SPI Based Meteorological Drought Assessment over a Humid Basin: Effects of Processing Schemes

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.