Characteristic of Drought and Flood in the Dian-Qian-Gui Karst Areas Based on TRMM-Z Index

Abstract

Abstract. In order to study the spatial and temporal variation of characteristics of drought and flood in Dian-Qian-Gui Karst Areas of China, TRMM 3B43 precipitation data from 1998 to 2017 and 72 rain gauge station data from 1998 to 2012 were used to verify the TRMM 3B43 data on monthly scale by correlation coefficient and relative deviation. The TRMM-Z index was taken as an index of drought and flood to quantitatively analyze the drought and flood characteristics. The results show that: (1) there was a significant positive correlation between TRMM 3B43 precipitation data and the measured data of meteorological stations on the monthly scale, with a correlation coefficient of 0.92, passing the significance test of 0.01 level. The calculated result of relative Bias is -0.058, indicating that TRMM 3B43 precipitation is slightly higher than the actual precipitation. (2) From 1998 to 2017, the TRMM-Z index in the research area fluctuated between −1.160 and 1.678, among which the Z index in July 1999 reached the maximum value of 1.678, and in February 2010 the Z index reached the minimum value of −1.160. (3) During the past 20 years, the flood months in the study areas were 47 months, accounting for 19.58% of the study time, and 40 months were drought months, accounting for 16.67% of the study time. Floods mainly occurred in the summer with abundant rainfall, while droughts mainly occurred in the winter with less rainfall. (4) Taking 2008–2009 as typical representative of drought and flood, the spatial variation of drought and flood were researched.

Spatial and Temporal Dynamics of Drought and Waterlogging in Karst Mountains in Southwest China

“…The status fluctuated quite often (seven mutation in 61 years, as seen in Figure 2b) and was more obvious during the 1997-2000 period. Similar studies were carried out by Wang et al [19] (based on monthly analysis for 51 years) and Liu et al [10] (based on daily analysis for 20 years) in southwest China, and results showed a high frequency of drought and fluctuation at the beginning of the 21st century. Some characteristics of DW were scale-dependent (time and space) in this study.…”

“…Karst drought and flood studies are often based on data from meteorological stations [18], climatic datasets [19], and remote sensing images [20]. Multiple indexes are the most common methods used to monitor drought and flood events, e.g., SPI (standardized precipitation index) [18,21], SWAP (standardized weighted average of the precipitation index) [22], ETI (evapotranspiration index) [23], CDI (composite drought index) [24], China-Z index [19], etc.…”

“…Karst drought and flood studies are often based on data from meteorological stations [18], climatic datasets [19], and remote sensing images [20]. Multiple indexes are the most common methods used to monitor drought and flood events, e.g., SPI (standardized precipitation index) [18,21], SWAP (standardized weighted average of the precipitation index) [22], ETI (evapotranspiration index) [23], CDI (composite drought index) [24], China-Z index [19], etc. Systemic and hydrological models are also applied in karst aquifers without accurate knowledge regarding the physics and detailed geometry of the karst system, i.e., neural network models [25] and SWAT (the soil and water assessment tool) [7,26].…”

Temporal and Spatial Distribution Characteristics of Drought and Flood Considering the Influence of Underlying Surface in Hainan Island, Tropical Areas of China

“…Assuming that the precipitation series follow the Pearson III curve, the seasonal precipitation series are standardized, the probability density function is transformed into a standard normal distribution, and the new variable is the Z value. According to the size of the Z index, the drought and ood level of each grid point can be judged (Wang et al, 2020b).…”