Daily extreme precipitation indices and their impacts on rice yield—A case study over the tropical island in China
Frequent occurrences of extreme precipitation events have significant impacts on agricultural production. Tropical agriculture has been playing an important role in national economy in China. A precise understanding of variability in extreme precipitation indices and their impacts on crop yields are of great value for farmers and policy makers at county level, particularly in tropical China where almost all agriculture is rainfed. This research has studied observed trends in extreme precipitation indices (a total of 10) during 1988–2013 over Hainan island, tropical China. Mann–Kendall nonparametric test was adopted for trend detection and the results showed that most of precipitation indices showed increasing trend. Since rice is the most important staple food in Hainan island, the impacts of extreme precipitation indices on rice yields were also analyzed through simple correlations. In general, the rainy days and rain intensity in late rice growing season showed increasing trend over Hainan island. The rice yield presented ninth-degree polynomial technological trend at all stations and increasing trend for early rice yield. Late rice yield showed a decreasing trend in some parts of Hainan island. Spearman rank correlation coefficient indicated that the correlation was more pronounced between extreme precipitation indices and yields at Haikou site for early rice, and Haikou, Sanya, and Qionghai stations for late rice, respectively. Further results also indicated that there were statistically significant positive trends of R10 and R20 (number of days with precipitation ≥10 mm and precipitation ≥20 mm, respectively) from July to November at Haikou (located in north of Hainan island), and this positive trend may be a disadvantage for late rice yield. The cut-off value of extreme precipitation indices and its correlation with rice yield anomaly indices for Hainan island provided a foundation for vulnerability assessment as well as a contribution to set up contingency program under potential climate change conditions.
This research was funded by the Natural Science Foundation Project of Hainan (20154184) and Research and Demonstration of Key Technology for Cropland Improving in Hainan (HNGDzy201503). This study is also supported by the Key Laboratory of Practical Research on Tropical Crops Information Technology in Hainan, China. We are very grateful to the National Meteorological Information Center (NMIC) of China Meteorological Administration (CMA) for data offering and to the reviewers for their constructive comments and thoughtful suggestions.
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