water resources, limiting the ecosystem services that wetlands provide. Knowledge gap: There is a lack of information on the availability of water resources in the wetland area, which would be useful for efficient and inclusive water governance in the area. This would contribute to the formulation of public policies for the integrated management of water resources, thereby maximizing social and economic well-being in the municipality. To achieve the aforementioned objectives, it is necessary to determine this availability in order to conserve wetland ecosystems of regional importance. Purpose: This work estimated the available [net] surface water supply, using the rainfall-runoff method, in the El Gallinazo wetland, located in Aguachica (Cesar–Colombia), as a contribution to the integrated management of the water resource. Methodology: The vegetation cover of the area was identified using the "Corine Land Cover" methodology adapted for Colombia, and the hydrological group was determined by soil texture; with these two inputs, the number of curves was determined using tables. The research included calculating the average annual precipitation using the Kriging interpolation method with the aid of ArcGIS software and evaluating meteorological data from IDEAM (Institute of Hydrology, Meteorology and Environmental Studies) stations to determine the effective precipitation of the area. Additionally, the rainfall-runoff method based on the number of curves (SCS-CN) was used, and Resolution 865 of 2004 (Ministry of Environment, Housing and Territorial Development, 2004) was examined to establish the net available water supply of the El Gallinazo wetland. Results and conclusions: the area has two types of vegetation cover, three hydrological soil groups, and an average CN of 59.29, demonstrating a moderately high runoff potential and a moderate infiltration capacity; the water supply is [m3]. The behavior of water availability depends on human activities carried out inside and outside the wetland, as well as the precipitation regime. | en_US |
| dc.subject.proposal | Cobertura vegetal, disponibilidad de agua, humedal, llu-via-escorrentía, método SCS-CN. | en_US |
| dc.subject.proposal | Cobertura vegetal, disponibilidad de agua, humedal, llu-via-escorrentía, método SCS-CN. | en_US |
| dc.subject.keywords | Vegetation cover, water availability, wetland, rainfall-via-runoff, SCS-CN method. | en_US |
| dc.subject.keywords | Vegetation cover, water availability, wetland, rainfall-via-runoff, SCS-CN method. | en_US |
| dc.publisher.faculty | Facultad ciencias agrarias y del ambiente | en_US |
| dc.type.redcol | http://purl.org/redcol/resource_type/ART | en_US |
| dc.relation.references | Bal, M., Dandpat, A. K. & Naik, B. (2021). Hydrological modeling with respect to impact of land-use and land-cover change on the runoff dy-namics in Budhabalanga river basing using ArcGIS and SWAT model. Re-mote Sensing Applications: Society and Environment, 23, 100527. https://doi.org/10.1016/j.rsase.2021.100527 | en_US |
| dc.relation.references | Bao, G., Bao, Y., Sanjjava, A., Qin, Z., Zhou, Y. & Xu, G. (2015). NDVI-indi-spheres, 120(10), 4534–4550. https://doi.org/10.1002/2014JD022558 | en_US |
| dc.relation.references | Bégué, A., Vintrou, E., Ruelland, D., Claden, M. & Dessay, N. (2011). Can a 25-year trend in Soudano-Sahelian vegetation dynamics be interpreted in terms of land use change? A re-mote sensing approach. Global En-vironmental Change, 21(2), 413–420. https://doi.org/10.1016/j.gloenv-cha.2011.02.002 | en_US |
| dc.relation.references | Biau, G., Zorita, E., von Storch, H. & Wackernagel, H. (1999). Estimation of Precipitation by Kriging in the EOF Space of the Sea Level Pressure Field. Journal of Climate, 12(4), 1070–1085. https://doi.org/10.1175/1520-0442(1999)012<1070:EOPBKI>2.0.CO;2 | en_US |
| dc.relation.references | Braud, I., Breil, P., Thollet, F., Lagouy, M., Branger, F., Jacqueminet, C., Ker-madi, S. & Michel, K. (2013). Evi-dence of the impact of urbanization on the hydrological regime of a me-dium-sized periurban catchment in France. Journal of Hydrology, 485, 5–23. https://doi.org/10.1016/j.jhy-drol.2012.04.049 | en_US |
| dc.relation.references | Brown, A. E., Zhang, L., McMahon, T. A., Western, A. W. & Vertessy, R. A. (2005). A review of paired catchment studies for determining changes in water yield resulting from alter-ations in vegetation. Journal of Hy-drology, 310(1–4), 28–61. https://doi.org/10.1016/j.jhydrol.2004.12.010 | en_US |
| dc.relation.references | Caicedo, M. A. (2019). Evaluación del índice de escasez para aguas superficia-les mediante el cálculo de la demanda y disponibilidad hídrica de la microcuen-ca del Río Mulato, municipio de Mo-de la demanda de agua bajo escenari-os de cambio climático. Ribagua, 2(1), 3–13. https://doi.org/10.1016/j.riba.2015.04.001 | en_US |
| dc.relation.references | Chen, T., de Jeu, R. A. M., Liu, Y. Y., van der Werf, G. R. & Dolman, A. J. (2014). Using satellite based soil moisture to quantify the water driven variability in NDVI: A case study over main-land Australia. Remote Sensing of En-vironment, 140, 330–338. https://doi.org/10.1016/j.rse.2013.08.022 | en_US |
| dc.relation.references | Córdoba, E. (2021). Evaluación del índice de escasez para aguas superficiales me-diante el cálculo de la oferta y demanda hídrica en la microcuenca del río palo en el municipio de Puerto Tejada (Cau-ca) [Tesis de pregrado, Corporación Universitaria Autónoma Del Cauca]. Repositorio institucional. https://re-positorio.uniautonoma.edu.co/han-dle/123456789/596 | en_US |
| dc.relation.references | Das, S. & Islam, A. R. M. T. (2021). As-sessment of mapping of annual aver-age rainfall in a tropical country like Bangladesh: remotely sensed output vs. kriging estimate. Theoretical and Applied Climatology, 146, 111–123. https://doi.org/10.1007/s00704-021-03729-3 | en_US |
| dc.relation.references | Daza, M. C., Hernández, F. y Triana, F. A. (2014). Efecto del Uso del Suelo en la Capacidad de Almacenamiento Hídrico en el Páramo de Sumapaz - Colombia. Revista Facultad Nacional de Agronomía Medellín, 67(1), 7189–7200. https://doi.org/10.15446/rf-nam.v67n1.42642 | en_US |
| dc.relation.references | Duan, L., Huang, M. & Zhang, L. (2016). Differences in hydrological respons-https://repository.ucatolica.edu.co/handle/10983/2727 | en_US |
| dc.relation.references | Hostache, R., Chini, M., Giustarini, L., Neal, J., Kavetski, D., Wood, M., Co-rato, G., Pelich, R. & Matgen, P. (2018). Near‐Real‐Time Assimilation of SAR‐Derived Flood Maps for Improving Flood Forecasts. Water Resources Re-search, 54(8), 5516–5535. https://doi.org/10.1029/2017WR022205 | en_US |
| dc.relation.references | Hughes, D. A. & Farinosi, F. (2020). Assessing development and climate variability impacts on water resourc-es in the Zambezi River basin. Simu-lating future scenarios of climate and development. Journal of Hydrology: Regional Studies, 32, 100763. https://doi.org/10.1016/j.ejrh.2020.100763 | en_US |
| dc.relation.references | Hughes, D., Mantel, S. & Farinosi, F. (2020). Assessing development and climate variability impacts on water resources in the Zambezi River ba-sin: Initial model calibration, uncer-tainty issues and performance. Jour-nal of Hydrology: Regional Studies, 32, 100765. https://doi.org/10.1016/j.ejrh.2020.100765 | en_US |
| dc.relation.references | Kang, H. & Sridhar, V. (2017). Com-bined statistical and spatially dis-tributed hydrological model for evaluating future drought indices in Virginia. Journal of Hydrology: Region-al Studies, 12, 253–272. https://doi.org/10.1016/j.ejrh.2017.06.003 | en_US |
| dc.relation.references | Kumar, A., Kanga, S., Taloor, A. K., Singh, S. K. & Đurin, B. (2021). Sur-face runoff estimation of Sind river basin using integrated SCS-CN and GIS techniques. HydroResearch, 4,mx/scielo.php?script=sci_arttex-t&pid=S1405-31952013000800001 | en_US |
| dc.relation.references | Manz, B., Buytaert, W., Zulkafli, Z., La-vado, W., Willems, B., Robles, L. A. & Rodríguez‐Sánchez, J. P. (2016). High‐resolution satellite‐gauge mer-ged precipitation climatologies of the Tropical Andes. Journal of Geophy-sical Research: Atmospheres, 121(3), 1190–1207. https://doi.org/10.1002/2015JD023788 | en_US |
| dc.relation.references | Mehvar, S., Filatova, T., Sarker, M. H., Dastgheib, A. & Ranasinghe, R. (2019). Climate change-driven los-ses in ecosystem services of coas-tal wetlands: A case study in the West coast of Bangladesh. Ocean & Coastal Management, 169, 273–283. https://doi.org/10.1016/j.oce-coaman.2018.12.009 | en_US |
| dc.relation.references | Meng, F., Su, F., Yang, D., Tong, K. & Hao, Z. (2016). Impacts of recent climate change on the hydrology in the source region of the Yellow Ri-ver basin. Journal of Hydrology: Re-gional Studies, 6, 66–81. https://doi.org/10.1016/j.ejrh.2016.03.003 | en_US |
| dc.relation.references | Meraj, G., Khan, T., Romshoo, S. A., Farooq, M., Rohitashw, K. & Sheikh, B. A. (2018). An Integrated Geoin-formatics and Hydrological Mode-lling-Based Approach for Effective Flood Management in the Jhelum Ba-sin, NW Himalaya. Proceedings, 7(1), 8. https://doi.org/10.3390/ECWS-3-05804 | en_US |
| dc.relation.references | Resolución 865 de 2004. (2004, 4 de agosto). Ministerio de Ambiente, Vi-vienda y Desarrollo Territorial. Dia-rio oficial N.o 45630. https://www.model for the Upper Benue River Basin, Northern Cameroon. Jour-nal of Hydrology: Regional Studies, 36, 100849. https://doi.org/10.1016/j.ejrh.2021.100849 | en_US |
| dc.relation.references | Pachauri, R. K., Allen, M. R., Barros, V. R., Broome, J., Cramer, W., Christ, R., Church, J. A., Clarke, L., Dahe, Q., Dasgupta, P., Dubash, N. K., Edenhofer, O., Elgizouli, I., Field, C. B., Forster, P., Friedlingstein, P., & Fuglestvedt, J, J. P. (2014). Climate Change 2014: Synthesis Report. Contri-bution of Working Groups I, II and III to the Fifth Assessment Report of the Inter-governmental Panel on Climate Change. Intergovernmental Panel on Climate Change. | en_US |
| dc.relation.references | Pan, Z., Liu, P., Xu, C.-Y., Cheng, L., Tian, J., Cheng, S., & Xie, K. (2020). The influence of a prolonged me-teorological drought on catchment water storage capacity: a hydrologi-cal-model perspective. Hydrology and Earth System Sciences, 24(9), 4369–4387. https://doi.org/10.5194/hess-24-4369-2020 | en_US |
| dc.relation.references | Parra, V., Fuentes-Aguilera, P. & Muñoz, E. (2018). Identifying advantages and drawbacks of two hydrological mod-els based on a sensitivity analysis: a study in two Chilean watersheds. Hydrological Sciences Journal, 63(12), 1831–1843. https://doi.org/10.1080/02626667.2018.1538593 | en_US |
| dc.relation.references | Peng, X., Shen, H., Zhang, L., Zeng, C., Yang, G., & He, Z. (2016). Spatially continuous mapping of daily glob-al ozone distribution (2004–2014) with the Aura OMI sensor. JournalPeng, X., Shen, H., Zhang, L., Zeng, C., Yang, G., & He, Z. (2016). Spatially continuous mapping of daily glob-al ozone distribution (2004–2014) with the Aura OMI sensor. Journal | en_US |
| dc.relation.references | Salazar, D. A. (2016). Procedimiento para calcular la oferta hídrica superficial por método relación lluvia-escorrentía, caso de estudio cuenca de la quebrada Apauta para el año 2015 [Tesis de es-pecialización, Universidad Militar Nueva Granada]. Repositorio Insti-tucional UMNG. http://hdl.handle.net/10654/15513%0ACollections | en_US |
| dc.relation.references | Saldaña-Escorcia, R. & Otalvarez-He-rrera, R. (2021) Evaluación de la re-carga hídrica en relación a la capaci-dad de retención y almacenamiento de agua del humedal El Gallina-zo en Aguachica - Cesar. Aguachi-ca. http://dx.doi.org/10.13140/RG.2.2.34632.44802/1 | en_US |
| dc.relation.references | Shi, W. & Wang, N. (2020). An Impro-ved SCS-CN Method Incorporating Slope, Soil Moisture, and Storm Duration Factors for Runoff Predic-tion. Water, 12(5), 1335. https://doi.org/10.3390/w12051335 | en_US |
| dc.relation.references | Shi, Z.H., Chen, L.-D., Fang, N.-F., Qin, D.-F. & Cai, C.-F. (2009). Research on the SCS-CN initial abstraction ratio using rainfall-runoff event analy-sis in the Three Gorges Area, China. CATENA, 77(1), 1–7. https://doi.or-g/10.1016/j.catena.2008.11.006 | en_US |
| dc.relation.references | Singh, P. K., Mishra, S. K., Berndtsson, R., Jain, M. K. & Pandey, R. P. (2015). Development of a Modified SMA Based MSCS-CN Model for Runoff Estimation. Water Resources Manage-ment, 29(11), 4111–4127. https://doi.org/10.1007/s11269-015-1048-1ty of Civil Engineers. https://doi.org/10.1061/9780784410042 | en_US |
| dc.relation.references | Tigkas, D., Vangelis, H. & Tsakiris, G. (2016). Introducing a Modified Re-connaissance Drought Index (RDIe) Incorporating Effective Precipi-tation. Procedia Engineering, 162, 332–339. https://doi.org/10.1016/j.proeng.2016.11.072 | en_US |
| dc.relation.references | Trigg, M. A. & Tshimanga, R. M. (2020). Capacity Building in the Congo Basin: Rich Resources Requiring Sustain-able Development. One Earth, 2(3), 207–210. https://doi.org/10.1016/j.oneear.2020.02.008 | en_US |
| dc.relation.references | Tshimanga, R. M., Hughes, D. A. & Kapangaziwiri, E. (2011). Initial cali-bration of a semi-distributed rainfall runoff model for the Congo River ba-sin. Physics and Chemistry of the Earth, 36(14–15), 761–774. https://doi.or-g/10.1016/j.pce.2011.07.045 | en_US |
| dc.relation.references | Verma, S., Singh, P. K., Mishra, S. K., Singh, V. P., Singh, V. & Singh, A. (2020). Activation soil moisture ac-counting (ASMA) for runoff estima-tion using soil conservation service curve number (SCS-CN) method. Journal of Hydrology, 589, 125114. https://doi.org/10.1016/j.jhy-drol.2020.125114 | en_US |
| dc.relation.references | Wagner, P. D., Fiener, P., Wilken, F., Kumar, S. & Schneider, K. (2012). Comparison and evaluation of spa-tial interpolation schemes for daily rainfall in data scarce regions. Jour-nal of Hydrology, 464–465, 388–400. https://doi.org/10.1016/j.jhy-drol.2012.07.026using the dimension-adaptive key grid calibration strategy. Journal of Hydrology, 598, 125772. https://doi.org/10.1016/j.jhydrol.2020.125772 | en_US |
| dc.relation.references | Xu, P., Wang, D., Singh, V. P., Wang, Y., Wu, J., Wang, L., Zou, X., Liu, J., Zou, Y. & He, R. (2018). A kriging and en-tropy-based approach to raingauge network design. Environmental Re-search, 161, 61–75. https://doi.or-g/10.1016/j.envres.2017.10.038 | en_US |
| dc.relation.references | Yan, B., Fang, N. F., Zhang, P. C. & Shi, Z. H. (2013). Impacts of land use change on watershed streamflow and sediment yield: An assessment using hydrologic modelling and par-tial least squares regression. Journal of Hydrology, 484, 26–37. https://doi.org/10.1016/j.jhydrol.2013.01.008 | en_US |
| dc.relation.references | Zhang, S., Li, Z., Hou, X. & Yi, Y. (2019). Impacts on watershed-scale runoff and sediment yield resulting from synergetic changes in climate and vegetation. CATENA, 179, 129–138. https://doi.org/10.1016/j.cate-na.2019.04.007cated long-term vegetation dynam-ics in Mongolia and their response to climate change at biome scale. Inter-national Journal of Climatology, 35(14), 4293–4306. https://doi.org/10.1002/joc.4286 | en_US |
| dc.relation.references | Bechler, A., Vrac, M. & Bel, L. (2015). A spatial hybrid approach for down-scaling of extreme precipitation fields. Journal of Geophysical Research: Atmo-coa [Tesis de pregrado, Corporación Universitaria Autónoma Del Cauca]. Repositorio institucional. https://re-positorio.uniautonoma.edu.co/han-dle/123456789/26 | en_US |
| dc.relation.references | Caletka, M., Šulc, M., Karásek, P. & Fučík, P. (2020). Improvement of SCS-CN Initial Abstraction Coefficient in the Czech Republic: A Study of Five Catchments. Water, 12(7), 1964. https://doi.org/10.3390/w12071964 | en_US |
| dc.relation.references | Camera, C., Bruggeman, A., Hadjinico-laou, P., Pashiardis, S. & Lange, M. A. (2014). Evaluation of interpolation techniques for the creation of grid-ded daily precipitation (1 × 1 km 2 ); Cyprus, 1980-2010. Journal of Geo-physical Research: Atmospheres, 119(2), 693–712. https://doi.org/10.1002/2013JD020611 | en_US |
| dc.relation.references | Centro Internacional de Agricultura Tropical, Corporación BIOTEC, & Universidad Nacional de Colombia. (2006). RASTA Rapid Soil and Ter-rainm Assessment: Guía práctica para la caracterización del suelo y del terreno2.a ed.). Centro Internacional de Ag-ricultura Tropical (CIAT). https://cgspace.cgiar.org/bitstream/han-dle/10568/69682/RASTA_2011.pd-f?sequence=2&isAllowed=y | en_US |
| dc.relation.references | Chatanga, P., Kotze, D. C., Okello, T. W. & Sieben, E. J. J. (2020). Ecosystem ser-vices of high-altitude Afromontane palustrine wetlands in Lesotho. Eco-system Services, 45, 101185. https://doi.org/10.1016/j.ecoser.2020.101185 | en_US |
| dc.relation.references | Chávez-Jiménez, A. y González-Zeas, D. (2015). El impacto de los caudales medioambientales en la satisfacciónes for different vegetation types on a steep slope on the Loess Plateau, China. Journal of Hydrology, 537, 356–366. https://doi.org/10.1016/j.jhy-drol.2016.03.057 | en_US |
| dc.relation.references | Fay, P. A., Guntenspergen, G. R., Olker, J. H. & Johnson, W. C. (2016). Climate change impacts on freshwater wet-land hydrology and vegetation cover cycling along a regional aridity gra-dient. Ecosphere, 7(10). https://doi.org/10.1002/ecs2.1504 | en_US |
| dc.relation.references | Gabriels, K., Willems, P. & Orshoven, J. V. (2021). Performance evaluation of spatially distributed, CN-based rainfall-runoff model configurations for implementation in spatial land use optimization analyses. Journal of Hydrology, 602, 126872. https://doi.org/10.1016/j.jhydrol.2021.126872 | en_US |
| dc.relation.references | Gao, S., Liu, P., Pan, Z., Ming, B., Guo, S., Cheng, L. & Wang, J. (2019). In-corporating reservoir impacts into flood frequency distribution func-tions. Journal of Hydrology, 568, 234–246. https://doi.org/10.1016/j.jhy-drol.2018.10.061 | en_US |
| dc.relation.references | Govindaraju, R. S., Kavvas, M. L. & Tay-fur, G. (1992). A simplified model for two-dimensional overland flows. Ad-vances in Water Resources, 15(2), 133–141. https://doi.org/10.1016/0309-1708(92)90040-9 | en_US |
| dc.relation.references | Gutiérrez-Forero, C. P., Díaz-Mena, C. y Muñoz-Cifuentes, J. N. (2015). Cál-culo del índice de escasez de la cuenca del río Opia, departamento del Tolima[Tesis de especialización, Universi-dad Católica de Colombia]. RIUCaC61–74. https://doi.org/10.1016/j.hy-dres.2021.08.001 | en_US |
| dc.relation.references | Kumar, T. & Jhariya, D. C. (2017). Iden-tification of rainwater harvesting sites using SCS-CN methodology, remote sensing and Geographical Information System techniques. Geo-carto International, 32(12), 1367–1388. https://doi.org/10.1080/10106049.2016.1213772 | en_US |
| dc.relation.references | Lian, H., Yen, H., Huang, J.-C., Feng, Q., Qin, L., Bashir, M. A., Wu, S., Zhu, A.-X., Luo, J., Di, H., Lei, Q., & Liu, H. (2020). CN-China: Revised runoff curve number by using rain-fall-runoff events data in China. Wa-ter Research, 177, 115767. https://doi.org/10.1016/j.watres.2020.115767 | en_US |
| dc.relation.references | Ling, L., Yusop, Z., Yap, W.-S., Tan, W. L., Chow, M. F. & Ling, J. L. (2019). A Calibrated, Watershed-Specific SCS-CN Method: Application to Wangji-aqiao Watershed in the Three Gorges Area, China. Water, 12(1), 60. https://doi.org/10.3390/w12010060 | en_US |
| dc.relation.references | Liu, S., Huang, S., Xie, Y., Wang, H., Huang, Q., Leng, G., Li, P. & Wang, L. (2019). Spatial-temporal changes in vegetation cover in a typical semi-hu-mid and semi-arid region in China: Changing patterns, causes and im-plications. Ecological Indicators, 98, 462–475. https://doi.org/10.1016/j.ecolind.2018.11.037 | en_US |
| dc.relation.references | Magaña-Hernández, F., Bâ, K. M. y Guer-ra-Cobián, V. H. (2013). Estimación del hidrograma de crecientes con model-ación determinística y precipitación derivada de radar. Agrociencia, 47(8), 739–752. http://www.scielo.org.Vol. 14 No. 1 • enero - junio • 2023 / ISSN: 2145-6453 / pp. 221 - 249corpamag.gov.co/archivos/norma-tividad/Resolucion865_20040722.htm | en_US |
| dc.relation.references | Mozo, J., Varni, M., Ares, M. G, & Chagas, C. I. (2020). Rainfall-runoff hydrological modeling of an agri-cultural watershed of Azul district, Buenos Aires. Ciencia Del Suelo, 38(1), 121–132. https://agris.fao.org/agris-search/search.do?recordID=A-R2021A00838 | en_US |
| dc.relation.references | Muñoz, E., Arumí, J. L., Wagener, T., Oyarzún, R & Parra, V. (2016). Unra-veling complex hydrogeological pro-cesses in Andean basins in south-cen-tral Chile: An integrated assessment to understand hydrological dissimi-larity. Hydrological Processes, 30(26), 4934–4943. https://doi.org/10.1002/hyp.11032 | en_US |
| dc.relation.references | Negi, A., Rawat, K. S., Nainwal, A., Shah, M. C. & Kumar, V. (2021). Qua-lity analysis of statistical and da-ta-driven rainfall-runoff models for a mountainous catchment. Materials Today: Proceedings, 46, 10376–10383. https://doi.org/10.1016/j.mat-pr.2020.12.544 | en_US |
| dc.relation.references | Nonki, R. M., Lenouo, A., Lennard, C. J. & Tchawoua, C. (2019). Assessing climate change impacts on water resources in the Benue River Basin, Northern Cameroon. Environmental Earth Sciences, 78(20), 606. https://doi.org/10.1007/s12665-019-8614-4 | en_US |
| dc.relation.references | Nonki, R. M., Lenouo, A., Tshimanga, R. M., Donfack, F. C. & Tchawoua, C. (2021). Performance assessment and uncertainty prediction of a daily ti-me-step HBV-Light rainfall-runoff Área ambientalof Geophysical Research: Atmospheres, 121(21), 702-722. https://doi.or-g/10.1002/2016JD025013 | en_US |
| dc.relation.references | Přibáň, K. & Ondok, J. P. (1985). Heat balance components and evapo-transpiration from a sedge-grass marsh. Folia Geobotanica et Phytota-xonomica, 20(1), 41–56. https://doi.org/10.1007/BF02856464 | en_US |
| dc.relation.references | Rebelo, A. J., Morris, C., Meire, P. & Es-ler, K. J. (2019). Ecosystem services provided by South African palmiet wetlands: A case for investment in strategic water source areas. Ecologi-cal Indicators, 101, 71–80. https://doi.org/10.1016/j.ecolind.2018.12.043 | en_US |
| dc.relation.references | Revueltas, J. E., Zabaleta, A., Mercado, T. y Aguirre, S. (2020). Cambios en el clima local y su efecto en la regulación hídrica en microcuencas del departa-mento del Magdalena, Norte de Co-lombia. Información Tecnológica, 31(6), 193–206. https://doi.org/10.4067/S0718-07642020000600193 | en_US |
| dc.relation.references | Rousis, N. I., Bade, R., Bijlsma, L., Zuc-cato, E., Sancho, J. V., Hernández, F., & Castiglioni, S. (2017). Monitoring a large number of pesticides and trans-formation products in water samples from Spain and Italy. Environmental Research, 156, 31–38. https://doi.or-g/10.1016/j.envres.2017.03.013 | en_US |
| dc.relation.references | Ruales, M. E. y Dávila, N. J. (2019). Efec-tos del cambio del uso del suelo sobre el servicio ecosistémico hídrico de pro-visión en la microcuenca del río Itam-bi [Tesis de pregrado, Universidad Técnica del Norte]. Repositorio Dig-ital Universidad Técnica del Norte. | en_US |
| dc.relation.references | Skaugen, T., Peerebom, I. O. & Nilsson, A. (2015). Use of a parsimonious ra-infall-run-off model for predicting hydrological response in ungauged basins. Hydrological Processes, 29(8), 1999–2013. https://doi.org/10.1002/hyp.10315 | en_US |
| dc.relation.references | Soulis, K. X. (2021). Soil Conservation Service Curve Number (SCS-CN) Method: Current Applications, Re-maining Challenges, and Future Perspectives. Water, 13(2), 192. ht-tps://doi.org/10.3390/w1302019 | en_US |
| dc.relation.references | Soulis, K. X. & Valiantzas, J. D. (2012). SCS-CN parameter determination using rainfall-runoff data in hetero-geneous watersheds – the two-CN system approach. Hydrology and Ear-th System Sciences, 16(3), 1001–1015. https://doi.org/10.5194/hess-16-1001-2012 | en_US |
| dc.relation.references | Tajiki, M., Schoups, G., Hendricks, H. J., Najafinejad, A. & Bahremand, A. (2020). Recursive Bayesian Estima-tion of Conceptual Rainfall‐Runoff Model Errors in Real‐Time Predic-tion of Streamflow. Water Resources Research, 56(2), 1-25. https://doi.or-g/10.1029/2019WR025237 | en_US |
| dc.relation.references | Tegegne, G., Park, D. K. & Kim, Y.O. (2017). Comparison of hydrological models for the assessment of water resources in a data-scarce region, the Upper Blue Nile River Basin. Jour-nal of Hydrology: Regional Studies, 14, 49–66. https://doi.org/10.1016/j.ejrh.2017.10.002 | en_US |
| dc.relation.references | American Society of Civil Engineers. (2009). Curve number hydrology: sta-te of the practice. American Socie-Wang, X. L. & Lin, A. (2015). An algo-rithm for integrating satellite precip-itation estimates with in situ precip-itation data on a pentad time scale. Journal of Geophysical Research: Atmo-spheres, 120(9), 3728–3744. https://doi.org/10.1002/2014JD022788 | en_US |
| dc.relation.references | Watson, A., Miller, J., Fleischer, M. & de Clercq, W. (2018). Estimation of groundwater recharge via percola-tion outputs from a rainfall/runoff model for the Verlorenvlei estuarine system, west coast, South Africa. Journal of Hydrology, 558, 238–254. https://doi.org/10.1016/j.jhy-drol.2018.01.028 | en_US |
| dc.relation.references | Webster, R. & Oliver, M. A. (2007). Geo-statistics for environmental scientists(2nd ed.). John Wiley & Sons Ltd Xie, K., Liu, P., Zhang, J., Han, D., Wang, G. & Shen, C. (2021). Phys-ics-guided deep learning for rain-fall-runoff modeling by considering extreme events and monotonic rela-tionships. Journal of Hydrology, 603, 127043. https://doi.org/10.1016/j.jhydrol.2021.127043 | en_US |
| dc.relation.references | Xie, K., Liu, P., Zhang, J., Libera, D. A., Wang, G., Li, Z. & Wang, D. (2020). Verification of a New Spatial Distri-bution Function of Soil Water Stor-age Capacity Using Conceptual and SWAT Models. Journal of Hydrologic Engineering, 25(3), 04020001. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001887 | en_US |
| dc.relation.references | Xie, K., Liu, P., Zhang, J., Wang, G., Zhang, X. & Zhou, L. (2021). Iden-tification of spatially distributed parameters of hydrological models Zhang, X., Liu, P., Zhao, Y., Deng, C., Li, Z. & Xiong, M. (2018). Error correc-tion-based forecasting of reservoir water levels: Improving accuracy over multiple lead times. Environ-mental Modelling & Software, 104, 27–39. https://doi.org/10.1016/j.env-soft.2018.02.017 | en_US |
| dc.relation.references | Zhou, X., Wang, F., Huang, K., Zhang, H., Yu, J. & Han, A. Y. (2021). System Dynamics-Multiple Objective Opti-mization Model for Water Resource Management: A Case Study in Jia-xing City, China. Water, 13(5), 671.https://doi.org/10.3390/w1305067 | en_US |
| dc.relation.references | Zhu, J., Sun, G., Li, W., Zhang, Y., Miao, G., Noormets, A., McNulty, S. G., King, J. S., Kumar, M. & Wang, X. (2017). Modeling the potential im-pacts of climate change on the water table level of selected forested wet-lands in the southeastern United Sta-tes. Hydrology and Earth System Scien-ces, 21(12), 6289–6305. https://doi.org/10.5194/hess-21-6289-2017 | en_US |
| dc.identifier.DOI | 10.22490/21456453.5959 | en_US |
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