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

Droughts occur frequently during summer maize growth in the Huaihe River Basin, China. Identifying the critical precipitation thresholds that can lead to drought is conducive to drought monitoring and the creation of early warning systems. Based on meteorological data from 66 stations from 1961 to 2015 in areas of the Bengbu Sluice in the Huaihe River Basin (BHR), and using correlation analysis between maize climatic yield and water deficit index at different growth stages, the critical period of water deficit in summer maize growth was determined. Twenty-eight types of distribution functions were used to fit the precipitation sequence during the critical period for water during summer maize growth. By applying Akaike Information Criterion and Bayesian Information Criterion, an optimal probability distribution model was established. The precipitation thresholds (Define R as the precipitation thresholds) for each level of drought for summer maize were then quantified based on the precipitation probability quantile method, and the rationality of the index was verified. The results were as follows: (1) The stage of tassel appearance-maturity was the critical period for water during summer maize growth. (2) There was a significant difference in the optimal probability distribution model at the 66 typical sites in the precipitation sequence during the critical period of water during summer maize growth. (3) In this paper, we identified a rapid and effective method for assessing agricultural drought in summer maize, which is based on the precipitation thresholds and dividing the different levels of drought. The precipitation thresholds of a drought disaster for summer maize at the 66 sites varied greatly from region to region. By using the Thiessen polygon method, the precipitation thresholds of a drought disaster during the critical water period during summer maize growth in the Huaihe River Basin were mild drought: 139 ≤ R < 169 mm, moderate drought: 108 ≤ R <139 mm, severe drought: 81 ≤ R < 108 mm, and extreme drought: R < 81 mm.

Section: Thiessen Polygonmentioning

confidence: 99%

Precipitation Thresholds of Drought Disaster for Maize in Areas in Front of Bengbu Sluice, Huaihe River Basin, China

Gao

2018

“…For example, for the purpose of providing more robust integrated water management insights under the implementation of the European Water Framework Directive, drought assessment was suggested on the basis of the basin-scale approach and information [13]. Since hydro-metrological conditions used for drought evaluations are based on at-site observations, simply using the mean of at-site drought characteristics to represent basin-scale droughts would reduce drought severity due to the strong asynchronous evolutions of droughts at sites in a large basin [14]. Therefore, it is necessary to divide a heterogeneous region into several homogeneous sub-regions.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Evolution of Droughts and Their Teleconnections with Large-Scale Climate Indices over Guizhou Province in Southwest China

Xiao

Chen

Zhang

et al. 2019

The spatiotemporal evolution of meteorological droughts in Guizhou Province, Southwest China is analyzed based on a new set of the Standardized Precipitation Index series that mainly includes drought events that occurred from 1961 to 2004 at 81 meteorological stations. The cluster analysis shows that the study region can be classified into six homogeneous sub-regions where the drought characteristics and their temporal evolutions are quite different. The trend test and periodicity analysis indicate that Guizhou Province experienced a drier trend, which was most significant in the western parts of the region. It was found that the intensified drought severity was not always coincident with the drier trend but relied on the occurrence of extreme drought events. The trends of drier climate and drought severity were highly coincident with the temporal evolution of the drought periodicities, which were shortened from 1–4 years to less than one year. The shortened drought periodicity was found to be associated principally with a shift of the large-scale dominant climate indices from the North Atlantic Oscillation to the Indian Ocean Dipole after the late 1970s, and variations of the extreme drought events were mostly related to NINO34 in the study region.

“…For instance, from 1972 to 2004, the warming increased global dry areas by 20% to 38% [15]. The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report [19] proposed a continuous increase in global mean surface air temperature during the 21st century owing to the increase of anthropogenic greenhouse gas concentration [20], indicating an increase in drought frequency, severity and spatial extension in future.Drought can be characterized by many indices such as the Palmer Drought Severity Index (PDSI), Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) [21][22][23]. PDSI and SPI have a wide range of applications, but each of them has its limitations.…”

mentioning

confidence: 99%

“…Drought can be characterized by many indices such as the Palmer Drought Severity Index (PDSI), Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) [21][22][23]. PDSI and SPI have a wide range of applications, but each of them has its limitations.…”

mentioning

confidence: 99%

Drought Characteristics and Its Response to the Global Climate Variability in the Yangtze River Basin, China

Huang

Fan

2018

The frequent occurrence of drought events in humid and semi-humid regions is closely related to the global climate variability (GCV). In this study, the Standard Precipitation Evapotranspiration Index (SPEI) was taken as an index to investigate the drought in the Yangtze River Basin (YRB), a typical humid and semi-humid region in China. Furthermore, nine GCV indices, such as North Atlantic Oscillation (NAO) were taken to characterize the GCV. Correlation analysis and a joint probability distribution model were used to explore the relationship between the drought events and the GCV. The results demonstrated that there were six significant spatiotemporal modes revealed by SPEI3 (i.e., seasonal drought), which were consistent with the distribution of the main sub basins in the YRB, indicating a heterogeneity of drought regime. However, the SPEI12 (i.e., annual drought) can only reveal five modes. Precipitation Indices and El Niño/Southern Oscillation (ENSO) Indices were more closely related to the drought events. A causal relationship existed between ENSO precipitation index (ESPI), NAO, East Central Tropical Pacific Sea Surface Temperature (Nino3.4) and Northern Oscillation Index (NOI) and drought in the YRB, respectively. Drought events were most sensitive to the low NAO and high NOI events. This study shows a great significance for the understanding of spatiotemporal characteristics of meteorological drought and will provide a reference for the further formulation of water resources policy and the prevention of drought disasters.tropical Pacific phenomenon worldwide. A number of studies have confirmed that there were connections between ENSO and regional climate extremes like floods and droughts [14]. A concern exists that the ongoing global warming may increase the severity of droughts and many studies have shown that drought severity increases with temperature rise [10,[15][16][17][18]. For instance, from 1972 to 2004, the warming increased global dry areas by 20% to 38% [15]. The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report [19] proposed a continuous increase in global mean surface air temperature during the 21st century owing to the increase of anthropogenic greenhouse gas concentration [20], indicating an increase in drought frequency, severity and spatial extension in future.Drought can be characterized by many indices such as the Palmer Drought Severity Index (PDSI), Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) [21][22][23]. PDSI and SPI have a wide range of applications, but each of them has its limitations. PDSI takes account of changes in surface water balance so that it is suitable for the measurement of long-term drought conditions, but the acquisition is difficult because the calculation process is complex, and the time scale is limited [24]. SPI takes precipitation as a factor. Although its calculation method is simple and time scale is flexible, it does not consider temperature, evapotranspiration and other influe...