2019
DOI: 10.3390/w11122455
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Drought Trend Analysis Based on the Standardized Precipitation–Evapotranspiration Index Using NASA’s Earth Exchange Global Daily Downscaled Projections, High Spatial Resolution Coupled Model Intercomparison Project Phase 5 Projections, and Assessment of Potential Impacts on China’s Crop Yield in the 21st Century

Abstract: Drought is among the costliest natural disasters on both ecosystems and agroeconomics in China. However, most previous studies have used coarse resolution data or simply stopped short of investigating drought projection and its impact on crop yield. Motivated by the newly released higher-resolution climate projection dataset and the crucial need to assess the impact of climate change on agricultural production, the overarching goal of this study was to systematically and comprehensively predict future droughts… Show more

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Cited by 6 publications
(5 citation statements)
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“…This finding is consistent with the previous study [49], which indicated that there was more rainfall in the south than that in the north, while there were less precipitation days in the south than in the north in Guizhou province. This finding is consistent with the previous study [50], which indicated that there was more rainfall in the south than in the north, while there were less precipitation days in the south than in the north in Guizhou province. The variable "number of Dnp" exhibited different spatial patterns in different seasons.…”
Section: The Relationship Analysissupporting
confidence: 93%
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“…This finding is consistent with the previous study [49], which indicated that there was more rainfall in the south than that in the north, while there were less precipitation days in the south than in the north in Guizhou province. This finding is consistent with the previous study [50], which indicated that there was more rainfall in the south than in the north, while there were less precipitation days in the south than in the north in Guizhou province. The variable "number of Dnp" exhibited different spatial patterns in different seasons.…”
Section: The Relationship Analysissupporting
confidence: 93%
“…The aggravation of drought had seriously affected agricultural production during these two periods. According to data, the seasonal distribution of drought tends to be severe, and it will become drier in winter and spring in China, affecting crop growth and restricting agricultural production [24,50], especially in southwestern China, where 24% of agricultural areas are affected by drought [51,52]. In Northeast China, drought is accompanied by the spring maize growth period, and long-term drought will make it impossible to recover the phys- On the decadal scale, there were longest Dnp twice in 1960s with an average of 27 days each time; 5 times in 1980s with an average period of also 27 days each time; 3 times in 1990s with an average of 32 days; since 2000s, there was 9 times, with an average of 35.6 days; the average period was up to 37 days each time since 2010s.…”
Section: Temporal and Spatial Variation Of Annual Longest Dnpmentioning
confidence: 99%
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“…More importantly, the water budget and energy exchange in the region have a considerable impact on the intensity of the Asian monsoon and high pressure [35,36]. Guo et al concluded, by studying the trend of the evapotranspiration index of standard precipitation in China, that winter and spring in the TP will become drier in the 21st century [37]. Ye et al further found that the frequency of extreme drought events in the Qaidam Basin is the highest (3-6 times) in the TP [38].…”
Section: Introductionmentioning
confidence: 99%
“…For instance, [22] investigated the future changes of precipitation at the local scale over China using NEX-GDDP and reported a "certain" reliability over the Han River, emphasizing the potential usefulness of this dataset for climate change impact studies at watershed scales. The author of [23] reported that, although NEX-GDDP offers potential improvements in reproducing monthly temperature and precipitation over China, it still exhibits region-dependent systematic errors. The author of [24] reported this dataset to be well in agreement with the observations on a monthly basis over southeast Asia; however, they also found significant biases, which were predominantly region-specific.…”
Section: Introductionmentioning
confidence: 99%