Abstract
Meteorological drought monitoring is important for drought early warning and disaster prevention. Regional meteorological drought can be evaluated and analyzed with standardized precipitation index (SPI). Two main processing schemes are frequently adopted: (1) mean of all SPI calculated from precipitation at individual stations (SPI-mean); and (2) SPI calculated from all-station averaged precipitation (precipitation-mean). It yet remains unclear if two processing schemes could make difference in drought assessment, which is of significance to reliable drought monitoring. Taking the Poyang Lake Basin with monthly precipitation recorded by 13 national stations for 1957–2014, this study examined two processing schemes. The precipitation mean and SPI mean were respectively calculated with the Thiessen Polygon weighting approach. Our results showed that the two SPI series individually constructed from two schemes had similar features and monitoring trends of regional meteorological droughts. Both SPI series had a significantly positive correlation (p < 0.005) with the number of precipitation stations. The precipitation-mean scheme reduced the extent of precipitation extremes and made the precipitation data more clustered in some certain, it made less precipitation deviate from the precipitation-mean series farther when less precipitation occurred universally, which would probably change the drought levels. Alternatively, the SPI-mean scheme accurately highlighted the extremes especially for those with wide spatial distribution over the region. Therefore, for regional meteorological drought monitoring, the SPI-mean scheme is recommended for its more suitable assessment of historical droughts.
Highlights
As a hydroclimatic hazard, drought poses a serious threat to society, economy, ecosystem and other sectors [1,2]
This study investigated the effects of two different processing schemes on meteorological drought assessment with long-term precipitation data in the Poyang Lake Basin for 1957–2014
In the study of Dash et al [41], we noticed that the standardized precipitation index (SPI) series from selected individual stations had barely extreme SPI values (SPI > 3.0 or SPI < −3.0), whereas the extreme values were found frequently in SPI series obtained from the regional average of observed data in the research
Summary
Drought poses a serious threat to society, economy, ecosystem and other sectors [1,2]. Quantitative assessment of drought features and its development is essential to understanding different drought types at scales from the local to the global [6]. There is currently no general consensus on the definition of drought [4,6,7,8,9,10,11,12], which has been a stumbling block in drought monitoring and analysis. The American Meteorological Society [13] summarized dozens of drought definitions into four categories: meteorological, agricultural, hydrological and socioeconomic droughts. The four categories are associated with different components of hydrologic cycle [14]. Precipitation is the driving and critical factor in the hydrologic cycle. The absence or reduction of precipitation instigates meteorological drought.
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