DROUGHTS ASSESSMENT IN THE VUGIA-THUBON RIVER BASIN USING REMOTE SENSING
Main Article Content
Abstract
This study has implemented an index-based approach for monitoring the droughts in the Vu Gia – Thu Bon river basin using remote sensing data and the Google Earth Engine cloud computing service. Landsat series remotely sensed data had been used effectively for the time-series calculation of the indices related to the drought hazard. In this study, we examined the performance of several remote sensing-based drought indices (RSDI) for monitoring droughts in the VuGia - ThuBon river basin (VGTB) from January 2010 to December 2020 using the cloud-based Google Earth Engine (GEE) computational platform. When tested again in-situ Potential Evapotranspiration (PET) and Soil temperature, a high agreement exists between our RSDI and PET. These results prove that remote sensing data can be an alternative solution for monitoring drought when remote sensing is the only available source.
Keywords
drought, Google Earth Engine, Landsat, Remote Sensing, RSDI, VGTB
Article Details
References
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Jain, V. K., Pandey, R. P., Jain, M. K., & Byun, H.-R. (2015). Comparison of drought indices for appraisal of drought characteristics in the Ken River Basin. Weather and Climate Extremes, 8, 1-11. https://doi.org/10.1016/j.wace.2015.05.002
Ji, L., & Peters, A. J. (2003). Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices. Remote Sensing of Environment, 87(1), 85-98. https://doi.org/10.1016/S0034-4257(03)00174-3
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Le, M. S., & Liou, Y. A. (2022). Temperature-Soil Moisture Dryness Index for Remote Sensing of Surface Soil Moisture Assessment. IEEE Geoscience and Remote Sensing Letters, 19, 1-5. https://doi.org/10.1109/LGRS.2021.3095170
Masek, J. G., Vermote, E. F., Saleous, N. E., Wolfe, R., Hall, F. G., Huemmrich, K. F., Feng, G., Kutler, J., & Teng-Kui, L. (2006). A Landsat surface reflectance dataset for North America, 1990-2000. IEEE Geoscience and Remote Sensing Letters, 3(1), 68-72. https://doi.org/10.1109/LGRS.2005.857030
McKee, T. B., Doesken, N. J., & Kleist, J. R. (1993). The relationship of drought frequency and duration to time scales
Nagarajan, R. (2010). Drought Assessment. https://doi.org/10.1007/978-90-481-2500-5
Newman, J. E., & Oliver, J. E. (2005). Palmer Index/Palmer Drought Severity Index. In J. E. Oliver (Ed.), Encyclopedia of World Climatology (pp. 571-573). Springer Netherlands. https://doi.org/10.1007/1-4020-3266-8_159
Palmer, W. (1965). Meteorological Drought. Research Paper No. 45, 1965, 58 p. 1-65.
Petropoulos, G. P., Carlson, T. N., Wooster, M. J., & Islam, S. M. (2009). A review of Ts/VI remote sensing based methods for the retrieval of land surface energy fluxes and soil surface moisture. Progress in Physical Geography, 33, 224-250.
Rhee, J., Im, J., & Carbone, G. J. (2010). Monitoring agricultural drought for arid and humid regions using multi-sensor remote sensing data. Remote Sensing of Environment, 114(12), 2875-2887. https://doi.org/10.1016/j.rse.2010.07.005.
Rouse, J. W., Haas, R. H., Schell, J. A., & Deering, D. W. (1973). Monitoring vegetation systems in the great plains with ERTS.
Sandholt, I., Rasmussen, K., & Andersen, J. (2002). A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status. Remote Sensing of Environment, 79(2), 213-224. https://doi.org/10.1016/S0034-4257(01)00274-7
Sazib, N., Mladenova, I., & Bolten, J. (2018). Leveraging the Google Earth Engine for Drought Assessment Using Global Soil Moisture Data. Remote Sensing, 10(8), 1265. https://www.mdpi.com/2072-4292/10/8/1265
Son, N. T., Chen, C. F., Chen, C. R., Chang, L. Y., & Minh, V. Q. (2012). Monitoring agricultural drought in the Lower Mekong Basin using MODIS NDVI and land surface temperature data. International Journal of Applied Earth Observation and Geoinformation, 18, 417-427. https://doi.org/10.1016/j.jag.2012.03.014
Statistical Handbook of Vietnam 2016. (2017). Hanoi: Statistical Publishing House
Thornthwaite, C. W. (1948). An Approach toward a Rational Classification of Climate. Geographical Review, 38(1), 55-94. https://doi.org/10.2307/210739
Trinh, L. H., & Dao, K. H. (2015). Drought risk evaluation using remote sensing: a case study in Bac Binh district, Binh Thuan province. Ho Chi Minh City University of Education Journal of Science, 5(7), 128-139 (Vietnamese).
Tucker, C. J. (1979). Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment, 8(2), 127-150. https://doi.org/10.1016/0034-4257(79)90013-0
Van Loon, A. F. (2015). Hydrological drought explained. 2(4), 359-392. https://doi.org/10.1002/wat2.1085
AghaKouchak, A., Farahmand, A., Melton, F. S., Teixeira, J., Anderson, M. C., Wardlow, B. D., & Hain, C. R. (2015). Remote sensing of drought: Progress, challenges and opportunities. Reviews of Geophysics, 53(2), 452-480. https://doi.org/ 10.1002/2014rg000456
Amoli, A. A., Aghighi, H., & Lopez-Baeza, E. (2022). Drought Risk Evaluation in Iran by Using Geospatial Technologies. Remote Sensing, 14(13). https://doi.org/ ARTN 309610.3390/rs14133096
Buurman, J., Goedbloed, A., Yuan, C., Bui, D., Hai, V., & Du, T. (2015). Measuring and Monitoring Droughts and Drought Risks in the Vu Gia – Thu Bon River Basin.
Du, L., Tian, Q., Yu, T., Meng, Q., Jancso, T., Udvardy, P., & Huang, Y. (2013). A comprehensive drought monitoring method integrating MODIS and TRMM data. International Journal of Applied Earth Observation and Geoinformation, 23, 245-253. https://doi.org/10.1016/j.jag.2012.09.010
Du, T., Bui, D., Buurman, J., & Quach, X. (2018). Towards adaptive governance for urban drought resilience: the case of Da Nang, Vietnam. International Journal of Water Resources Development, 1-19. https://doi.org/ 10.1080/07900627.2018.1438886
Gao, B.-c. (1996). NDWI—A normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sensing of Environment, 58(3), 257-266. https://doi.org/10.1016/S0034-4257(96)00067-3
Gidey, E., Dikinya, O., Sebego, R., Segosebe, E., & Zenebe, A. (2018). Analysis of the long-term agricultural drought onset, cessation, duration, frequency, severity and spatial extent using Vegetation Health Index (VHI) in Raya and its environs, Northern Ethiopia. Environmental Systems Research, 7(1), 13. https://doi.org/ 10.1186/s40068-018-0115-z
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
Goward, S. N., Xue, Y., & Czajkowski, K. P. (2002). Evaluating land surface moisture conditions from the remotely sensed temperature/vegetation index measurements: An exploration with the simplified simple biosphere model. Remote Sensing of Environment, 79(2), 225-242. https://doi.org/10.1016/S0034-4257(01)00275-9
Gu, Y., Hunt, E., Wardlow, B., Basara, J. B., Brown, J. F., & Verdin, J. P. (2008). Evaluation of MODIS NDVI and NDWI for vegetation drought monitoring using Oklahoma Mesonet soil moisture data. Geophysical Research Letters, 35(22). https://doi.org/10.1029/2008GL035772.
He, Y., Chen, F., Jia, H., Wang, L., & Bondur, V. G. (2020). Different Drought Legacies of Rain-Fed and Irrigated Croplands in a Typical Russian Agricultural Region. Remote Sensing, 12(11). https://doi.org/10.3390/rs12111700
Ho, L. T. K., & Umitsu, M. (2011). Micro-landform classification and flood hazard assessment of the Thu Bon alluvial plain, central Vietnam via an integrated method utilizing remotely sensed data. Applied Geography, 31, 1082-1093
Jain, V. K., Pandey, R. P., Jain, M. K., & Byun, H.-R. (2015). Comparison of drought indices for appraisal of drought characteristics in the Ken River Basin. Weather and Climate Extremes, 8, 1-11. https://doi.org/10.1016/j.wace.2015.05.002
Ji, L., & Peters, A. J. (2003). Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices. Remote Sensing of Environment, 87(1), 85-98. https://doi.org/10.1016/S0034-4257(03)00174-3
Karnieli, A., Agam, N., Pinker, R. T., Anderson, M., Imhoff, M. L., Gutman, G. G., Panov, N., & Goldberg, A. (2010). Use of NDVI and Land Surface Temperature for Drought Assessment: Merits and Limitations. Journal of Climate, 23(3), 618-633. https://doi.org/10.1175/2009JCLI2900.1
Kogan, F. N. (1995). Droughts of the Late 1980s in the United States as Derived from NOAA Polar-Orbiting Satellite Data. Bulletin of the American Meteorological Society, 76(5), 655-668. http://www.jstor.org/stable/26232390
Le, M. S., & Liou, Y. A. (2022). Temperature-Soil Moisture Dryness Index for Remote Sensing of Surface Soil Moisture Assessment. IEEE Geoscience and Remote Sensing Letters, 19, 1-5. https://doi.org/10.1109/LGRS.2021.3095170
Masek, J. G., Vermote, E. F., Saleous, N. E., Wolfe, R., Hall, F. G., Huemmrich, K. F., Feng, G., Kutler, J., & Teng-Kui, L. (2006). A Landsat surface reflectance dataset for North America, 1990-2000. IEEE Geoscience and Remote Sensing Letters, 3(1), 68-72. https://doi.org/10.1109/LGRS.2005.857030
McKee, T. B., Doesken, N. J., & Kleist, J. R. (1993). The relationship of drought frequency and duration to time scales
Nagarajan, R. (2010). Drought Assessment. https://doi.org/10.1007/978-90-481-2500-5
Newman, J. E., & Oliver, J. E. (2005). Palmer Index/Palmer Drought Severity Index. In J. E. Oliver (Ed.), Encyclopedia of World Climatology (pp. 571-573). Springer Netherlands. https://doi.org/10.1007/1-4020-3266-8_159
Palmer, W. (1965). Meteorological Drought. Research Paper No. 45, 1965, 58 p. 1-65.
Petropoulos, G. P., Carlson, T. N., Wooster, M. J., & Islam, S. M. (2009). A review of Ts/VI remote sensing based methods for the retrieval of land surface energy fluxes and soil surface moisture. Progress in Physical Geography, 33, 224-250.
Rhee, J., Im, J., & Carbone, G. J. (2010). Monitoring agricultural drought for arid and humid regions using multi-sensor remote sensing data. Remote Sensing of Environment, 114(12), 2875-2887. https://doi.org/10.1016/j.rse.2010.07.005.
Rouse, J. W., Haas, R. H., Schell, J. A., & Deering, D. W. (1973). Monitoring vegetation systems in the great plains with ERTS.
Sandholt, I., Rasmussen, K., & Andersen, J. (2002). A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status. Remote Sensing of Environment, 79(2), 213-224. https://doi.org/10.1016/S0034-4257(01)00274-7
Sazib, N., Mladenova, I., & Bolten, J. (2018). Leveraging the Google Earth Engine for Drought Assessment Using Global Soil Moisture Data. Remote Sensing, 10(8), 1265. https://www.mdpi.com/2072-4292/10/8/1265
Son, N. T., Chen, C. F., Chen, C. R., Chang, L. Y., & Minh, V. Q. (2012). Monitoring agricultural drought in the Lower Mekong Basin using MODIS NDVI and land surface temperature data. International Journal of Applied Earth Observation and Geoinformation, 18, 417-427. https://doi.org/10.1016/j.jag.2012.03.014
Statistical Handbook of Vietnam 2016. (2017). Hanoi: Statistical Publishing House
Thornthwaite, C. W. (1948). An Approach toward a Rational Classification of Climate. Geographical Review, 38(1), 55-94. https://doi.org/10.2307/210739
Trinh, L. H., & Dao, K. H. (2015). Drought risk evaluation using remote sensing: a case study in Bac Binh district, Binh Thuan province. Ho Chi Minh City University of Education Journal of Science, 5(7), 128-139 (Vietnamese).
Tucker, C. J. (1979). Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment, 8(2), 127-150. https://doi.org/10.1016/0034-4257(79)90013-0
Van Loon, A. F. (2015). Hydrological drought explained. 2(4), 359-392. https://doi.org/10.1002/wat2.1085