Copyright (c) 2022 Revista de Investigación Agraria y Ambiental
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
When RIAA receives the postulation of an original by its author, either through email or post mail, considers that it can be published in physical and/or electronic format and facilitates its inclusion in databases, newspaper archives and other systems and indexing process. RIAA authorizes the reproduction and citation of the Journal’s material, provided that explicitly indicates journal name, the authors, the article title, volume, number and pages. The ideas and concepts expressed in the articles are responsibility of the authors and in no case reflect the institutional policies of the UNAD.
Supply of surface water in “El Gallinazo” wetland, located on Aguachica-Colombia
Results and conclusions: The area has two types of vegetation cover, three hydrological soil groups and an average NC of 59.29, demonstrating a moderately high runoff potential and a moderate infiltration capacity; the available annual water supply was 42573.6 m3. The behavior of water availability depends on anthropic activities inside and outside the wetland as well as on the precipitation regime.
Bal, M., Dandpat, A. K., & Naik, B. (2021). Hydrological modeling with respect to impact of land-use and land-cover change on the runoff dynamics in Budhabalanga river basing using ArcGIS and SWAT model. Remote Sensing Applications: Society and Environment, 23, 100527. https://doi.org/10.1016/j.rsase.2021.100527
Bao, G., Bao, Y., Sanjjava, A., Qin, Z., Zhou, Y., & Xu, G. (2015). NDVI-indicated long-term vegetation dynamics in Mongolia and their response to climate change at biome scale. International Journal of Climatology, 35(14), 4293–4306. https://doi.org/10.1002/joc.4286
Bechler, A., Vrac, M., & Bel, L. (2015). A spatial hybrid approach for downscaling of extreme precipitation fields. Journal of Geophysical Research: Atmospheres, 120(10), 4534–4550. https://doi.org/10.1002/2014JD022558
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 remote sensing approach. Global Environmental Change, 21(2), 413–420. https://doi.org/10.1016/j.gloenvcha.2011.02.002
Biau, G., Zorita, E., von Storch, H., & Wackernagel, H. (1999). Estimation of Precipitation by Kriging in the EOF Space of theSea 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
Braud, I., Breil, P., Thollet, F., Lagouy, M., Branger, F., Jacqueminet, C., Kermadi, S., & Michel, K. (2013). Evidence of the impact of urbanization on the hydrological regime of a medium-sized periurban catchment in France. Journal of Hydrology, 485, 5–23. https://doi.org/10.1016/j.jhydrol.2012.04.049
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 alterations in vegetation. Journal of Hydrology, 310(1–4), 28–61. https://doi.org/10.1016/j.jhydrol.2004.12.010
Caicedo Lagos, M. A. (2019). Evaluación del índice de escasez para aguas superficiales mediante el cálculo de la demanda y disponibilidad hídrica de la microcuenca del Río Mulato, municipio de Mocoa. Corporación Universitaria Autónoma Del Cauca.
Caletka, M., Šulc Michalková, 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
Camera, C., Bruggeman, A., Hadjinicolaou, P., Pashiardis, S., & Lange, M. A. (2014). Evaluation of interpolation techniques for the creation of gridded daily precipitation (1 × 1 km 2 ); Cyprus, 1980-2010. Journal of Geophysical Research: Atmospheres, 119(2), 693–712. https://doi.org/10.1002/2013JD020611
Centro Internacional de Agricultura Tropical, Corporación BIOTEC, & Universidad Nacional de Colombia. (2006). RASTA Rapid Soil and Terrainm Assessment: Guía práctica para la caracterización del suelo y del terreno (J. H. Cock, D. M. Alvarez, & M. Estrada (eds.); 2nd ed.). Centro Internacional de Agricultura Tropical (CIAT); Corporación BIOTEC; Universidad Nacional de Colombia.
Chatanga, P., Kotze, D. C., Okello, T. W., & Sieben, E. J. J. (2020). Ecosystem services of high-altitude Afromontane palustrine wetlands in Lesotho. Ecosystem Services, 45, 101185. https://doi.org/10.1016/j.ecoser.2020.101185
Chávez-Jiménez, A., & González-Zeas, D. (2015). El impacto de los caudales medioambientales en la satisfacción de la demanda de agua bajo escenarios de cambio climático. Ribagua, 2(1), 3–13. https://doi.org/10.1016/j.riba.2015.04.001
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 mainland Australia. Remote Sensing of Environment, 140, 330–338. https://doi.org/10.1016/j.rse.2013.08.022
Córdoba Anaya, E. (2021). Evaluación del índice de escasez para aguas superficiales mediante el cálculo de la oferta y demanda hídrica en la microcuenca del río palo en el municipio de Puerto Tejada (Cauca). Corporación Universitaria Autónoma Del Cauca.
Das, S., & Islam, A. R. M. T. (2021). Assessment of mapping of annual average rainfall in a tropical country like Bangladesh: remotely sensed output vs. kriging estimate. Theoretical and Applied Climatology, 146(1–2), 111–123. https://doi.org/10.1007/s00704-021-03729-3
Duan, L., Huang, M., & Zhang, L. (2016). Differences in hydrological responses 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.jhydrol.2016.03.057
Fay, P. A., Guntenspergen, G. R., Olker, J. H., & Johnson, W. C. (2016). Climate change impacts on freshwater wetland hydrology and vegetation cover cycling along a regional aridity gradient. Ecosphere, 7(10). https://doi.org/10.1002/ecs2.1504
Gabriels, K., Willems, P., & Van Orshoven, J. (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
Gao, S., Liu, P., Pan, Z., Ming, B., Guo, S., Cheng, L., & Wang, J. (2019). Incorporating reservoir impacts into flood frequency distribution functions. Journal of Hydrology, 568, 234–246. https://doi.org/10.1016/j.jhydrol.2018.10.061
Govindaraju, R. S., Kavvas, M. L., & Tayfur, G. (1992). A simplified model for two-dimensional overland flows. Advances in Water Resources, 15(2), 133–141. https://doi.org/10.1016/0309-1708(92)90040-9
Gutiérrez-Forero, C. P., Díaz-Mena, C., & Muñoz-Cifuentes, J. N. (2015). Cálculo del índice de escasez de la cuenca del río Opia, departamento del Tolima. Universidad Católica de Colombia.
Hostache, R., Chini, M., Giustarini, L., Neal, J., Kavetski, D., Wood, M., Corato, G., Pelich, R., & Matgen, P. (2018). Near‐Real‐Time Assimilation of SAR‐Derived Flood Maps for Improving Flood Forecasts. Water Resources Research, 54(8), 5516–5535. https://doi.org/10.1029/2017WR022205
Hughes, D. A., & Farinosi, F. (2020). Assessing development and climate variability impacts on water resources in the Zambezi River basin. Simulating future scenarios of climate and development. Journal of Hydrology: Regional Studies, 32, 100763. https://doi.org/10.1016/j.ejrh.2020.100763
Hughes, D., Mantel, S., & Farinosi, F. (2020). Assessing development and climate variability impacts on water resources in the Zambezi River basin: Initial model calibration, uncertainty issues and performance. Journal of Hydrology: Regional Studies, 32, 100765. https://doi.org/10.1016/j.ejrh.2020.100765
Kang, H., & Sridhar, V. (2017). Combined statistical and spatially distributed hydrological model for evaluating future drought indices in Virginia. Journal of Hydrology: Regional Studies, 12, 253–272. https://doi.org/10.1016/j.ejrh.2017.06.003
Kumar, A., Kanga, S., Taloor, A. K., Singh, S. K., & Đurin, B. (2021). Surface runoff estimation of Sind river basin using integrated SCS-CN and GIS techniques. HydroResearch, 4, 61–74. https://doi.org/10.1016/j.hydres.2021.08.001
Kumar, T., & Jhariya, D. C. (2017). Identification of rainwater harvesting sites using SCS-CN methodology, remote sensing and Geographical Information System techniques. Geocarto International, 32(12), 1367–1388. https://doi.org/10.1080/10106049.2016.1213772
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 rainfall-runoff events data in China. Water Research, 177, 115767. https://doi.org/10.1016/j.watres.2020.115767
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 Wangjiaqiao Watershed in the Three Gorges Area, China. Water, 12(1), 60. https://doi.org/10.3390/w12010060
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-humid and semi-arid region in China: Changing patterns, causes and implications. Ecological Indicators, 98, 462–475. https://doi.org/10.1016/j.ecolind.2018.11.037
Magaña-Hernández, F., Bâ, K. M., & Guerra-Cobián, V. H. (2013). Estimación del hidrograma de crecientes con modelación determinística y precipitación derivada de radar. Agrociencia, 47(8), 739–752.
Manz, B., Buytaert, W., Zulkafli, Z., Lavado, W., Willems, B., Robles, L. A., & Rodríguez‐Sánchez, J. (2016). High‐resolution satellite‐gauge merged precipitation climatologies of the Tropical Andes. Journal of Geophysical Research: Atmospheres, 121(3), 1190–1207. https://doi.org/10.1002/2015JD023788
Mehvar, S., Filatova, T., Sarker, M. H., Dastgheib, A., & Ranasinghe, R. (2019). Climate change-driven losses in ecosystem services of coastal wetlands: A case study in the West coast of Bangladesh. Ocean and Coastal Management, 169, 273–283. https://doi.org/10.1016/j.ocecoaman.2018.12.009
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 River basin. Journal of Hydrology: Regional Studies, 6, 66–81. https://doi.org/10.1016/j.ejrh.2016.03.003
Meraj, G., Khan, T., Romshoo, S. A., Farooq, M., Rohitashw, K., & Sheikh, B. A. (2018). An Integrated Geoinformatics and Hydrological Modelling-Based Approach for Effective Flood Management in the Jhelum Basin, NW Himalaya. Proceedings, 7(1), 8. https://doi.org/10.3390/ECWS-3-05804
Ministerio de Ambiente Vivienda y Desarrollo Territorial. (2004). Resolución 865.
Mozo, J., Varni, M., Ares, M. G., & Chagas, C. I. (2020). Rainfall-runoff hydrological modeling of an agricultural watershed of Azul district, Buenos Aires. Ciencia Del Suelo, 38(1), 121–132.
Muñoz, E., Arumí, J. L., Wagener, T., Oyarzún, R., & Parra, V. (2016). Unraveling complex hydrogeological processes in Andean basins in south-central Chile: An integrated assessment to understand hydrological dissimilarity. Hydrological Processes, 30(26), 4934–4943. https://doi.org/10.1002/hyp.11032
Negi, A., Rawat, K. S., Nainwal, A., Shah, M. C., & Kumar, V. (2021). Quality analysis of statistical and data-driven rainfall-runoff models for a mountainous catchment. Materials Today: Proceedings, 46, 10376–10383. https://doi.org/10.1016/j.matpr.2020.12.544
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
Nonki, R. M., Lenouo, A., Tshimanga, R. M., Donfack, F. C., & Tchawoua, C. (2021). Performance assessment and uncertainty prediction of a daily time-step HBV-Light rainfall-runoff model for the Upper Benue River Basin, Northern Cameroon. Journal of Hydrology: Regional Studies, 36, 100849. https://doi.org/10.1016/j.ejrh.2021.100849
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. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (R. Pachauri & L. Meyer (eds.)). IPCC.
Pan, Z., Liu, P., Xu, C.-Y., Cheng, L., Tian, J., Cheng, S., & Xie, K. (2020). The influence of a prolonged meteorological drought on catchment water storage capacity: a hydrological-model perspective. Hydrology and Earth System Sciences, 24(9), 4369–4387. https://doi.org/10.5194/hess-24-4369-2020
Parra, V., Fuentes-Aguilera, P., & Muñoz, E. (2018). Identifying advantages and drawbacks of two hydrological models 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
Peng, X., Shen, H., Zhang, L., Zeng, C., Yang, G., & He, Z. (2016). Spatially continuous mapping of daily global ozone distribution (2004–2014) with the Aura OMI sensor. Journal of Geophysical Research: Atmospheres, 121(21), 12,702-12,722. https://doi.org/10.1002/2016JD025013
Přibáň, K., & Ondok, J. P. (1985). Heat balance components and evapotranspiration from a sedge-grass marsh. Folia Geobotanica et Phytotaxonomica, 20(1), 41–56. https://doi.org/10.1007/BF02856464
Rebelo, A. J., Morris, C., Meire, P., & Esler, K. J. (2019). Ecosystem services provided by South African palmiet wetlands: A case for investment in strategic water source areas. Ecological Indicators, 101, 71–80. https://doi.org/10.1016/j.ecolind.2018.12.043
Revueltas, J. E., Zabaleta, A., Mercado, T., & Aguirre, S. (2020). Cambios en el clima local y su efecto en la regulación hídrica en microcuencas del departamento del Magdalena, Norte de Colombia. Información Tecnológica, 31(6), 193–206. https://doi.org/10.4067/S0718-07642020000600193
Rousis, N. I., Bade, R., Bijlsma, L., Zuccato, E., Sancho, J. V., Hernandez, F., & Castiglioni, S. (2017). Monitoring a large number of pesticides and transformation products in water samples from Spain and Italy. Environmental Research, 156, 31–38. https://doi.org/10.1016/j.envres.2017.03.013
Salazar Carmona, 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. Universidad Militar Nueva Granada.
Shi, W., & Wang, N. (2020). An Improved SCS-CN Method Incorporating Slope, Soil Moisture, and Storm Duration Factors for Runoff Prediction. Water, 12(5), 1335. https://doi.org/10.3390/w12051335
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 analysis in the Three Gorges Area, China. CATENA, 77(1), 1–7. https://doi.org/10.1016/j.catena.2008.11.006
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 Management, 29(11), 4111–4127. https://doi.org/10.1007/s11269-015-1048-1
Skaugen, T., Peerebom, I. O., & Nilsson, A. (2015). Use of a parsimonious rainfall-run-off model for predicting hydrological response in ungauged basins. Hydrological Processes, 29(8), 1999–2013. https://doi.org/10.1002/hyp.10315
Soulis, K. X. (2021). Soil Conservation Service Curve Number (SCS-CN) Method: Current Applications, Remaining Challenges, and Future Perspectives. Water, 13(2), 192. https://doi.org/10.3390/w13020192
Soulis, K. X., & Valiantzas, J. D. (2012). SCS-CN parameter determination using rainfall-runoff data in heterogeneous watersheds – the two-CN system approach. Hydrology and Earth System Sciences, 16(3), 1001–1015. https://doi.org/10.5194/hess-16-1001-2012
Tajiki, M., Schoups, G., Hendricks Franssen, H. J., Najafinejad, A., & Bahremand, A. (2020). Recursive Bayesian Estimation of Conceptual Rainfall‐Runoff Model Errors in Real‐Time Prediction of Streamflow. Water Resources Research, 56(2). https://doi.org/10.1029/2019WR025237
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. Journal of Hydrology: Regional Studies, 14, 49–66. https://doi.org/10.1016/j.ejrh.2017.10.002
The ASCE/EWRI Curve Number Hydrology Task Committee. (2009). Curve number hydrology : state of the practice. Environmental and Water Resources Institute (EWRI) of the American Society of Civil Engineers.
Tigkas, D., Vangelis, H., & Tsakiris, G. (2016). Introducing a Modified Reconnaissance Drought Index (RDIe) Incorporating Effective Precipitation. Procedia Engineering, 162, 332–339. https://doi.org/10.1016/j.proeng.2016.11.072
Trigg, M. A., & Tshimanga, R. M. (2020). Capacity Building in the Congo Basin: Rich Resources Requiring Sustainable Development. One Earth, 2(3), 207–210. https://doi.org/10.1016/j.oneear.2020.02.008
Tshimanga, R. M., Hughes, D. A., & Kapangaziwiri, E. (2011). Initial calibration of a semi-distributed rainfall runoff model for the Congo River basin. Physics and Chemistry of the Earth, Parts A/B/C, 36(14–15), 761–774. https://doi.org/10.1016/j.pce.2011.07.045
Verma, S., Singh, P. K., Mishra, S. K., Singh, V. P., Singh, V., & Singh, A. (2020). Activation soil moisture accounting (ASMA) for runoff estimation using soil conservation service curve number (SCS-CN) method. Journal of Hydrology, 589, 125114. https://doi.org/10.1016/j.jhydrol.2020.125114
Wagner, P. D., Fiener, P., Wilken, F., Kumar, S., & Schneider, K. (2012). Comparison and evaluation of spatial interpolation schemes for daily rainfall in data scarce regions. Journal of Hydrology, 464–465, 388–400. https://doi.org/10.1016/j.jhydrol.2012.07.026
Wang, X. L., & Lin, A. (2015). An algorithm for integrating satellite precipitation estimates with in situ precipitation data on a pentad time scale. Journal of Geophysical Research: Atmospheres, 120(9), 3728–3744. https://doi.org/10.1002/2014JD022788
Watson, A., Miller, J., Fleischer, M., & de Clercq, W. (2018). Estimation of groundwater recharge via percolation 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.jhydrol.2018.01.028
Webster, R., & Oliver, M. A. (2007). Geostatistics for environmental scientists (John Wiley & Sons (ed.); 2nd ed.).
Xie, K., Liu, P., Zhang, J., Han, D., Wang, G., & Shen, C. (2021). Physics-guided deep learning for rainfall-runoff modeling by considering extreme events and monotonic relationships. Journal of Hydrology, 603, 127043. https://doi.org/10.1016/j.jhydrol.2021.127043
Xie, K., Liu, P., Zhang, J., Libera, D. A., Wang, G., Li, Z., & Wang, D. (2020). Verification of a New Spatial Distribution Function of Soil Water Storage Capacity Using Conceptual and SWAT Models. Journal of Hydrologic Engineering, 25(3), 04020001. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001887
Xie, K., Liu, P., Zhang, J., Wang, G., Zhang, X., & Zhou, L. (2021). Identification of spatially distributed parameters of hydrological models using the dimension-adaptive key grid calibration strategy. Journal of Hydrology, 598, 125772. https://doi.org/10.1016/j.jhydrol.2020.125772
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 entropy-based approach to raingauge network design. Environmental Research, 161, 61–75. https://doi.org/10.1016/j.envres.2017.10.038
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 partial least squares regression. Journal of Hydrology, 484, 26–37. https://doi.org/10.1016/j.jhydrol.2013.01.008
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.catena.2019.04.007
Zhang, X., Liu, P., Zhao, Y., Deng, C., Li, Z., & Xiong, M. (2018). Error correction-based forecasting of reservoir water levels: Improving accuracy over multiple lead times. Environmental Modelling & Software, 104, 27–39. https://doi.org/10.1016/j.envsoft.2018.02.017
Zhou, X., Wang, F., Huang, K., Zhang, H., Yu, J., & Han, A. Y. (2021). System Dynamics-Multiple Objective Optimization Model for Water Resource Management: A Case Study in Jiaxing City, China. Water, 13(5), 671. https://doi.org/10.3390/w13050671
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 impacts of climate change on the water table level of selected forested wetlands in the southeastern United States. Hydrology and Earth System Sciences, 21(12), 6289–6305. https://doi.org/10.5194/hess-21-6289-2017
Copyright (c) 2022 Revista de Investigación Agraria y Ambiental
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
When RIAA receives the postulation of an original by its author, either through email or post mail, considers that it can be published in physical and/or electronic format and facilitates its inclusion in databases, newspaper archives and other systems and indexing process. RIAA authorizes the reproduction and citation of the Journal’s material, provided that explicitly indicates journal name, the authors, the article title, volume, number and pages. The ideas and concepts expressed in the articles are responsibility of the authors and in no case reflect the institutional policies of the UNAD.
