Impact of land cover changes on water quality: an application to the Guájaro reservoir, Colombia
In this study, remote sensing and geographic information systems were used to assess the influence of land cover characteristics on the water quality of the El Guájaro reservoir, in northern Colombia. The water quality data were acquired during three measurement and sampling campaigns (2013, 2015 an...
- Autores:
-
Torres-Bejarano, Franklin
Torregroza Espinosa, Ana Carolina
Martínez-Mera, Eliana
González Márquez, Luis Carlos
- Tipo de recurso:
- Article of investigation
- Fecha de publicación:
- 2022
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/9978
- Acceso en línea:
- https://hdl.handle.net/11323/9978
https://repositorio.cuc.edu.co/
- Palabra clave:
- Vegetation cover
NDVI
NDMI
Remote sensing
Water contamination
- Rights
- embargoedAccess
- License
- Atribución 4.0 Internacional (CC BY 4.0)
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| dc.title.eng.fl_str_mv |
Impact of land cover changes on water quality: an application to the Guájaro reservoir, Colombia |
| title |
Impact of land cover changes on water quality: an application to the Guájaro reservoir, Colombia |
| spellingShingle |
Impact of land cover changes on water quality: an application to the Guájaro reservoir, Colombia Vegetation cover NDVI NDMI Remote sensing Water contamination |
| title_short |
Impact of land cover changes on water quality: an application to the Guájaro reservoir, Colombia |
| title_full |
Impact of land cover changes on water quality: an application to the Guájaro reservoir, Colombia |
| title_fullStr |
Impact of land cover changes on water quality: an application to the Guájaro reservoir, Colombia |
| title_full_unstemmed |
Impact of land cover changes on water quality: an application to the Guájaro reservoir, Colombia |
| title_sort |
Impact of land cover changes on water quality: an application to the Guájaro reservoir, Colombia |
| dc.creator.fl_str_mv |
Torres-Bejarano, Franklin Torregroza Espinosa, Ana Carolina Martínez-Mera, Eliana González Márquez, Luis Carlos |
| dc.contributor.author.none.fl_str_mv |
Torres-Bejarano, Franklin Torregroza Espinosa, Ana Carolina Martínez-Mera, Eliana González Márquez, Luis Carlos |
| dc.subject.proposal.eng.fl_str_mv |
Vegetation cover NDVI NDMI Remote sensing Water contamination |
| topic |
Vegetation cover NDVI NDMI Remote sensing Water contamination |
| description |
In this study, remote sensing and geographic information systems were used to assess the influence of land cover characteristics on the water quality of the El Guájaro reservoir, in northern Colombia. The water quality data were acquired during three measurement and sampling campaigns (2013, 2015 and 2016), complemented with data obtained by the regional environmental authority. The status of land cover in the basin of the El Guájaro reservoir was assessed by calculating the Normalized Difference Vegetation Index (NDVI), Normalized Difference Moisture Index (NDMI) indicators and land cover classification, using Landsat-8 surface reflectance images obtained from the Google Earth Engine platform. The analysis of the interaction between vegetation cover and water quality was based on Pearson correlations and Principal Component Analysis (PCA). The correlation analysis indicated significant correlations of NDVI with temperature (r = 0.47), DO (r = − 0.64), pH (r = − 0.37), general vegetation (r = 0.83), urban areas (r = 0.56), bare soil (r = − 0.86), and nutrients (r = − 0.92 and r = − 0.82, for NO3 and PO4 respectively); and NDMI with temperature (r = 0.46), DO (r = − 0.64), TSS (r = − 0.33), general vegetation (r = 0.87), urban areas (r = 0.61), bare soil (r = − 0.89), water areas (r = − 0.40), and nutrients (r = − 0.93 and r = − 0.83, for NO3 and PO4 respectively). Additionally, it was observed that land covers corresponding to urban areas and bare soil affects the water quality of the reservoir. The results displayed strong correlation and association between vegetation cover conditions, which are affected by the various agricultural activities that take place in the basin, and the water quality of the reservoir. |
| publishDate |
2022 |
| dc.date.issued.none.fl_str_mv |
2022-09-21 |
| dc.date.accessioned.none.fl_str_mv |
2023-04-11T15:52:32Z |
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2023-09-21 2023-04-11T15:52:32Z |
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Artículo de revista |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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Torres-Bejarano, F., Torregroza-Espinosa, A.C., Martínez-Mera, E. et al. Impact of land cover changes on water quality: an application to the Guájaro reservoir, Colombia. Int. J. Environ. Sci. Technol. 20, 3577–3590 (2023). https://doi.org/10.1007/s13762-022-04535-8 |
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https://hdl.handle.net/11323/9978 |
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10.1007/s13762-022-04535-8 |
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1735-2630 |
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Corporación Universidad de la Costa |
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REDICUC - Repositorio CUC |
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https://repositorio.cuc.edu.co/ |
| identifier_str_mv |
Torres-Bejarano, F., Torregroza-Espinosa, A.C., Martínez-Mera, E. et al. Impact of land cover changes on water quality: an application to the Guájaro reservoir, Colombia. Int. J. Environ. Sci. Technol. 20, 3577–3590 (2023). https://doi.org/10.1007/s13762-022-04535-8 10.1007/s13762-022-04535-8 1735-2630 Corporación Universidad de la Costa REDICUC - Repositorio CUC |
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https://hdl.handle.net/11323/9978 https://repositorio.cuc.edu.co/ |
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eng |
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eng |
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International Journal of Environmental Science and Technology |
| dc.relation.references.spa.fl_str_mv |
Alcaldía de Repelón-Atlántico (2016) Información General. http://www.repelon-atlantico.gov.co/informacion_general.shtml#geografa Alcaldía de Repelón-Atlántico (2017) Información General. http://www.repelonatlantico.gov.co/index.shtml?apc¼gbxx2760911&sh_itm=98bd43dd20b101b40297b595248a69a4&add_disc=1 Alexander RB, Smith RA, Schwarz GE, Boyer EW, Nolan JV, Brakebill JW (2008) Diferences in phosphorus and nitrogen delivery to the Gulf of Mexico from the Mississippi River Basin. Environ Sci Technol 42(3):822–830. https://doi.org/10.1021/es0716103 Aljahdali MO, Munawar S, Khan WR (2021) Monitoring mangrove forest degradation and regeneration: landsat time series analysis of moisture and vegetation indices at rabigh lagoon. Red Sea Forests 12(52):1–19. https://doi.org/10.3390/f12010052 Anthony A, Atwood J, August P, Byron C, Cobb S, Foster C, FryC, Gold A, Hagos K, Heffner L, Kellogg DQ, Lellis-Dibble K, Opaluch JJ, Oviatt C, Pfeifer-Herbert A, Rohr N, Smith L, Smythe T, Swift J, Vinhateiro N (2009) Coastal lagoons and climate change: ecological and social ramifcations in US Atlantic and Gulf coast ecosystems. Ecol Soc 14(1):8 Bai J, Ouyang H, Xiao R, Gao GJ, H, Cui B, Huang L, (2010) Spatial variability of soil carbon, nitrogen, and phosphorus content and storage in an alpine wetland in the Qinghai-Tibet Plateau, China. Aust J Soil Res 48(8):730–736. https://doi.org/10.1071/SR09171 Becker W, Ló T, Johann J, Mercante E (2021) Statistical features for land use and land cover classifcation in Google Earth Engine. Remote Sens Appl Soc Environ. https://doi.org/10.1016/j.rsase. 2020.100459 Bu H, Meng W, Zhang Y, Wan J (2014) Relationships between land use patterns and water quality in the Taizi River basin, China. Ecol Ind 41:187–197. https://doi.org/10.1016/j.ecolind.2014.02.003 Camara M, Jamil NR, Abdullah AFB (2019) Impact of land uses on water quality in Malaysia: a review. Ecol Process 8:10. https://doi. org/10.1186/s13717-019-0164-x Chu HJ, Liu CY, Wang CK (2013) Identifying the relationships between water quality and land cover changes in the Tseng–Wen reservoir watershed of Taiwan. Int J Environ Res Public Health 10:478–489. https://doi.org/10.3390/ijerph10020478 CRA-Corporación Autónoma Regional del Atlántico (2007) Documentación del estado de las cuencas hidrográfcas en el Departamento del Atlántico. https://www.crautonoma.gov.co/atencion-al-publi co/transparencia-y-acceso-a-informacion-publica/planeacion/ plan-de-ordenamiento-y-manejo-de-las-cuencas-hidrografcas CRA-Corporación Autónoma Regional del Atlántico (2012) Actualización del Manual de Operaciones del Hidrosistema al cual pertenece el Embalse el Guájaro y llevar a cabo el diseño de las estructuras y sistemas para disminuir la vulnerabilidad de la zona ante eventos climatológicos extremos. Protocolo de operación de las compuertas del embalse el Guájaro. Convenio 003 de 2012, Colombia CRA-Corporación Autónoma Regional del Atlántico (2014) Diagnóstico inicial para el ordenamiento del embalse El Guájaro y la Ciénaga de Luruaco, Barranquilla, Atlántico. http://www.craut onoma.gov.co/documentos/recurrico/6_Diagn%C3%B3stico% 20Ordenamiento%20.pdf Foga S, Scaramuzza PL, Guo S, Zhu Z, Dilley RD, Beckmann T, Schmidt GL, Dwyer JL, Joseph Hughes M, Laue B (2017) Cloud detection algorithm comparison and validation for operational Landsat data products. Remote Sens Environ 194:379–390 Glibert PM, Manager R, Sobota DJ, Bouwman L (2014) The HaberBosch-Harmful algal bloom (HB-HAB) link. Environ Res Lett 9(10):1–13. https://doi.org/10.1088/17489326/9/10/105001. 105001 González-Márquez LC, Torres-Bejarano F, Rodríguez-Cuevas C, Torregroza-Espinosa AC, Sandoval-Romero JA (2018) Estimation of water quality parameters using Landsat 8 images: application to Playa Colorada Bay, Sinaloa, Mexico. Appl Geomat 10(2):147– 158. https://doi.org/10.1007/s12518-018-0211-9 González-Márquez LC, Torres-Bejarano FM, Torregroza-Espinosa AC, Hansen-Rodríguez IR (2018) Rodríguez-Gallegos HB (2018) Use of LANDSAT 8 images for depth and water quality assessment of El Guájaro reservoir, Colombia. J S Am Earth Sci 82:231–238. https://doi.org/10.1016/j.jsames.2018.01.004 Gorelick N, Hancher M, Dixon M, Ilyushchenko S, Thau D, Moore R (2017) Google Earth Engine: planetary-scale geospatial analysis for everyone. Remote Sens Environ 202:18–27. https://doi.org/10. 1016/j.rse.2017.06.031 Gorgoglione A, Gregorio J, Ríos A, Alonso J, Chreties C, Fossati M (2020) Infuence of Land Use/Land Cover on Surface-Water Quality of Santa Lucía River, Uruguay. Sustain MDPI 12(11):4692. https://doi.org/10.3390/su12114692 Haidaryy A, Amiri BJ, Adamowski J, Fohrer N, Nakane K (2013) Assessing the impacts of four land use types on water quality of Wetlands in Japan. Water Resour Manag 27(7):2217–2229. https://doi.org/10.1007/s11269-013-0284-5 Hamid A, Bhat SU, Jehangir A (2020) Local determinants infuencing stream water quality. Appl Water Sci 10(24):1–16. https://doi.org/ 10.1007/s13201-019-1043-4 Hefer P, Prud’homme M (2016) Fertilizer outlook 2016–2010. In: 84th International Fertilizer Industry Association Annual Conference. Moscow (Russia), 30 May–1 June 2016. https://www. fertilizer.org/images/Library_Downloads/2016_IFa_Moscow_ Sum mary.pdf Hull V, Mocenni C, Falcucci M, Marchettini N (2000) A trophodynamic model for the lagoon of Fogliano (Italy) with ecological dependent modifying parameters. Ecol Model 134:153–167 Hur J, Lee BM, Lee TH, Park DH (2010) Estimation of biological oxygen demand and chemical oxygen demand for combined sewer systems using synchronous fuorescence spectra. Sensors 10(4):2460–2471 IGAC-Instituto Geográfco Agustín Codazzi (2008) Estudio general de suelos y zonifcación de tierras. Departamento del Atlántico. Imprenta Nacional de Colombia, Bogotá, 324 Issaka S, Ashraf M (2017) Impact of soil erosion and degradation on water quality: a review. Geol Ecol Landsc 1(1):1–11. https:// doi.org/10.1080/24749508.2017.1301053 Jiménez PAL, Alemany VE, Alberola MC, Solano FJM (2003) Metodología para la calibración de modelos de calidad de aguas. Ingeniería Del Agua 10(4):501–516 Jin Z, Azzari G, You C, Di Tommaso S, Aston S, Burke M, Lobell D (2019) Smallholder maize area and yield mapping at national scales with Google Earth Engine. Remote Sens Environ. https:// doi.org/10.1016/j.rse.2019.04.016 Larrahondo-Molina M (1992) Aprovechamiento acuícola de embalsesen Colombia. In: Juárez JR, Varsi E (eds) Avances en el manejo yaprovechamiento acuícola de embalses en América Latina y el Caribe. Proyecto Aquila II. FAO, Organización de las Naciones Unidaspara la Agricultura y la Alimentación, Roma, p 172. https://www.fao.org/3/ab488s/AB488S04.htm Lassaletta L, Billen G, Grizzetti B, Garnier J, Leach AM, Galloway JN (2014) Food and feed trade as a driver in the global nitrogen cycle: 50-year trends. Biogeochemistry 118(1–3):225–241. https://doi.org/10.1007/s10533-013-9923-4 Lastovicka J, Svec P, Paluba D, Kobliuk N, Svoboda J, Hladky R, Stych P (2020) Sentinel-2 Data in an Evaluation of the Impact of the Disturbances on Forest Vegetation. Remote Sens 12:1914. https://doi.org/10.3390/rs12121914 Li K, Zhang L, Li Y, Zhang L, Wang X (2015) A three-dimensional water quality model to evaluate the environmental capacity of nitrogen and phosphorus in Jiaozhou Bay, China. Mar Pollut Bull 91(1):306–316. https://doi.org/10.1016/j.marpolbul.2014. 11.020 Lopes FB, Andrade EM, Meireles ACM, Becker H, Batista AA (2014) Assessment of the water quality in a large reservoir in semiarid region of Brazil. Revista Brasileira De Engenharia Agrícola Ambiental 18:437–445 Malik S, Pal SC, Das B, Chakrabortty R (2019) Assessment of vegetation status of Sali River basin, a tributary of Damodar River in Bankura District, West Bengal, using satellite data. Environ Dev Sustain 22:5651–5685. https://doi.org/10.1007/ s10668-019-00444-y Martínez-Mera E, Torregroza-Espinosa A, Castañeda-Valbuena D, Crissien-Borrero T, Torres-Bejarano F (2018) El Distrito de Riego de Repelón. Editorial Universitaria de la Costa, Educosta, Diagnóstico y Evaluación Ambiental de la Actividad Agrícola. Primera Edición, p 208 Martínez-Mera E, Torregroza-Espinosa AC, Crissien-Borrero TC, Marrugo Negrete JL, González-Márquez LC (2019) Evaluation of contaminants in agricultural soils in an Irrigation District in Colombia. Heliyon 5:e02217. https://doi.org/10.1016/j.heliyon. 2019.e02217 Meneses BM, Reis R, Vale MJ, Saraiva R (2015) Land use and land cover changes in Zêzere watershed (Portugal)-Water quality implications. Sci Total Environ 527–528:439–447. https://doi. org/10.1016/j.scitotenv.2015.04.092 Masocha M, Murwira A, Magadza CHD, Hirji R, Dube T (2017) Remote sensing of surface water quality in relation to catchment condition in Zimbabwe. Phys Chem Earth Parts A/B/C 100:13–18. https://doi.org/10.1016/j.pce.2017.02.013 Ministerio de Ambiente y Desarrollo Sostenible (MinAmbiente) (1984) Decreto 1594. Usos del agua y residuos líquidos Ngoye E, Machiwa JF (2004) The infuence of land-use patterns in the Ruvu river watershed on water quality in the river system. Phys Chem Earth Parts a/b/c 29(15–18):1161–1166. https://doi. org/10.1016/j.pce.2004.09.002 Parson TR, Maitia Y, Lalli CM (1984) A manual of chemical and biological methods for sea water analysis. Pergamonn Press, Oxford, p 135 Quamrul A, Benson B, Visser J, Gang D (2016) Response of estuarine phytoplankton to nutrient and spatio temporal pattern of physicochemical water quality parameters in little Vermilion Bay. Louisiana Ecol Inf 32:79–90 Rodrigues V, Estrany J, Ranzini M, de Cicco V, Martín-Benito JM, Hedo J, Lucas-Borja ME (2018) Efects of land use and seasonality on stream water qualityin a small tropical catchment: the headwater of Córrego Água Limpa, SãoPaulo (Brazil). Sci Total Environ 622–623:1553–1561.https://doi.org/10.1016/J.SCITO TENV.2017.10.028 Romero-Sierra P, Rivas D, Almazán-Becerril A, Hernández-Terrones L (2018) Hydrochemistry and hydrodynamics of a Mexican Caribbean Lagoon: Nichupté Lagoon System. Estuar Coast Shelf Sci 215:185–198 Ruíz-Cabarcas AC, Pabón-Caicedo JD (2013) Efecto de los fenómenos del niño y la niña en la precipitación y su impacto en la producción agrícola del departamento del Atlántico. Colombia Cuadernos De Geografía 22(2):35–54 Sahana M, Dutta S, Sajjad H (2018) Assessing land transformation and its relation with land surface temperature in Mumbai city, India using geospatial techniques. Int J Urban Sci 23(2):205–225. https://doi.org/10.1080/12265934.2018.1488604 Shi P, Zhang Y, Li Z, Li P, Xu G (2017) Infuence of land use and land cover patterns on seasonal water quality at multi-spatial scales. CATENA 151:182–190. https://doi.org/10.1016/j.catena.2016. 12.017 Sidi Almouctar MA, Wu Y, Kumar A et al (2021) Spatiotemporal analysis of vegetation cover changes around surface water based on NDVI: a case study in Korama basin, Southern Zinder. Niger Appl Water Sci 11:4. https://doi.org/10.1007/s13201-020-01332-x Sliva L, Williams DD (2001) Bufer zone versus whole catchment approaches to studying land use impact on river water quality. Water Res 35(14):3462–3472. https://doi.org/10.1016/s0043- 1354(01)00062-8 Spalevic V, Barovic G, Vujacic D, Curovic M, Behzadfar M, Djurovic N, Dudic B, Billi P (2020) The impact of land use changes on soil erosion in the river Basin of Miocki Potok. Montenegro Water 12(2973):1–28. https://doi.org/10.3390/w12112973 Srilert C, Satika B (2018) Impacts of land-use changes on watershed discharge and water quality in a large intensive agricultural area in Thailand. Hydrol Sci J 63(9):1386–1407. https://doi.org/10.1080/ 02626667.2018.1506128 Susilowati S, Sutrisno J, Masykuri M, Maridi M (2018) Dynamics and factors that afects DO-BOD concentrations of Madiun River. AIP Conf Proc 2049:020052. https://doi.org/10.1063/1.5082457 Torregroza-Espinosa AC, Martínez-Mera E, Castañeda-Valbuena D, González-Márquez LC, Torres-Bejarano F (2018) Contamination level and spatial distribution of heavy metals in water and sediments of El Guájaro reservoir, Colombia. Bull Environ Contam Toxicol 101:61–67. https://doi.org/10.1007/s00128-018-2365-x Torres-Bejarano F, Padilla Coba J, Rodríguez-Cuevas C, Ramírez-León H, Cantero-Rodelo R (2016) La modelación hidrodinámica para la gestión hídrica del embalse del Guájaro, Colombia. Revista Internacional De Métodos Numéricos Para Cálculo y Diseño En Ingeniería 32(3):163–172. https://doi.org/10.1016/j.rimni.2015. 04.001 Trenberth K (2020) National Center for Atmospheric Research Staf. The Climate Data Guide: Nino SST Indices (Nino 1+2, 3, 3.4, 4; ONI and TNI). Last modifed 21 Jan. https://climatedataguide. ucar.edu/climate-data/nino-sst-indices-nino-12-3-34-4-oni-and-tni Umwali ED, Kurban A, Isabwe A, Mind’je R, Azadi H, Guo Z, Udahogora M, Nyirarwasa A, Umuhoza J, Nzabarinda V, Gasirabo A, Sabirhazi G, (2021) Spatio-seasonal variation of water quality infuenced by land use and land cover in Lake Muhazi. Sci Rep 11:17376. https://doi.org/10.1038/s41598-021-96633-9 Uninorte-Universidad del Norte (2009) Embalse El Guájaro. Diagnóstico hidráulico y ambiental de las condiciones actuales. Gobernación del Atlántico. Secretaría de Agua Potable y Saneamiento Básico, Barranquilla. p 122 United Nations, Department of Economic and Social Afairs, Population Division (2014) World Urbanization Prospects: The 2014 Revision, Highlights (ST/ESA/SER.A/352). Available at: https:// population.un.org/wup/publications/fles/wup2014-highlights.pdf USGS (2021) Landsat Missions. Disponible en: https://www.usgs.gov/ core-science-systems/nli/landsat/landsat-8?qt-science_support_ page_related_con=0#qt-science_support_page_related_con Vermote E, Justice C, Claverie M, Franch B (2016) Preliminary analysis of the performance of the Landsat 8/OLI land surface refectance product. Remote Sensing of Environment 185, 46–56. doi. org/https://doi.org/10.1016/j.rse.2016.04.008 Wang R, Xu T, Yu L, Zhu J, Li X (2013) Efects of land use types on surface water quality across an anthropogenic disturbance gradient in the upper reach of the Hun River, Northeast China. Environmental Monitoring and Assessment, 185: 4141–4151. http://dx. doi. org/https://doi.org/10.1007/s10661-012-2856-x Weather Spark (2021) El clima de Repelón, Atlántico. Available at: https://es.weatherspark.com/m/22615/5/Tiempo-promedio-enmayo-en-Repel%C3%B3n-Colombia#Sections-Rain. Whistler JL (1996) A phenological approach to land cover characterization using Landsat mss data for analysis of nonpoint source pollution. Project Report. U.S. Environmental Protection Agency. pp 59. Available at: http://kufs.ku.edu/media/uploads/work/kars_ report_ 96–1.pdf Wilson EH, Sader SA (2002) Detection of forest harvest type using multiple dates of Landsat TM imagery. Remote Sens Environ 80(3):385–396. https://doi.org/10.1016/s0034-4257(01)00318-2 |
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Atribución 4.0 Internacional (CC BY 4.0)© 2023 Springer Nature Switzerland AG. Part of Springer Nature.https://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/embargoedAccesshttp://purl.org/coar/access_right/c_f1cfTorres-Bejarano, Franklin660fd46e9dd4f272aa85142eb8f15f9b600Torregroza Espinosa, Ana Carolina14d5fa0aefc89b13f1d5fbafd806f092600Martínez-Mera, Eliana047cb156e3eb15486923f8e4069ec3e2600González Márquez, Luis Carlosec8a677723b0ad835042ee21b93ae943600The Guájaro reservoirColombia2023-04-11T15:52:32Z2023-09-212023-04-11T15:52:32Z2022-09-21Torres-Bejarano, F., Torregroza-Espinosa, A.C., Martínez-Mera, E. et al. Impact of land cover changes on water quality: an application to the Guájaro reservoir, Colombia. Int. J. Environ. Sci. Technol. 20, 3577–3590 (2023). https://doi.org/10.1007/s13762-022-04535-8https://hdl.handle.net/11323/997810.1007/s13762-022-04535-81735-2630Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/In this study, remote sensing and geographic information systems were used to assess the influence of land cover characteristics on the water quality of the El Guájaro reservoir, in northern Colombia. The water quality data were acquired during three measurement and sampling campaigns (2013, 2015 and 2016), complemented with data obtained by the regional environmental authority. The status of land cover in the basin of the El Guájaro reservoir was assessed by calculating the Normalized Difference Vegetation Index (NDVI), Normalized Difference Moisture Index (NDMI) indicators and land cover classification, using Landsat-8 surface reflectance images obtained from the Google Earth Engine platform. The analysis of the interaction between vegetation cover and water quality was based on Pearson correlations and Principal Component Analysis (PCA). The correlation analysis indicated significant correlations of NDVI with temperature (r = 0.47), DO (r = − 0.64), pH (r = − 0.37), general vegetation (r = 0.83), urban areas (r = 0.56), bare soil (r = − 0.86), and nutrients (r = − 0.92 and r = − 0.82, for NO3 and PO4 respectively); and NDMI with temperature (r = 0.46), DO (r = − 0.64), TSS (r = − 0.33), general vegetation (r = 0.87), urban areas (r = 0.61), bare soil (r = − 0.89), water areas (r = − 0.40), and nutrients (r = − 0.93 and r = − 0.83, for NO3 and PO4 respectively). Additionally, it was observed that land covers corresponding to urban areas and bare soil affects the water quality of the reservoir. The results displayed strong correlation and association between vegetation cover conditions, which are affected by the various agricultural activities that take place in the basin, and the water quality of the reservoir.14 páginasapplication/pdfengSpringerIranhttps://link.springer.com/article/10.1007/s13762-022-04535-8Impact of land cover changes on water quality: an application to the Guájaro reservoir, ColombiaArtículo de revistahttp://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a85International Journal of Environmental Science and TechnologyAlcaldía de Repelón-Atlántico (2016) Información General. http://www.repelon-atlantico.gov.co/informacion_general.shtml#geografaAlcaldía de Repelón-Atlántico (2017) Información General. http://www.repelonatlantico.gov.co/index.shtml?apc¼gbxx2760911&sh_itm=98bd43dd20b101b40297b595248a69a4&add_disc=1Alexander RB, Smith RA, Schwarz GE, Boyer EW, Nolan JV, Brakebill JW (2008) Diferences in phosphorus and nitrogen delivery to the Gulf of Mexico from the Mississippi River Basin. Environ Sci Technol 42(3):822–830. https://doi.org/10.1021/es0716103Aljahdali MO, Munawar S, Khan WR (2021) Monitoring mangrove forest degradation and regeneration: landsat time series analysis of moisture and vegetation indices at rabigh lagoon. Red Sea Forests 12(52):1–19. https://doi.org/10.3390/f12010052Anthony A, Atwood J, August P, Byron C, Cobb S, Foster C, FryC, Gold A, Hagos K, Heffner L, Kellogg DQ, Lellis-Dibble K, Opaluch JJ, Oviatt C, Pfeifer-Herbert A, Rohr N, Smith L, Smythe T, Swift J, Vinhateiro N (2009) Coastal lagoons and climate change: ecological and social ramifcations in US Atlantic and Gulf coast ecosystems. Ecol Soc 14(1):8Bai J, Ouyang H, Xiao R, Gao GJ, H, Cui B, Huang L, (2010) Spatial variability of soil carbon, nitrogen, and phosphorus content and storage in an alpine wetland in the Qinghai-Tibet Plateau, China. Aust J Soil Res 48(8):730–736. https://doi.org/10.1071/SR09171Becker W, Ló T, Johann J, Mercante E (2021) Statistical features for land use and land cover classifcation in Google Earth Engine. Remote Sens Appl Soc Environ. https://doi.org/10.1016/j.rsase. 2020.100459Bu H, Meng W, Zhang Y, Wan J (2014) Relationships between land use patterns and water quality in the Taizi River basin, China. Ecol Ind 41:187–197. https://doi.org/10.1016/j.ecolind.2014.02.003Camara M, Jamil NR, Abdullah AFB (2019) Impact of land uses on water quality in Malaysia: a review. Ecol Process 8:10. https://doi. org/10.1186/s13717-019-0164-xChu HJ, Liu CY, Wang CK (2013) Identifying the relationships between water quality and land cover changes in the Tseng–Wen reservoir watershed of Taiwan. Int J Environ Res Public Health 10:478–489. https://doi.org/10.3390/ijerph10020478CRA-Corporación Autónoma Regional del Atlántico (2007) Documentación del estado de las cuencas hidrográfcas en el Departamento del Atlántico. https://www.crautonoma.gov.co/atencion-al-publi co/transparencia-y-acceso-a-informacion-publica/planeacion/ plan-de-ordenamiento-y-manejo-de-las-cuencas-hidrografcasCRA-Corporación Autónoma Regional del Atlántico (2012) Actualización del Manual de Operaciones del Hidrosistema al cual pertenece el Embalse el Guájaro y llevar a cabo el diseño de las estructuras y sistemas para disminuir la vulnerabilidad de la zona ante eventos climatológicos extremos. Protocolo de operación de las compuertas del embalse el Guájaro. Convenio 003 de 2012, ColombiaCRA-Corporación Autónoma Regional del Atlántico (2014) Diagnóstico inicial para el ordenamiento del embalse El Guájaro y la Ciénaga de Luruaco, Barranquilla, Atlántico. http://www.craut onoma.gov.co/documentos/recurrico/6_Diagn%C3%B3stico% 20Ordenamiento%20.pdfFoga S, Scaramuzza PL, Guo S, Zhu Z, Dilley RD, Beckmann T, Schmidt GL, Dwyer JL, Joseph Hughes M, Laue B (2017) Cloud detection algorithm comparison and validation for operational Landsat data products. Remote Sens Environ 194:379–390Glibert PM, Manager R, Sobota DJ, Bouwman L (2014) The HaberBosch-Harmful algal bloom (HB-HAB) link. Environ Res Lett 9(10):1–13. https://doi.org/10.1088/17489326/9/10/105001. 105001González-Márquez LC, Torres-Bejarano F, Rodríguez-Cuevas C, Torregroza-Espinosa AC, Sandoval-Romero JA (2018) Estimation of water quality parameters using Landsat 8 images: application to Playa Colorada Bay, Sinaloa, Mexico. Appl Geomat 10(2):147– 158. https://doi.org/10.1007/s12518-018-0211-9González-Márquez LC, Torres-Bejarano FM, Torregroza-Espinosa AC, Hansen-Rodríguez IR (2018) Rodríguez-Gallegos HB (2018) Use of LANDSAT 8 images for depth and water quality assessment of El Guájaro reservoir, Colombia. J S Am Earth Sci 82:231–238. https://doi.org/10.1016/j.jsames.2018.01.004Gorelick N, Hancher M, Dixon M, Ilyushchenko S, Thau D, Moore R (2017) Google Earth Engine: planetary-scale geospatial analysis for everyone. Remote Sens Environ 202:18–27. https://doi.org/10. 1016/j.rse.2017.06.031Gorgoglione A, Gregorio J, Ríos A, Alonso J, Chreties C, Fossati M (2020) Infuence of Land Use/Land Cover on Surface-Water Quality of Santa Lucía River, Uruguay. Sustain MDPI 12(11):4692. https://doi.org/10.3390/su12114692Haidaryy A, Amiri BJ, Adamowski J, Fohrer N, Nakane K (2013) Assessing the impacts of four land use types on water quality of Wetlands in Japan. Water Resour Manag 27(7):2217–2229. https://doi.org/10.1007/s11269-013-0284-5Hamid A, Bhat SU, Jehangir A (2020) Local determinants infuencing stream water quality. Appl Water Sci 10(24):1–16. https://doi.org/ 10.1007/s13201-019-1043-4Hefer P, Prud’homme M (2016) Fertilizer outlook 2016–2010. In: 84th International Fertilizer Industry Association Annual Conference. Moscow (Russia), 30 May–1 June 2016. https://www. fertilizer.org/images/Library_Downloads/2016_IFa_Moscow_ Sum mary.pdfHull V, Mocenni C, Falcucci M, Marchettini N (2000) A trophodynamic model for the lagoon of Fogliano (Italy) with ecological dependent modifying parameters. Ecol Model 134:153–167Hur J, Lee BM, Lee TH, Park DH (2010) Estimation of biological oxygen demand and chemical oxygen demand for combined sewer systems using synchronous fuorescence spectra. Sensors 10(4):2460–2471IGAC-Instituto Geográfco Agustín Codazzi (2008) Estudio general de suelos y zonifcación de tierras. Departamento del Atlántico. Imprenta Nacional de Colombia, Bogotá, 324Issaka S, Ashraf M (2017) Impact of soil erosion and degradation on water quality: a review. Geol Ecol Landsc 1(1):1–11. https:// doi.org/10.1080/24749508.2017.1301053Jiménez PAL, Alemany VE, Alberola MC, Solano FJM (2003) Metodología para la calibración de modelos de calidad de aguas. Ingeniería Del Agua 10(4):501–516Jin Z, Azzari G, You C, Di Tommaso S, Aston S, Burke M, Lobell D (2019) Smallholder maize area and yield mapping at national scales with Google Earth Engine. Remote Sens Environ. https:// doi.org/10.1016/j.rse.2019.04.016Larrahondo-Molina M (1992) Aprovechamiento acuícola de embalsesen Colombia. In: Juárez JR, Varsi E (eds) Avances en el manejo yaprovechamiento acuícola de embalses en América Latina y el Caribe. Proyecto Aquila II. FAO, Organización de las Naciones Unidaspara la Agricultura y la Alimentación, Roma, p 172. https://www.fao.org/3/ab488s/AB488S04.htmLassaletta L, Billen G, Grizzetti B, Garnier J, Leach AM, Galloway JN (2014) Food and feed trade as a driver in the global nitrogen cycle: 50-year trends. Biogeochemistry 118(1–3):225–241. https://doi.org/10.1007/s10533-013-9923-4Lastovicka J, Svec P, Paluba D, Kobliuk N, Svoboda J, Hladky R, Stych P (2020) Sentinel-2 Data in an Evaluation of the Impact of the Disturbances on Forest Vegetation. Remote Sens 12:1914. https://doi.org/10.3390/rs12121914Li K, Zhang L, Li Y, Zhang L, Wang X (2015) A three-dimensional water quality model to evaluate the environmental capacity of nitrogen and phosphorus in Jiaozhou Bay, China. Mar Pollut Bull 91(1):306–316. https://doi.org/10.1016/j.marpolbul.2014. 11.020Lopes FB, Andrade EM, Meireles ACM, Becker H, Batista AA (2014) Assessment of the water quality in a large reservoir in semiarid region of Brazil. Revista Brasileira De Engenharia Agrícola Ambiental 18:437–445Malik S, Pal SC, Das B, Chakrabortty R (2019) Assessment of vegetation status of Sali River basin, a tributary of Damodar River in Bankura District, West Bengal, using satellite data. Environ Dev Sustain 22:5651–5685. https://doi.org/10.1007/ s10668-019-00444-yMartínez-Mera E, Torregroza-Espinosa A, Castañeda-Valbuena D, Crissien-Borrero T, Torres-Bejarano F (2018) El Distrito de Riego de Repelón. Editorial Universitaria de la Costa, Educosta, Diagnóstico y Evaluación Ambiental de la Actividad Agrícola. Primera Edición, p 208Martínez-Mera E, Torregroza-Espinosa AC, Crissien-Borrero TC, Marrugo Negrete JL, González-Márquez LC (2019) Evaluation of contaminants in agricultural soils in an Irrigation District in Colombia. Heliyon 5:e02217. https://doi.org/10.1016/j.heliyon. 2019.e02217Meneses BM, Reis R, Vale MJ, Saraiva R (2015) Land use and land cover changes in Zêzere watershed (Portugal)-Water quality implications. Sci Total Environ 527–528:439–447. https://doi. org/10.1016/j.scitotenv.2015.04.092Masocha M, Murwira A, Magadza CHD, Hirji R, Dube T (2017) Remote sensing of surface water quality in relation to catchment condition in Zimbabwe. Phys Chem Earth Parts A/B/C 100:13–18. https://doi.org/10.1016/j.pce.2017.02.013Ministerio de Ambiente y Desarrollo Sostenible (MinAmbiente) (1984) Decreto 1594. Usos del agua y residuos líquidosNgoye E, Machiwa JF (2004) The infuence of land-use patterns in the Ruvu river watershed on water quality in the river system. Phys Chem Earth Parts a/b/c 29(15–18):1161–1166. https://doi. org/10.1016/j.pce.2004.09.002Parson TR, Maitia Y, Lalli CM (1984) A manual of chemical and biological methods for sea water analysis. Pergamonn Press, Oxford, p 135Quamrul A, Benson B, Visser J, Gang D (2016) Response of estuarine phytoplankton to nutrient and spatio temporal pattern of physicochemical water quality parameters in little Vermilion Bay. Louisiana Ecol Inf 32:79–90Rodrigues V, Estrany J, Ranzini M, de Cicco V, Martín-Benito JM, Hedo J, Lucas-Borja ME (2018) Efects of land use and seasonality on stream water qualityin a small tropical catchment: the headwater of Córrego Água Limpa, SãoPaulo (Brazil). Sci Total Environ 622–623:1553–1561.https://doi.org/10.1016/J.SCITO TENV.2017.10.028Romero-Sierra P, Rivas D, Almazán-Becerril A, Hernández-Terrones L (2018) Hydrochemistry and hydrodynamics of a Mexican Caribbean Lagoon: Nichupté Lagoon System. Estuar Coast Shelf Sci 215:185–198Ruíz-Cabarcas AC, Pabón-Caicedo JD (2013) Efecto de los fenómenos del niño y la niña en la precipitación y su impacto en la producción agrícola del departamento del Atlántico. Colombia Cuadernos De Geografía 22(2):35–54Sahana M, Dutta S, Sajjad H (2018) Assessing land transformation and its relation with land surface temperature in Mumbai city, India using geospatial techniques. Int J Urban Sci 23(2):205–225. https://doi.org/10.1080/12265934.2018.1488604Shi P, Zhang Y, Li Z, Li P, Xu G (2017) Infuence of land use and land cover patterns on seasonal water quality at multi-spatial scales. CATENA 151:182–190. https://doi.org/10.1016/j.catena.2016. 12.017Sidi Almouctar MA, Wu Y, Kumar A et al (2021) Spatiotemporal analysis of vegetation cover changes around surface water based on NDVI: a case study in Korama basin, Southern Zinder. Niger Appl Water Sci 11:4. https://doi.org/10.1007/s13201-020-01332-xSliva L, Williams DD (2001) Bufer zone versus whole catchment approaches to studying land use impact on river water quality. Water Res 35(14):3462–3472. https://doi.org/10.1016/s0043- 1354(01)00062-8Spalevic V, Barovic G, Vujacic D, Curovic M, Behzadfar M, Djurovic N, Dudic B, Billi P (2020) The impact of land use changes on soil erosion in the river Basin of Miocki Potok. Montenegro Water 12(2973):1–28. https://doi.org/10.3390/w12112973Srilert C, Satika B (2018) Impacts of land-use changes on watershed discharge and water quality in a large intensive agricultural area in Thailand. Hydrol Sci J 63(9):1386–1407. https://doi.org/10.1080/ 02626667.2018.1506128Susilowati S, Sutrisno J, Masykuri M, Maridi M (2018) Dynamics and factors that afects DO-BOD concentrations of Madiun River. AIP Conf Proc 2049:020052. https://doi.org/10.1063/1.5082457Torregroza-Espinosa AC, Martínez-Mera E, Castañeda-Valbuena D, González-Márquez LC, Torres-Bejarano F (2018) Contamination level and spatial distribution of heavy metals in water and sediments of El Guájaro reservoir, Colombia. Bull Environ Contam Toxicol 101:61–67. https://doi.org/10.1007/s00128-018-2365-xTorres-Bejarano F, Padilla Coba J, Rodríguez-Cuevas C, Ramírez-León H, Cantero-Rodelo R (2016) La modelación hidrodinámica para la gestión hídrica del embalse del Guájaro, Colombia. Revista Internacional De Métodos Numéricos Para Cálculo y Diseño En Ingeniería 32(3):163–172. https://doi.org/10.1016/j.rimni.2015. 04.001Trenberth K (2020) National Center for Atmospheric Research Staf. The Climate Data Guide: Nino SST Indices (Nino 1+2, 3, 3.4, 4; ONI and TNI). Last modifed 21 Jan. https://climatedataguide. ucar.edu/climate-data/nino-sst-indices-nino-12-3-34-4-oni-and-tniUmwali ED, Kurban A, Isabwe A, Mind’je R, Azadi H, Guo Z, Udahogora M, Nyirarwasa A, Umuhoza J, Nzabarinda V, Gasirabo A, Sabirhazi G, (2021) Spatio-seasonal variation of water quality infuenced by land use and land cover in Lake Muhazi. Sci Rep 11:17376. https://doi.org/10.1038/s41598-021-96633-9Uninorte-Universidad del Norte (2009) Embalse El Guájaro. Diagnóstico hidráulico y ambiental de las condiciones actuales. Gobernación del Atlántico. Secretaría de Agua Potable y Saneamiento Básico, Barranquilla. p 122United Nations, Department of Economic and Social Afairs, Population Division (2014) World Urbanization Prospects: The 2014 Revision, Highlights (ST/ESA/SER.A/352). Available at: https:// population.un.org/wup/publications/fles/wup2014-highlights.pdfUSGS (2021) Landsat Missions. Disponible en: https://www.usgs.gov/ core-science-systems/nli/landsat/landsat-8?qt-science_support_ page_related_con=0#qt-science_support_page_related_conVermote E, Justice C, Claverie M, Franch B (2016) Preliminary analysis of the performance of the Landsat 8/OLI land surface refectance product. Remote Sensing of Environment 185, 46–56. doi. org/https://doi.org/10.1016/j.rse.2016.04.008Wang R, Xu T, Yu L, Zhu J, Li X (2013) Efects of land use types on surface water quality across an anthropogenic disturbance gradient in the upper reach of the Hun River, Northeast China. Environmental Monitoring and Assessment, 185: 4141–4151. http://dx. doi. org/https://doi.org/10.1007/s10661-012-2856-xWeather Spark (2021) El clima de Repelón, Atlántico. Available at: https://es.weatherspark.com/m/22615/5/Tiempo-promedio-enmayo-en-Repel%C3%B3n-Colombia#Sections-Rain.Whistler JL (1996) A phenological approach to land cover characterization using Landsat mss data for analysis of nonpoint source pollution. Project Report. U.S. Environmental Protection Agency. pp 59. Available at: http://kufs.ku.edu/media/uploads/work/kars_ report_ 96–1.pdfWilson EH, Sader SA (2002) Detection of forest harvest type using multiple dates of Landsat TM imagery. Remote Sens Environ 80(3):385–396. https://doi.org/10.1016/s0034-4257(01)00318-23590357720Vegetation coverNDVINDMIRemote sensingWater contaminationORIGINALImpact of land cover changes on water quality. an application to the Guájaro reservoir, Colombia.pdfImpact of land cover changes on water quality. an application to the Guájaro reservoir, Colombia.pdfArtículoapplication/pdf5431352https://repositorio.cuc.edu.co/bitstream/11323/9978/1/Impact%20of%20land%20cover%20changes%20on%20water%20quality.%20an%20application%20to%20the%20Gu%c3%a1jaro%20reservoir%2c%20Colombia.pdfdb80633b042b61caedab6ba4302a9dfbMD51open accessLICENSElicense.txtlicense.txttext/plain; charset=utf-814828https://repositorio.cuc.edu.co/bitstream/11323/9978/2/license.txt2f9959eaf5b71fae44bbf9ec84150c7aMD52open accessTEXTImpact of land cover changes on water quality. an application to the Guájaro reservoir, Colombia.pdf.txtImpact of land cover changes on water quality. an application to the Guájaro reservoir, 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corporada en las Obras Colectivas.

b.	Distribuir copias o fonogramas de las Obras, exhibirlas públicamente, ejecutarlas públicamente y/o ponerlas a disposición pública, incluyéndolas como incorporadas en Obras Colectivas, según corresponda.

c.	Distribuir copias de las Obras Derivadas que se generen, exhibirlas públicamente, ejecutarlas públicamente y/o ponerlas a disposición pública.
Los derechos mencionados anteriormente pueden ser ejercidos en todos los medios y formatos, actualmente conocidos o que se inventen en el futuro. Los derechos antes mencionados incluyen el derecho a realizar dichas modificaciones en la medida que sean técnicamente necesarias para ejercer los derechos en otro medio o formatos, pero de otra manera usted no está autorizado para realizar obras derivadas. Todos los derechos no otorgados expresamente por el Licenciante quedan por este medio reservados, incluyendo pero sin limitarse a aquellos que se mencionan en las secciones 4(d) y 4(e).

4. Restricciones.
La licencia otorgada en la anterior Sección 3 está expresamente sujeta y limitada por las siguientes restricciones:

a.	Usted puede distribuir, exhibir públicamente, ejecutar públicamente, o poner a disposición pública la Obra sólo bajo las condiciones de esta Licencia, y Usted debe incluir una copia de esta licencia o del Identificador Universal de Recursos de la misma con cada copia de la Obra que distribuya, exhiba públicamente, ejecute públicamente o ponga a disposición pública. No es posible ofrecer o imponer ninguna condición sobre la Obra que altere o limite las condiciones de esta Licencia o el ejercicio de los derechos de los destinatarios otorgados en este documento. No es posible sublicenciar la Obra. Usted debe mantener intactos todos los avisos que hagan referencia a esta Licencia y a la cláusula de limitación de garantías. Usted no puede distribuir, exhibir públicamente, ejecutar públicamente, o poner a disposición pública la Obra con alguna medida tecnológica que controle el acceso o la utilización de ella de una forma que sea inconsistente con las condiciones de esta Licencia. Lo anterior se aplica a la Obra incorporada a una Obra Colectiva, pero esto no exige que la Obra Colectiva aparte de la obra misma quede sujeta a las condiciones de esta Licencia. Si Usted crea una Obra Colectiva, previo aviso de cualquier Licenciante debe, en la medida de lo posible, eliminar de la Obra Colectiva cualquier referencia a dicho Licenciante o al Autor Original, según lo solicitado por el Licenciante y conforme lo exige la cláusula 4(c).

b.	Usted no puede ejercer ninguno de los derechos que le han sido otorgados en la Sección 3 precedente de modo que estén principalmente destinados o directamente dirigidos a conseguir un provecho comercial o una compensación monetaria privada. El intercambio de la Obra por otras obras protegidas por derechos de autor, ya sea a través de un sistema para compartir archivos digitales (digital file-sharing) o de cualquier otra manera no será considerado como estar destinado principalmente o dirigido directamente a conseguir un provecho comercial o una compensación monetaria privada, siempre que no se realice un pago mediante una compensación monetaria en relación con el intercambio de obras protegidas por el derecho de autor.

c.	Si usted distribuye, exhibe públicamente, ejecuta públicamente o ejecuta públicamente en forma digital la Obra o cualquier Obra Derivada u Obra Colectiva, Usted debe mantener intacta toda la información de derecho de autor de la Obra y proporcionar, de forma razonable según el medio o manera que Usted esté utilizando: (i) el nombre del Autor Original si está provisto (o seudónimo, si fuere aplicable), y/o (ii) el nombre de la parte o las partes que el Autor Original y/o el Licenciante hubieren designado para la atribución (v.g., un instituto patrocinador, editorial, publicación) en la información de los derechos de autor del Licenciante, términos de servicios o de otras formas razonables; el título de la Obra si está provisto; en la medida de lo razonablemente factible y, si está provisto, el Identificador Uniforme de Recursos (Uniform Resource Identifier) que el Licenciante especifica para ser asociado con la Obra, salvo que tal URI no se refiera a la nota sobre los derechos de autor o a la información sobre el licenciamiento de la Obra; y en el caso de una Obra Derivada, atribuir el crédito identificando el uso de la Obra en la Obra Derivada (v.g., "Traducción Francesa de la Obra del Autor Original," o "Guión Cinematográfico basado en la Obra original del Autor Original"). Tal crédito puede ser implementado de cualquier forma razonable; en el caso, sin embargo, de Obras Derivadas u Obras Colectivas, tal crédito aparecerá, como mínimo, donde aparece el crédito de cualquier otro autor comparable y de una manera, al menos, tan destacada como el crédito de otro autor comparable.

d.	Para evitar toda confusión, el Licenciante aclara que, cuando la obra es una composición musical:

i.	Regalías por interpretación y ejecución bajo licencias generales. El Licenciante se reserva el derecho exclusivo de autorizar la ejecución pública o la ejecución pública digital de la obra y de recolectar, sea individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, SAYCO), las regalías por la ejecución pública o por la ejecución pública digital de la obra (por ejemplo Webcast) licenciada bajo licencias generales, si la interpretación o ejecución de la obra está primordialmente orientada por o dirigida a la obtención de una ventaja comercial o una compensación monetaria privada.

ii.	Regalías por Fonogramas. El Licenciante se reserva el derecho exclusivo de recolectar, individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, los consagrados por la SAYCO), una agencia de derechos musicales o algún agente designado, las regalías por cualquier fonograma que Usted cree a partir de la obra (“versión cover”) y distribuya, en los términos del régimen de derechos de autor, si la creación o distribución de esa versión cover está primordialmente destinada o dirigida a obtener una ventaja comercial o una compensación monetaria privada.

e.	Gestión de Derechos de Autor sobre Interpretaciones y Ejecuciones Digitales (WebCasting). Para evitar toda confusión, el Licenciante aclara que, cuando la obra sea un fonograma, el Licenciante se reserva el derecho exclusivo de autorizar la ejecución pública digital de la obra (por ejemplo, webcast) y de recolectar, individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, ACINPRO), las regalías por la ejecución pública digital de la obra (por ejemplo, webcast), sujeta a las disposiciones aplicables del régimen de Derecho de Autor, si esta ejecución pública digital está primordialmente dirigida a obtener una ventaja comercial o una compensación monetaria privada.

5. Representaciones, Garantías y Limitaciones de Responsabilidad.
A MENOS QUE LAS PARTES LO ACORDARAN DE OTRA FORMA POR ESCRITO, EL LICENCIANTE OFRECE LA OBRA (EN EL ESTADO EN EL QUE SE ENCUENTRA) “TAL CUAL”, SIN BRINDAR GARANTÍAS DE CLASE ALGUNA RESPECTO DE LA OBRA, YA SEA EXPRESA, IMPLÍCITA, LEGAL O CUALQUIERA OTRA, INCLUYENDO, SIN LIMITARSE A ELLAS, GARANTÍAS DE TITULARIDAD, COMERCIABILIDAD, ADAPTABILIDAD O ADECUACIÓN A PROPÓSITO DETERMINADO, AUSENCIA DE INFRACCIÓN, DE AUSENCIA DE DEFECTOS LATENTES O DE OTRO TIPO, O LA PRESENCIA O AUSENCIA DE ERRORES, SEAN O NO DESCUBRIBLES (PUEDAN O NO SER ESTOS DESCUBIERTOS). ALGUNAS JURISDICCIONES NO PERMITEN LA EXCLUSIÓN DE GARANTÍAS IMPLÍCITAS, EN CUYO CASO ESTA EXCLUSIÓN PUEDE NO APLICARSE A USTED.

6. Limitación de responsabilidad.
A MENOS QUE LO EXIJA EXPRESAMENTE LA LEY APLICABLE, EL LICENCIANTE NO SERÁ RESPONSABLE ANTE USTED POR DAÑO ALGUNO, SEA POR RESPONSABILIDAD EXTRACONTRACTUAL, PRECONTRACTUAL O CONTRACTUAL, OBJETIVA O SUBJETIVA, SE TRATE DE DAÑOS MORALES O PATRIMONIALES, DIRECTOS O INDIRECTOS, PREVISTOS O IMPREVISTOS PRODUCIDOS POR EL USO DE ESTA LICENCIA O DE LA OBRA, AUN CUANDO EL LICENCIANTE HAYA SIDO ADVERTIDO DE LA POSIBILIDAD DE DICHOS DAÑOS. ALGUNAS LEYES NO PERMITEN LA EXCLUSIÓN DE CIERTA RESPONSABILIDAD, EN CUYO CASO ESTA EXCLUSIÓN PUEDE NO APLICARSE A USTED.

7. Término.

a.	Esta Licencia y los derechos otorgados en virtud de ella terminarán automáticamente si Usted infringe alguna condición establecida en ella. Sin embargo, los individuos o entidades que han recibido Obras Derivadas o Colectivas de Usted de conformidad con esta Licencia, no verán terminadas sus licencias, siempre que estos individuos o entidades sigan cumpliendo íntegramente las condiciones de estas licencias. Las Secciones 1, 2, 5, 6, 7, y 8 subsistirán a cualquier terminación de esta Licencia.

b.	Sujeta a las condiciones y términos anteriores, la licencia otorgada aquí es perpetua (durante el período de vigencia de los derechos de autor de la obra). No obstante lo anterior, el Licenciante se reserva el derecho a publicar y/o estrenar la Obra bajo condiciones de licencia diferentes o a dejar de distribuirla en los términos de esta Licencia en cualquier momento; en el entendido, sin embargo, que esa elección no servirá para revocar esta licencia o que deba ser otorgada , bajo los términos de esta licencia), y esta licencia continuará en pleno vigor y efecto a menos que sea terminada como se expresa atrás. La Licencia revocada continuará siendo plenamente vigente y efectiva si no se le da término en las condiciones indicadas anteriormente.

8. Varios.

a.	Cada vez que Usted distribuya o ponga a disposición pública la Obra o una Obra Colectiva, el Licenciante ofrecerá al destinatario una licencia en los mismos términos y condiciones que la licencia otorgada a Usted bajo esta Licencia.

b.	Si alguna disposición de esta Licencia resulta invalidada o no exigible, según la legislación vigente, esto no afectará ni la validez ni la aplicabilidad del resto de condiciones de esta Licencia y, sin acción adicional por parte de los sujetos de este acuerdo, aquélla se entenderá reformada lo mínimo necesario para hacer que dicha disposición sea válida y exigible.

c.	Ningún término o disposición de esta Licencia se estimará renunciada y ninguna violación de ella será consentida a menos que esa renuncia o consentimiento sea otorgado por escrito y firmado por la parte que renuncie o consienta.

d.	Esta Licencia refleja el acuerdo pleno entre las partes respecto a la Obra aquí licenciada. No hay arreglos, acuerdos o declaraciones respecto a la Obra que no estén especificados en este documento. El Licenciante no se verá limitado por ninguna disposición adicional que pueda surgir en alguna comunicación emanada de Usted. Esta Licencia no puede ser modificada sin el consentimiento mutuo por escrito del Licenciante y Usted.
 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