Abstract
Drought is one of the most frequent and widespread natural disasters and has tremendous agricultural, ecological, societal, and economic impacts. Among the many drought indices, the standardized precipitation index (SPI) based on monthly precipitation data is simple to calculate and has multiscale characteristics. To evaluate the applicability of high spatiotemporal resolution satellite precipitation products for drought monitoring, based on the Tropical Rainfall Measuring Mission (TRMM) products and station-based meteorological data, the SPI values at different time scales (1, 3, 6, and 12 months) were calculated for the period of 1998–2016 in the middle and lower reaches of the Yangtze River Basin (MLRYRB). The temporal correlations show that there is a high degree of consistency between calculations at the different time scales (1, 3, 6 and 12 months) based on the two data sources and that the amplitude of fluctuations decreases with increasing time scale. In addition, the Mann-Kendall (MK) test method was applied to analyze the trends from 1998 to 2016, and the results suggest that wetting trends clearly prevailed over drying trends. Moreover, a correlation analysis of the two data sources based on 60 meteorological stations was performed with the SPI values at different time scales. The correlation coefficients at the short time scales (1, 3, and 6 months) are all greater than 0.7, and the correlation coefficient at the long time scale (12 months) is greater than 0.5. In summary, the results demonstrate that the TRMM 3B43 precipitation product provides a new data source that can be used for reliable drought monitoring in the MLRYRB.
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References
Cashion J, Lakshmi V, Bosch D et al., 2005. Microwave remote sensing of soil moisture: Evaluation of the TRMM microwave imager (TMI) satellite for the Little River Watershed Tifton, Georgia. Journal of Hydrology, 307(1–1): 242–253.
Dabanlı İ, Mishra A K, Sen Z, 2017. Long-term spatio-temporal drought variability in Turkey. Journal of Hydrology, 552: 779–792.
Dai A, 2011. Drought under global warming: A review. Wiley Interdisciplinary Reviews: Climate Change, 2(1): 45–65.
Dai A, Trenberth K E, Qian T, 2004. A global dataset of Palmer Drought Severity Index for 1870–2002: Relationship with soil moisture and effects of surface warming. Journal of Hydrometeorology, 5(6): 1117–1130.
Erazo B, Bourrel L, Frappart F et al., 2018. Validation of satellite estimates (Tropical Rainfall Measuring Mission, TRMM) for rainfall variability over the Pacific slope and coast of Ecuador. Water, 10(2): 213.
Fan K K, Duan L M, Zhang Q et al., 2017. Downscaling analysis of TRMM precipitation based on multiple high-resolution satellite data in the Inner Mongolia, China. Scientia Geographica Sinica, 37(9): 1411–1421. (in Chinese)
Gao J, Tang G, Hong Y, 2017. Similarities and improvements of GPM dual-frequency precipitation radar (DPR) upon TRMM precipitation radar (PR) in global precipitation rate estimation, type classification and vertical profiling. Remote Sensing, 9(11): 1142.
Gao X, Xu Q, Cong J et al., 2015. Temporal and spatial patterns of droughts based on standard precipitation index (SPI) in Liaoning Province in recent 54 a. Ecology and Environmental Sciences, 24(11): 1851–1857. (in Chinese)
Hamed K H, 2008. Trend detection in hydrologic data: The Mann-Kendall trend test under the scaling hypothesis. Journal of Hydrology, 349(3/4): 350–363.
Hao Z C, Tong K, Zhang L L et al., 2011. Applicability analysis of TRMM precipitation estimates in Tibetan Plateau. Hydrology, 31(5): 18–23. (in Chinese)
Huang W H, Yang X G, Li M S et al., 2010. Evolution characteristics of seasonal drought in the south of China during the past 58 years based on standardized precipitation index. Transactions of the Chinese Society of Agricultural Engineering, 26(7): 50–59. (in Chinese)
Li X, He B B, Quan X W et al., 2015. Use of the Standardized Precipitation Evapotranspiration Index (SPEI) to characterize the drying trend in Southwest China from 1982–2012. Remote Sensing, 7(8): 10917–10937.
Li X H, Zhang Q, Ye X C, 2013. Dry/wet conditions monitoring based on TRMM rainfall data and its reliability validation over Poyang Lake basin, China. Water, 5(4): 1848–1864.
Liu S H, Yan D H, Wang H et al., 2016. Evaluation of TRMM 3B42V7 at the basin scale over mainland China. Advances in Water Science, 27(5): 639–651. (in Chinese)
Ma Z Q, Zhou L Q, Yu W et al., 2018. Improving TMPA 3B43 V7 data sets using land-surface characteristics and ground observations on the Qinghai-Tibet Plateau. IEEE Geoscience and Remote Sensing Letters, 15(2): 178–182.
Ma Z Q, Zhou Y, Hu B F et al., 2017. Downscaling annual precipitation with TMPA and land surface characteristics in China. International Journal of Climatology, 37(15): 5107–5119.
McKee T B, 1995. Drought monitoring with multiple time scales, Proceedings of 9th Conference on Applied Climatology, Boston, 1995.
McKee T B, Doesken N J, Kleist J, 1993. The relationship of drought frequency and duration to time scales. In: Proceedings of the 8th Conference on Applied Climatology. American Meteorological Society Boston, MA, 179–183.
McRoberts D B, Nielsen- Gammon J W, 2012. The use of a high-resolution standardized precipitation index for drought monitoring and assessment. Journal of Applied Meteorology and Climatology, 51(1): 68–83.
Mishra A K, Singh V P, 2010. A review of drought concepts. Journal of Hydrology, 391(1/2): 202–216.
Mondol M A H, Ara I, Das S C, 2017. Meteorological drought index mapping in Bangladesh using Standardized Precipitation Index during 1981–2010. Advances in Meteorology, 2017: 1–17.
Naumann G, Barbosa P, Carrao H et al., 2012. Monitoring drought conditions and their uncertainties in Africa using TRMM data. Journal of Applied Meteorology and Climatology, 51(10): 1867–1874.
Palmer W C, 1965. Meteorological drought. Research Paper No.45. Washington, DC: US Department of Commerce. Weather Bureau, 59.
Patel N R, Chopra P, Dadhwal V K, 2007. Analyzing spatial patterns of meteorological drought using standardized precipitation index. Meteorological Applications, 14(4): 329–336.
Santos C A G, Neto R M B, de Araujo Passos J S et al., 2017. Drought assessment using a TRMM-derived standardized precipitation index for the upper Sao Francisco River basin, Brazil. Environmental Monitoring and Assessment, 189(6): 250.
Shan L J, Zhang L P, Song J Y et al., 2018. Characteristics of dry-wet abrupt alternation events in the middle and lower reaches of the Yangtze River Basin and the relationship with ENSO. Journal of Geographical Sciences, 28(8): 1039–1058.
Shi B L, Zhu X Y, Hu Y C et al., 2017. Drought characteristics of Henan province in 1961–2013 based on Standardized Precipitation Evapotranspiration Index. Journal of Geographical Sciences, 27(3): 311–325.
Tao H, Fischer T, Zeng Y et al., 2016. Evaluation of TRMM 3B43 precipitation data for drought monitoring in Jiangsu Province, China. Water, 8(6): 221.
Tosunoglu F, Kisi O, 2017. Trend analysis of maximum hydrologic drought variables using Mann-Kendall and Şen's innovative trend method. River Research and Applications, 33(4): 597–610.
Wu H, Hayes M J, Wilhite D A et al., 2005. The effect of the length of record on the standardized precipitation index calculation. International Journal of Climatology, 25(4): 505–520.
Zambrano F, Wardlow B, Tadesse T et al., 2017. Evaluating satellite-derived long-term historical precipitation datasets for drought monitoring in Chile. Atmospheric Research, 186: 26–42.
Zeng H W, Li L J, 2011. Accuracy validation of TRMM 3B43 data in Lancang river basin. Acta Geographica Sinica, 66(7): 994–1004. (in Chinese)
Zhai L X, Feng Q, 2009. Spatial and temporal pattern of precipitation and drought in Gansu Province, Northwest China. Natural Hazards, 49(1): 1–24.
Zhang M J, He J Y, Wang B L et al., 2013. Extreme drought changes in Southwest China from 1960 to 2009. Journal of Geographical Sciences, 23(1): 3–16.
Zhou Y, Li N, Ji Z H et al., 2013. Temporal and spatial patterns of droughts based on standard precipitation index (SPI) in Inner Mongolia during 1981–2010. Journal of Natural Resources, 28(10): 1694–1706. (in Chinese)
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Foundation: National Key Research and Development Program of China, No.2017YFA0603704; National Natural Science Foundation of China, No.51339004
Author: Chen Shaodan, PhD, specialized in remote sensing and its application in hydrology.
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Chen, S., Zhang, L., Zhang, Y. et al. Evaluation of Tropical Rainfall Measuring Mission (TRMM) satellite precipitation products for drought monitoring over the middle and lower reaches of the Yangtze River Basin, China. J. Geogr. Sci. 30, 53–67 (2020). https://doi.org/10.1007/s11442-020-1714-y
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DOI: https://doi.org/10.1007/s11442-020-1714-y