Determination of water quality Vichuquén Lake, using satellite images Landsat 8, sensor OLI, year 2016, Chile

Authors

  • I. Briceño-de-Urbaneja Universidad Mayor https://orcid.org/0000-0002-1722-636X
  • W. Pérez Universidad Mayor
  • D. San Miguel Ministerio de Obras Públicas
  • S. Ramos Universidad Central de Venezuela

DOI:

https://doi.org/10.4995/raet.2018.10126

Keywords:

Vichuquén lake, Trophic stages, Landsat8-OLI, Reservoirs management, LMR models

Abstract

Trophic structure deterioration in continental water bodies (lakes and damps) has been a growing problem during the last years. Numerous factors, either natural or man-made contribute in value increments of various water quality indexes ranging toward eutrophication. Our study had objective to use remote sensing as complementary tool to study the spatial distribution and dynamics of Lake Vichuquén water quality parameters in two seasons of 2016 through the use of two satellite images of the Landsat 8 OLI sensor, with in situ and laboratory data. The Chl-a and ZSD parameters were estimated from multiple linear regression models. The results indicate that the trophic state of Lake Vichuquén corresponds to a eutrophic level in summer and mesotrophic in autumn. The laboratory analyzes establish for the summer and autumn season that the Chl-a data oscillate between 14.1 and 5.5 μg/l and for the ZSD between 3.7 and 2.5 m respectively. The increase in the levels of eutrophication of Lake Vichuquén is influenced in the first place by the seasonality and secondly by the different land uses that accelerate this type of processes; such as the plantations of radiata pine and eucalyptus, the agricultural activities and the urban areas surrounding the lake. The mean square error for each variable and each season varied in Chl-a in summer and another year 0.74 and 0.01 µg/l and ZSD 0.16 m respectively.

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Author Biographies

I. Briceño-de-Urbaneja, Universidad Mayor

Hémera Centro de Observación de la Tierra, Facultad de Ciencias

Magíster en Teledetección

W. Pérez, Universidad Mayor

Director de Hémera Centro de Observación de la Tierra, Facultad de Ciencias

Magíster en Teledetección

D. San Miguel, Ministerio de Obras Públicas

Dirección General de Aguas (DGA), Unidad de Desarrollo Ambiental, Departamento de Conservación y Protección de Recursos Hídricos, Ministerio de Obras Públicas

S. Ramos, Universidad Central de Venezuela

Profesor, Instituto de Zoología y Ecología Tropical. Facultad de Ciencias

References

Boehrer, B., Schultze, M. 2008. Stratification of lakes. Reviews of Geophysics, 46(2), 1–27. https://doi.org/10.1029/2006RG000210

Bonansea, M., Ledesma, C., Rodríguez, C., Sanchez Delgado, A. R. 2012. Concentración de clorofila-a y limite de zona fótica en el embalse Rio Tercero (Argentina) utilizando imágenes del satélite CBERS-2B. Ambiente & Água -An Interdisciplinary Journal of Applied Science, 7(3). https://doi.org/10.4136/ambi-agua.847

Bukata, R. P., Jerome, J. H., Kondratyev, K. Y., Pozdnyakov, D. V. 1991. Estimation of Organic and Inorganic Matter in Inland Waters: Optical Cross Sections of Lakes Ontario and Ladoga. Journal of Great Lakes Research, 17(4), 461-469. https://doi.org/10.1016/S0380-1330(91)71382-8

Centro de Ecología Aplicada. 2014. Diagnóstico de la condición trófica de cuerpos lacustres utilizando nuevas herramientas tecnológicas. Gobierno de Chile, Ministerio de Obras Públicas, Santiago, Chile. Disponible en: http://documentos.dga.cl/LGO5517.pdf

Chen, H. 2016. Monitoring tropical billabong water turbidity using Remotely Piloted Aircraft System (RPAS) derived imagery. Charles Darwin University. Disponible en: http://espace.cdu.edu.au/eserv/ cdu:59859/Thesis_CDU_59859_Chen_H.pdf

CONAF. 2009. Catastro y evaluación de recursos vegetacionales nativos de Chile. Catastro de Bosque Nativo de la Región El Maule. Disponible en: http://www.conaf.cl/nuestros-bosques/bosques-enchile/catastro-vegetacional/

Cox, B. A. 2003. A review of currently available instream water-quality models and their applicability for simulating dissolved oxygen in lowland rivers. Science of the Total Environment, 314, 335-377. https://doi.org/10.1016/S0048-9697(03)00063-9

Cox, R. M., Forsythe, R. D., Vaughan, G. E., Olmsted, L. L. 1998. Assessing water quality in catawba river reservoirs using landsat thematic mapper satellite data. Lake and Reservoir Management, 14(4), 405- 416. https://doi.org/10.1080/07438149809354347

Frêne, C., Núñez, M. 2010. Hacia un nuevo Modelo Forestal en Chile. Revista Bosque Nativo, 47, 25- 35. Disponible en: http://www.bosquenativo.cl/ descargas/Revista_Bosque_Nativo/RBN_47_art_ op2web.pdf

Fuller, L. M., Aichele, S. S., Minnerick, R. J. 2004. Predicting water quality by relating Secchi-disk transparency and chlorophyll a measurements to satellite imagery for Michigan inland lakes, August 2002. US Department of the Interior, US Geological Survey. Disponible en: https://pubs.usgs.gov/ sir/2004/5086/pdf/sir2004-5086.pdf https://doi.org/10.3133/sir20045086

Giardino, C., Bresciani, M., Cazzaniga, I., Schenk, K., Rieger, P., Braga, F., Matta, E., Brando, V. E. 2014. Evaluation of multi-resolution satellite sensors for assessing water quality and bottom depth of Lake Garda. Sensors (Switzerland), 14(12), 24116- 24131. https://doi.org/10.3390/s141224116

Giardino, C., Pepe, M., Brivio, P. A., Ghezzi, P., Zilioli, E. 2001. Detecting chlorophyll, Secchi disk depth and surface temperature in a sub-alpine lake using Landsat imagery. Science of the Total Environment, 268(1–3), 19-29. https://doi.org/10.1016/S0048- 9697(00)00692-6

Gitelson, A. 1992. The peak near 700 nm on radiance spectra of algae and water: relationships of its magnitude and position with chlorophyll concentration. International Journal of Remote Sensing, 13(17), 3367-3373. https://doi.org/10.1080/01431169208904125

Gitelson, A., Garbuzov, G., Szilagyi, F., Mittenzwey, K. H., Karnieli, A., Kaiser, A. 1993. Quantitative remote sensing methods for real-time monitoring of inland waters quality. International Journal of Remote Sensing, 14(7), 1269-1295. https://doi.org/10.1080/01431169308953956

Gomi, T., Moore, R. D., Hassan, M. A. 2005. Suspended sediment dynamics in samll forest streams of the Pacific Northwest. Journal of the American Water Resources Association, 41(4), 877-898. https://doi.org/10.1111/j.1752-1688.2005.tb03775.x

Khorram, S., Cheshire, H., Geraci, A. L., Rosa, G. 1991. Water quality mapping of Augusta Bay, Italy from Landsat-TM data. International Journal of Remote Sensing, 12(4), 803-808. https://doi.org/10.1080/01431169108929696

Kruse, F. A. 2004. Comparison of ATREM, ACORN, and FLAASH atmospheric corrections using lowaltitude AVIRIS data of Boulder, CO. In Summaries of 13th JPL Airborne Geoscience Workshop, Jet Propulsion Lab, Pasadena, CA. Disponible en: http://ww.hgimaging.com/PDF/Kruse-JPL2004_ ATM_Compare.pdf

Larkin, J. H. 2014. Detecting Long-Term Trends in Water Quality Parameters Using Remote Sensing Techniques. Thesis. University of Illinois at UrbanaChampaign. Disponible en: http://hdl.handle. net/2142/49576

Ledesma, C., Bonansea, M., Rodríguez, C. M., Sánchez, A. R. 2013. Determinación de indicadores de eutrofización en el embalse Río Tercero, Córdoba (Argentina). Revista Ciencia Agronomica, 44(3), 419-425. https://doi.org/10.1590/S1806- 66902013000300002

Lillesand, T. M., Kiefer, R. W., Chipman, J. W. 2004. Remote Sensing and Image Interpretation. (I. John Wiley & Sons, Ed.) (Fifth, Vol. 53). United States of America: UG I GGS Information Services, Inc.

Lim, J., Choi, M. 2015. Assessment of water quality based on Landsat 8 operational land imager associated with human activities in Korea. Environmental Monitoring and Assessment, 187(6), 384. https://doi.org/10.1007/s10661-015-4616-1

M &W Ambientales. 2014. Evaluación de la condición trófica de la red de control de lagos de la Dirección General de Aguas. Santiago. Disponible en: http://documentos.dga.cl/LGO5518.pdf

Matthews, M. W. 2011. A current review of empirical procedures of remote sensing in inland and near-coastal transitional waters. International Journal of Remote Sensing, 32(21), 6855-6899. https://doi.org/10.1080/01431161.2010.512947

OCDE. 1982. Eutrophication of waters: monitoring, assessment and control. Paris: Organisation for Economic Co-operation and Development; Washington, DC: Sold by OECD Publications and Information Center. https://doi.org/10.1002/iroh.19840690206

Peters, N. E., Meybeck, M. 2000. Water quality degradation effects on freshwater availability: impacts of human activities. Water International, 25(2), 185- 193. https://doi.org/10.1080/02508060008686817

Rojas Vuscovich, J. L., Tavares Rocha, Y. 2011. Implementación de prácticas públicas y privadas relacionadas al ordenamiento territorial a través de la determinación de unidades de paisaje en la cuenca hidrográfica del Lago Vichuquén, Chile. Revista Geográfica de América Central, 2, 1-22. http:// www.redalyc.org/articulo.oa?id=451744820762

Ruddick, K. G., Cauwer, V. De, Park, Y., Moore, G. 2006. Seaborne measurements of near infrared water-leaving reflectance : The similarity spectrum for turbid waters. Limology and Oceanography, 51(2), 1167-1179. https://doi.org/10.4319/ lo.2006.51.2.1167

Sánchez, E., Colmenarejo, M. F., Vicente, J., Rubio, A., García, M. G., Travieso, L., Borja, R. 2007. Use of the water quality index and dissolved oxygen deficit as simple indicators of watersheds pollution. Ecological Indicators, 7(2), 315-328. https://doi. org/10.1016/j.ecolind.2006.02.005

Sass, G. Z., Creed, I. F., Bayley, S. E., Devito, K. J. 2008. Interannual variability in trophic status of shallow lakes on the Boreal Plain: Is there a climate signal? Water Resources Research, 44(8). https://doi.org/10.1029/2007WR006310

Serwan, M. J. B. 1996. Trophic classification and ecosystem checking of lakes using remotely sensed information. Hydrological Sciences Journal, 41(6), 939-957. https://doi.org/10.1080/02626669609491560

Tenjo, C., Ruiz-Verdú, A., Delegido, J., Peña, R., Moreno, J. 2014. Determinación de componentes ópticamente activos en aguas continentales a partir de imágenes Landsat-8. UD y La Geomática, (9), 37-46.

Wang, Y., Xia, H., Fu, J., Sheng, G. 2004. Water quality change in reservoirs of Shenzhen, China: detection using LANDSAT/TM data. Science of the Total Environment, 328(1–3), 195-206. https://doi.org/10.1016/j.scitotenv.2004.02.020

Wells, M. L., Trainer, V. L., Smayda, T. J., Karlson, B. S. O., Trick, C. G., Kudela, R. M., Ishikawa, A., Bernard, S., Wulff, A., Anderson, D. M., Cochlan, W. P. 2015. Harmful algal blooms and climate change: Learning from the past and present to forecast the future. Harmful Algae, 49, 68-93. https://doi.org/10.1016/j.hal.2015.07.009

Yang, X., Wu, X., Hao, H., He, Z. 2008. Mechanisms and assessment of water eutrophication. Journal of Zhejiang University SCIENCE B, 9(3), 197-209. https://doi.org/10.1631/jzus.B0710626

Published

2018-12-26

Issue

Section

Practical cases