In this study, to improve the efficiency of the original Palmer Drought Severity Index (PDSI_original), we coupled the Soil and Water Assessment tool (SWAT) and PDSI_original to construct a drought ...index called PDSI_SWAT. The constructed PDSI_SWAT is applied in the Wei River Basin (WRB) of China during 1960–2012. The comparison of the PDSI_SWAT with four other commonly used drought indices reveals the effectiveness of the PDSI_SWAT in describing the drought propagation processes in WRB. The whole WRB exhibits a dry trend, with more significant trends in the northern, southeastern and western WRB than the remaining regions. Furthermore, the drought frequencies show that drought seems to occur more likely in the northern part than the southern part of WRB. The principle component analysis method based on the PDSI_SWAT reveals that the whole basin can be further divided into three distinct sub-regions with different drought variability, i.e., the northern, southeastern and western part. Additionally, these three sub-regions are also consistent with the spatial pattern of drought shown by the drought frequency. The wavelet transform analysis method indicates that the El Niño-Southern Oscillation (ENSO) events have strong impacts on inducing droughts in the WRB. The results of this study could be beneficial for a scientific water resources management and drought assessment in the current study area and also provide a valuable reference for other areas with similar climatic characteristics.
Abstract
Compound extremes of lethal heat stress-heavy precipitation events (CHPEs) seriously threaten social and ecological sustainability, while their evolution and effects at the global scale ...under climate warming remain unclear. Here we develop the global picture of projected changes in CHPEs under various scenarios and investigate their socioeconomic and ecosystem risks combining hazard, exposure, and vulnerability through the composite indicator approach. We find a high percentage of heat stress is followed by heavy precipitation, probably driven by atmospheric conditions. Global average frequency and intensity of CHPEs are projected to increase in the future under high-emission scenarios. Joint return periods of CHPEs are projected to decrease globally, predominantly driven by changes in heat stress extremes. In the long-term future, over half of the population, gross domestic product, and gross primary productivity may face high risk in most regions, with developed regions facing the highest risks under SSP5-8.5 and developing regions facing the highest risks under SSP3-7.0.
The Loess Plateau (LP) of China is famous with soil erosion and water shortage problems. Droughts were frequently occurred in this region, which becomes a critical limiting factor to the ...socioeconomic development, ecology and food production. Therefore, the major motivation of the present study is to investigate the drought characteristics and assess the potential drought risk in this area, which is crucial for drought resistance, water resource management as well as agricultural production. This study analyzes the variations of meteorological drought, characterized by the Standardized Precipitation Evapotranspiration Index (SPEI), and assesses the drought hazards in the LP during 1950–2014. The results show that the northwest of LP is more likely to experience long duration and large severity droughts than the southeast of LP. From the perspective of statistical probability models, the exponential distribution and Gamma distribution can well fit the drought duration and severity, respectively. Compared to Frank and Clayton copula, the Gumbel copula can better model the dependence structure between the drought variables in our study area. Moreover, the estimation of the upper tail dependence coefficient between drought duration and severity also demonstrate that Gumbel copula can provide the best description of the upper tail. The spatial distribution of joint return period under different cases indicates that drought risk in northwestern LP is relatively higher than that in other areas of LP. The results presented in this study can provide some scientific basis for the strategic planning of drought resistance and water resource management in the LP.
Drought risk assessment can identify high‐risk areas and bridge the gap between impacts and adaptation. It is thus vital to investigate changes in drought risk and exposed social economy under ...climate change. Here, the future global meteorological drought risk is projected for the 2021–2100 period under four combined scenarios of Representative Concentration Pathways and Shared Socioeconomic Pathways (SSPs), i.e., SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5. And then the exposed population and Gross Domestic Product (GDP) under high risk are analyzed. Drought risk will further strengthen in the future under SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5, with large increases distributed in South Asia, the Mediterranean, East Asia, Southeast Asia, and Central America. The strongest increasing trends in drought risk are concentrated in equatorial regions including South Asia, West Africa, and Central America. A large percentage of the population and economy are exposed to high drought risk. The exposed population under the highest risk level is the largest under SSP5‐8.5 and the smallest under SSP3‐7.0 for regions in North America, while being the largest under SSP3‐7.0 for other regions. The exposed GDP under the highest risk level is the highest under SSP5‐8.5 and the lowest under SSP3‐7.0, while the disparity among diverse scenarios is larger for the rich regions than the developing ones.
Plain Language Summary
Drought increasingly affects society, economy, and ecosystems as a frequent natural disaster. Drought risk assessment can help understand the extent of drought threat to the human system. Therefore, we projected 0.5° × 0.5° future drought risk for the 2021–2100 period under four scenarios and investigated the exposed population and Gross Domestic Product (GDP) under high risk. We find that high‐risk regions mainly concentrate in South Asia, the Mediterranean, East Asia, Southeast Asia, Central America, eastern North America, North Europe, and West Africa, and global drought risk will increase in the future. The population exposed to high drought risk for South Asia, West Africa, and East Asia is much larger than other regions. GDP exposed to high drought risk is the largest for East and South Asia. Large exposed population and GDP occur under high forcing fossil‐fueled development pathways. Our findings help policymakers develop adaptive disaster prevention measures.
Key Points
Drought risk will increase worldwide in the future, being the highest under SSP5‐8.5 and the lowest under SSP1‐2.6 for most regions
Exposed population under high risk is the largest under SSP5‐8.5 for regions in North America while under SSP3‐7.0 for other regions
Exposed Gross Domestic Product under high risk is significantly higher under SSP5‐8.5 than the other scenarios and the lowest under SSP3‐7.0 for all regions
Drought is a widespread and destructive natural hazard and is projected to occur more frequently and intensely, with more severe impacts in a changing environment. In this study, we used the ...standardized precipitation index (SPI) at various time scales (i.e., 3, 6, and 12 months) to provide an overall view of drought conditions across Sichuan Province, southwestern China, from 1961 to 2016. Then, the relationship between the SPI and the soil moisture anomalies was analyzed. Furthermore, the causes of SPI drought from the perspective of large-scale atmospheric circulation were assessed in the study area. The results showed that most stations with decreasing trends were located in the eastern part of Sichuan Province, while most stations with increasing trends were located in the northwestern part, indicating that the eastern region presented a drying trend, while the northwestern part exhibited a wetting trend. The specific analysis focused on extreme drought indicated an increasing occurrence the probability of extreme drought events, which could induce a high potential drought risk in the study area. The SPI values had a strong relationship with the soil moisture anomalies, and the linear correlation coefficients decreased as the time scale increased. This result indicated that SPI3 (3-month SPI) could be regarded as a good predictor of soil moisture drought. The cross wavelet analysis revealed that the Southern Oscillation Index (SOI) had statistically significant correlations with the SPIs in Sichuan Province. The results of this study are useful for assessing the change in local drought events, which will help reduce the losses caused by drought disasters in Sichuan Province.
The lack of meteorological observation data limits the hydro-climatic analysis and modeling, especially for the ungauged or data-limited regions, while satellite and reanalysis products can provide ...potential data sources in these regions. In this study, three daily products, including two satellite products (Tropic Rainfall Measuring Mission Multi-Satellite Precipitation Analysis, TMPA 3B42 and 3B42RT) and one reanalysis product (China Meteorological Assimilation Driving Datasets for the SWAT Model, CMADS), were used to assess the capacity of hydro-climatic simulation based on the statistical method and hydrological model in Ganjiang River Basin (GRB), a humid basin of southern China. CAMDS, TMPA 3B42 and 3B42RT precipitation were evaluated against ground-based observation based on multiple statistical metrics at different temporal scales. The similar evaluation was carried out for CMADS temperature. Then, eight scenarios were constructed into calibrating the Soil and Water Assessment Tool (SWAT) model and simulating streamflow, to assess their capacity in hydrological simulation. The results showed that CMADS data performed better in precipitation estimation than TMPA 3B42 and 3B42RT at daily and monthly scales, while worse at the annual scale. In addition, CMADS can capture the spatial distribution of precipitation well. Moreover, the CMADS daily temperature data agreed well with observations at meteorological stations. For hydrological simulations, streamflow simulation results driven by eight input scenarios obtained acceptable performance according to model evaluation criteria. Compared with the simulation results, the models driven by ground-based observation precipitation obtained the most accurate streamflow simulation results, followed by CMADS, TMPA 3B42 and 3B42RT precipitation. Besides, CMADS temperature can capture the spatial distribution characteristics well and improve the streamflow simulations. This study provides valuable insights for hydro-climatic application of satellite and reanalysis meteorological products in the ungauged or data-limited regions.
Actual evapotranspiration (Ea) plays a key role in the global water and energy cycles. The accurate quantification of the impacts of different factors on Ea change can help us better understand the ...driving mechanisms of Ea in a changing environment. Climate change and vegetation variations are well known as two main factors that have significant impacts on Ea change. Our study used three differential Budyko-type equations to quantify the contributions of climate change and vegetation variations to Ea change. First, in order to establish the relationship between the parameter n, which usually presents the land surface characteristics in the Budyko-type equations, with basic climatic variables and the Normalized Difference Vegetation Index (NDVI), the stepwise linear regression method has been used. Then, elasticity and contribution analyses were performed to quantify the contributions of different numbers of climatic factors and NDVI to Ea change. The North and South Panjiang basin in China was selected to investigate the efficiency of the modified Budyko-type equations and quantify the impacts of climate change and vegetation variations on Ea change. The empirical formal of the parameter n established in this study can be used to simulate the parameter n and Ea for the study area. The results of the elasticity and contribution analyses suggest that climate change contributed (whose average contribution is 149.6%) more to Ea change than vegetation variation (whose average contribution is −49.4%). Precipitation, NDVI and the maximum temperature are the major drivers of Ea change, while the minimum temperature and wind speed contribute the least to Ea change.
Affected by global climate change and rapid socio-economic development, China faces serious water security issues, especially in terms of water shortages, flood disasters, and water-related ...ecological and environmental problems ...
Based on the daily precipitation data of 27 meteorological stations from 1960 to 2009 in the Huaihe River Basin, spatio-temporal trend and statistical distribution of extreme precipitation events in ...this area are analyzed. Annual maximum series （AM） and peak over threshold series （POT） are selected to simulate the probability distribution of extreme pre- cipitation. The results show that positive trend of annual maximum precipitation is detected at most of used stations, only a small number of stations are found to depict a negative trend during the past five decades, and none of the positive or negative trend is significant. The maximum precipitation event almost occurred in the flooding period during the 1960s and 1970s. By the L-moments method, the parameters of three extreme distributions, i.e., Gen- eralized extreme value distribution （GEV）, Generalized Pareto distribution （GP） and Gamma distribution are estimated. From the results of goodness of fit test and Kolmogorov-Smirnov （K-S） test, AM series can be better fitted by GEV model and POT series can be better fitted by GP model. By the comparison of the precipitation amounts under different return levels, it can be found that the values obtained from POT series are a little larger than the values from AM series, and they can better simulate the observed values in the Huaihe River Basin.
Drought is one of the most detrimental natural hazards in Yellow River Basin (YRB). In this research, spatio-temporal variation and statistical characteristic of drought in YRB is studied by using ...dry spell. Two extreme series, including annual maximum series (AMS) and partial duration series (PDS), are used and simulated with generalized extreme value (GEV), generalized Pareto (GP), and Pearson type III (PE3) distributions. The results show that the northern part is drier than the southern part of YRB. Besides, the maximum dry spell usually starts in October, November, and December. According to the trend analysis, mean maximum length of dry spell (MxDS) shows a negative trend in most stations. From the L-moments and Kolmogorov–Smirnov test method, it can be found that GEV model can better fit AMS while GP and PE3 can better fit PDS. Moreover, the quantiles from optimal model of AMS and PDS depict a similar distribution with values increases from south to north. The spatial distribution of scale and location parameters of GEV model for AMS shows a south-to-north gradient, while the distribution of shape parameter is a little irregularity. Furthermore, based on the linear correlation analysis, there is an evident linear relation between location and scale parameters with mean and standard variation of MxDS, respectively.
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