Cambios en la cobertura de nieve y su relación con el caudal para la caracterización, monitoreo y gestión de las cuencas de montaña en los Andes extratropicales de Chile entre los 29° y 37°S utilizando teledetección
DOI:
https://doi.org/10.48162/rev.40.010Palabras clave:
cobertura nival, hidrología de montaña, Andes extratropicales, teledetección, Google Earth EngineResumen
Chile Central (30° - 37°S), concentra cerca del 75% de la población total del país, lo cual se traduce en una enorme demanda hídrica. Gran parte del agua disponible del área en cuestión proviene de la nieve estacional y los glaciares ubicados en la alta cordillera. En este contexto, el cambio climático se emplaza como una amenaza para la seguridad hídrica, mediante la disminución en las precipitaciones y la aceleración del derretimiento de las nieves. Se hace necesario contar con robustos sistemas de monitoreo de la variabilidad espacio temporal de los patrones de nieve de manera de poder cuantificar efectos y zonificar áreas afectadas para desarrollar sistemas de pronósticos y preparar planes de contingencia. El presente trabajo establece la relación entre cobertura nival y el caudal, determinando la variabilidad espaciotemporal entre el año 2000-2020 de subcuencas de los Andes extratropicales de Chile (29°-37°S), mediante imágenes satelitales MODIS y variables climáticas utilizando Google Earth Engine. Los resultados, dan cuenta a la caracterización del régimen hidrológico y el patrón estacional de la nieve de las subcuencas estudiadas, siendo de régimen nival las ubicadas en la porción central del área de estudio (30,5°-35° S), y las mixtas en los bordes (29° y 36° S). Esta configuración, repercute en la dinámica anual de los caudales en donde se aprecia un periodo de desfase entre el máximo de precipitación sólida y el máximo del caudal. Asimismo, se observó una disminución constante en la cobertura de nieves durante los últimos 20 años, siendo apreciable que en la porción central del área de estudio (i.e. 33° - 35°S) este proceso ocurre de forma más severa. La experiencia obtenida en función al análisis y resultados en este trabajo, indica la factibilidad de utilizar aproximaciones asociadas a la teledetección satelital a fin de estimar variaciones en el patrón de cobertura de nieve y caracterizar de mejor manera los regímenes hidrológicos de cuencas con datos meteorológicos limitados con el propósito de apoyar el monitoreo hídrico para
la sustentabilidad de la criósfera y para la seguridad hídrica de los territorios.
Citas
Aceituno, P., Boisier, J. P., Garreaud, R., Rondanelli, R., & Rutllant, J. A. (2021). Climate and Weather in Chile. In B. Fernández & J. Gironás (Eds.), Water Resources of Chile (pp. 7-29). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-030-56901-3_2
Adam, J. C., Hamlet, A. F., & Lettenmaier, D. P. (2009). Implications of global climate change for snowmelt hydrology in the twenty-first century. Hydrological processes, 23(7), 962-972. https://doi.org/10. 1002/hyp.7201
Adler, R. F., Huffman, G. J., Chang, A., Ferraro, R., Xie, P.-P., Janowiak, J., . . . Nelkin, E. (2003). The Version2 Global Precipitation Climatology Project (GPCP) Monthly Precipitation Analysis (1979–Present). Journal of Hydrometeorology, 4(6), 1147-1167. https://doi:10.1175/1525-7541(2003)004<1147:Tvgpcp>2.0.Co;2
Alizadeh, Z., Yazdi, J., Kim, J. H., & Al-Shamiri, A. K. (2018). Assessment of Machine Learning Techniques for Monthly Flow Prediction. Water, 10(11), 1676. Retrieved from https://www.mdpi.com/2073-4441/10/11/1676
Alvarez-Garreton, C., Boisier, J. P., Garreaud, R., Seibert, J., & Vis, M. (2021). Progressive water deficits during multiyear droughts in basins with long hydrological memory in Chile. Hydrol. Earth Syst. Sci., 25(1), 429-446.https://doi.org/10.5194/hess-25-429-2021
Aravena, J. C., & Luckman, B. H. (2009). Spatio-temporal rainfall patterns in southern South America. International Journal of Climatology: A Journal of the Royal Meteorological Society, 29(14), 2106-2120. https://doi.org/10.1002/joc.1761
Arsenault, K. R., Houser, P. R., & De Lannoy, G. J. M. (2014). Evaluation of the MODIS snow cover fraction product. Hydrological processes, 28(3), 980-998. https://doi.org/10.1002/hyp.9636
Barnett, T. P., Adam, J. C., & Lettenmaier, D. P. (2005). Potential impacts of a warming climate on water availability in snow-dominated regions. Nature, 438(7066), 303-309. https://doi.org/10.1038/nature04141
Bormann, K. J., Brown, R. D., Derksen, C., & Painter, T. H. (2018). Estimating snow-cover trends from space. Nature Climate Change, 8(11), 924-928. https://doi.org/10.1038/s41558-018-0318-3
Borsdorf, A., & Stadel, C. (2015). The Andes: a geographical portrait: Springer. https://doi.org/10.1007/978-3-319-03530-7
Cordero, R. R., Asencio, V., Feron, S., Damiani, A., Llanillo, P. J., Sepulveda, E., . . . Casassa, G. (2019). DrySeason Snow Cover Losses in the Andes (18°-40°S) driven by Changes in Large-Scale Climate Modes. Scientific Reports, 9(1), 16945-16945. https://doi.org/10.1038/s41598-019-53486-7
Cortés, G. (2010). Evaluación de un modelo hidrológico semi distribuido para la estimación de la escorrentía de deshielo en el río Juncal. Departamento de Ingenieria Civil.
Cortés, G., & Margulis, S. (2017). Impacts of El Niño and La Niña on interannual snow accumulation in the Andes: Results from a high-resolution 31 year reanalysis. Geophysical Research Letters, 44(13), 6859-6867. https://doi.org/10.1002/2017GL073826
Cortés, G., Vargas, X., & McPhee, J. (2011). Climatic sensitivity of streamflow timing in the extratropical western Andes Cordillera. Journal of Hydrology, 405(1), 93-109. https://doi.org/10.1016/j.jhydrol.2011.05.013
Deems, J. S., Painter, T. H., & Finnegan, D. C. (2013). Lidar measurement of snow depth: a review. Journal of Glaciology, 59(215), 467-479. doi:https://doi.org/10.3189/2013JoG12J154
Dong, C. (2018). Remote sensing, hydrological modeling and in situ observations in snow cover research: A review. Journal of Hydrology, 561, 573-583. https://doi.org/10.1016/j.jhydrol.2018.04.027
Falvey, M., & Garreaud, R. (2007). Wintertime Precipitation Episodes in Central Chile: Associated Meteorological Conditions and Orographic Influences. Journal of Hydrometeorology, 8(2), 171-193. doi:https://doi.org/10.1175/jhm562.1
Farías-Barahona, D., Vivero, S., Casassa, G., Schaefer, M., Burger, F., Seehaus, T., . . . Braun, M. H. (2019). Geodetic Mass Balances and Area Changes of Echaurren Norte Glacier (Central Andes, Chile) between 1955 and 2015. Remote Sensing, 11(3), 260. Retrieved fromhttps://www.mdpi.com/2072-4292/11/3/260
Favier, V., Falvey, M., Rabatel, A., Praderio, E., & López, D. (2009). Interpreting discrepancies between discharge and precipitation in high-altitude area of Chile's Norte Chico region (26–32°S). Water Resources Research, 45(2). https://doi.org/10.1029/2008WR006802
Fernández, B., & Gironás, J. (2021). Water Resources of Chile (Vol. 8): Springer.
Fritze, H., Stewart, I. T., & Pebesma, E. (2011). Shifts in Western North American Snowmelt Runoff Regimes for the Recent Warm Decades. Journal of Hydrometeorology, 12(5), 989-1006. https://doi.org/10.1175/2011jhm1360.1
Gao, F., Wang, Y., & Hu, X. (2019). Evaluation of the suitability of Landsat, MERIS, and MODIS for identifying spatial distribution patterns of total suspended matter from a self-organizing map (SOM) perspective. CATENA, 172, 699-710. https://doi.org/10.1016/j.catena.2018.09.031
Garreaud, R. D., Boisier, J. P., Rondanelli, R., Montecinos, A., Sepúlveda, H. H., & Veloso-Aguila, D. (2020). The Central Chile Mega Drought (2010–2018): A climate dynamics perspective. International Journal of Climatology, 40(1), 421-439. https://doi.org/10.1002/joc.6219
Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., & Moore, R. (2017). Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment, 202, 18-27. https://doi.org/10.1016/j.rse.2017.06.031
Hall, D., & Riggs, G. A. (2007). Accuracy assessment of the MODIS snow products. Hydrological processes, 21(12), 1534-1547. https://doi.org/10.1002/hyp.6715
Hall, D., Foster, J. L., DiGirolamo, N. E., & Riggs, G. A. (2012). Snow cover, snowmelt timing and stream power in the Wind River Range, Wyoming. Geomorphology, 137(1), 87-93. https://doi.org/10.1016/j.geomorph.2010.11.011
Hall, D. K., Riggs, G. A., DiGirolamo, N. E., & Román, M. O. (2019). Evaluation of MODIS and VIIRS cloudgap-filled snow-cover products for production of an Earth science data record. Hydrol. Earth Syst. Sci., 23(12), 5227-5241. https://doi.org/10.5194/hess-23-5227-2019
IPCC. (2019). IPCC Special Report on the ocean and cryosphere in a changing climate.
Khatibi, R., Sivakumar, B., Ghorbani, M. A., Kisi, O., Koçak, K., & Farsadi Zadeh, D. (2012). Investigating chaos in river stage and discharge time series. Journal of Hydrology, 414-415, 108-117. https://doi.org/10.1016/j.jhydrol.2011.10.026
Li, X., Jing, Y., Shen, H., & Zhang, L. (2019). The recent developments in cloud removal approaches of MODIS snow cover product. Hydrol. Earth Syst. Sci., 23(5), 2401-2416. https://doi.org/10.5194/hess-23-2401-2019
Lundquist, J. D., Dickerson-Lange, S., Gutmann, E., Jonas, T., Lumbrazo, C., & Reynolds, D. (2021). Snow interception modelling: Isolated observations have led to many land surface models lacking appropriate temperature sensitivities. Hydrological processes, 35(7), e14274.https://doi.org/10.1002/hyp.14274
Malmros, J. K., Mernild, S. H., Wilson, R., Tagesson, T., & Fensholt, R. (2018). Snow cover and snow albedo changes in the central Andes of Chile and Argentina from daily MODIS observations (2000–2016). Remote Sensing of Environment, 209, 240-252. https://doi.org/10.1016/j.rse.2018.02.072
Mardones Bascuñan, P. B. (2019). Impactos del cambio climático en la altura de la isoterma 0° C sobre Chile Central, Chile: Universidad de Chile.
Markstrom, S. L., Regan, R. S., Hay, L. E., Viger, R. J., Webb, R. M., Payn, R. A., & LaFontaine, J. H. (2015). PRMS-IV, the precipitation-runoff modeling system, version 4. US Geological Survey Techniques and Methods, 6, B7.
Masiokas, M. H., Rabatel, A., Rivera, A., Ruiz, L., Pitte, P., Ceballos, J. L.,. . . MacDonell, S. (2020). A Review of the Current State and Recent Changes of the Andean Cryosphere. frontiers in Earth Science, 8(99). https://doi.org/10.3389/feart.2020.00099
Masiokas, M., Villalba, R., Luckman, B., Christie, D., Betman, E., Le Quesne, C., . . . Prieto, M. (2013). Recent and historic Andean snowpack and streamflow variations and vulnerability to water shortages in Central Chile and Central-western Argentina.
Masiokas, M., Villalba, R., Luckman, B., Le Quesne, C., & Aravena, J. (2006). Snowpack Variations in the Central Andes of Argentina and Chile, 1951-2005: Large-Scale Atmospheric Influences and Implications for Water Resources in the Region. Journal of Climate, 19(24), 6334-6352.
https://doi.org/10.1175/jcli3969.1
Méndez-Gutiérrez, A. G., Corral-Rivas, S., Nájera-Luna, J. A., Cruz-Cobos, F., & Pompa-García, M. (2021).Morphometric analysis of El Salto watershed, Durango, México. Terra Latinoamericana, 39. https://doi.org/10.28940/terra.v39i0.641
McNamara, I., Nauditt, A., Zambrano-Bigiarini, M., Ribbe, L., & Hann, H. (2020). Modelling water resources for planning irrigation development in drought-prone southern Chile. International Journal of Water Resources Development, 1-26. https://doi.org/10.1080/07900627.2020.1768828
Mernild, S. H., Liston, G. E., Hiemstra, C. A., Malmros, J. K., Yde, J. C., & McPhee, J. (2017). The Andes Cordillera. Part I: snow distribution, properties, and trends (1979–2014). International Journal of Climatology, 37(4), 1680-1698. https://doi.org/10.1002/joc.4804
Mernild, S. H., Liston, G. E., Hiemstra, C. A., Yde, J. C., McPhee, J., & Malmros, J. K. (2017). The Andes Cordillera. Part II: Rio Olivares Basin snow conditions (1979–2014), central Chile. International Journal of Climatology, 37(4), 1699-1715.https://doi.org/10.1002/joc.4828
Molotch, N. P., & Meromy, L. (2014). Physiographic and climatic controls on snow cover persistence in the Sierra Nevada Mountains. Hydrological processes, 28(16), 4573-4586. https://doi.org/10.1002/hyp.10254
Pagano, T., & Garen, D. (2003). Use of Climate Information in Official Western US Water Supply Forecasts. World Water & Environmental Resources Congress 2003, 1-9. https://doi.org/doi:10.1061/40685(2003)377
Ragettli, S., Cortés, G., McPhee, J., & Pellicciotti, F. (2014). An evaluation of approaches for modelling hydrological processes in high-elevation, glacierized Andean watersheds. Hydrological processes, 28(23), 5674-5695. https://doi.org/10.1002/hyp.10055
Rango, A., Martinec, J., & Roberts, R. (2008). Relative importance of glacier contributions to water supply in a changing climate. World Resource Review, 20(3), 233-251.
Rango, A., Salomonson, V. V., & Foster, J. L. (1977). Seasonal streamflow estimation in the Himalayan region employing meteorological satellite snow cover observations. Water Resources Research, 13(1), 109-112. https://doi.org/10.1029/WR013i001p00109
Richer, E., Kampf, S., Fassnacht, S., & Moore, C. (2013). Spatiotemporal index for analyzing controls on snow climatology: application in the Colorado Front Range. Physical Geography, 34(2), 85-107. https://doi:10.1080/02723646.2013.787578
Rojas, M. (2006). Multiply Nested Regional Climate Simulation for Southern South America: Sensitivity to Model Resolution. Monthly Weather Review, 134(8), 2208-2223. https://doi.org/10.1175/mwr3167.1
Saavedra, F. (2016). Spatial and temporal variability of snow cover in the Andes Mountains and its influence on streamflow in snow dominant rivers. Colorado State: University. Libraries.
Saavedra, F, Kampf, S., Fassnacht, S., & Sibold, J. (2017). A snow climatology of the Andes Mountains from MODIS snow cover data. International Journal of Climatology, 37(3), 1526-1539. https://doi.org/10.1002/joc.4795
Saavedra, F., Kampf, S., Fassnacht, S., & Sibold, J.(2018). Changes in Andes snow cover from MODIS data, 2000–2016. The Cryosphere, 12(3), 1027-1046.https://doi.org/10.5194/tc-12-1027-2018
Shaw, T. E., Gascoin, S., Mendoza, P. A., Pellicciotti, F., & McPhee, J. (2020). Snow Depth Patterns in a High Mountain Andean Catchment from Satellite Optical Tristereoscopic Remote Sensing. Water Resources Research, 56(2), e2019WR024880. https://doi.org/10.1029/2019WR024880
Stewart, I. T. (2009). Changes in snowpack and snowmelt runoff for key mountain regions. Hydrological processes, 23(1), 78-94. https://doi.org/10.1002/hyp.7128
Theobald, D. M., Harrison-Atlas, D., Monahan, W. B., & Albano, C. M. (2015). Ecologically-Relevant Maps of Landforms and Physiographic Diversity for Climate Adaptation Planning. PLOS ONE, 10(12), e0143619. http://doi:10.1371/journal.pone.0143619
Tsai, Y.-L. S., Dietz, A., Oppelt, N., & Kuenzer, C. (2019). Wet and Dry Snow Detection Using Sentinel-1 SAR Data for Mountainous Areas with a Machine Learning Technique. Remote Sensing, 11(8), 895. http://dx.doi.org/10.3390/rs11080895
Wałęga, A., & Rutkowska, A. (2015). Usefulness of the Modified NRCS-CN Method for the Assessment of Direct Runoff in a Mountain Catchment. Acta Geophysica, 63(5), 1423-1446. http://dx.doi.org/10.1515/acgeo-2015-0043
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