Figure 1 - uploaded by Meixiu Yu
Content may be subject to copyright.
Source publication
Drought in China is a recurring phenomenon that becomes one of the most
damaging climate-related hazards to impact natural habitats, ecosystems,
and many economic and social sectors. Thus, it is of critical
significance to investigate the variation patterns of droughts over
China with long-term data time series. In recent years, meteorologists
have...
Context in source publication
Context 1
... the purposes of this study, China is divided into three parts: Northern China, Southern China, and the Tibetan plateau. Northern China consists of Northeast (NE), North (N), eastern Northwest (ENW), and western Northwest China (WNW); Southern China consists of Southwest (SW), East (E), and South (S) China; the Tibetan plateau is marked by Tibet (see Figure 1). It should also be noted that due to a shortage of data in western Tibet, the time series can only represent the drought variations of eastern Tibet. ...
Similar publications
The trend, severity, and duration of drought in the eastern fringe of the Tibetan Plateau (EFTP) have been investigated using the Mann-Kendall (M-K) trend test, standardized precipitation index (SPI), and generalized extreme value (GEV), using data obtained from 438 rainfall stations and reanalysis datasets for the period 1961–2014. A recent drough...
W pracy przedstawiono problem występowania susz meteorologicznych na rolniczym obszarze
zlewni Strugi Toruńskiej. Analizę zmienności miesięcznych susz meteorologicznych w latach 1951–
2010 przeprowadzono na podstawie danych ze stacji Zintegrowanego Monitoringu Środowiska Przyrodniczego w Koniczynce (Pojezierze Chełmińskie). Jest to rejon charaktery...
Drought is one of the adverse impacts of climate crisis and it operates on many different timescales. Droughts are occurring more often each year in different areas of India. Many negative effects on the environment, society, and the economy can result from drought. By determining the severity and length of the drought, drought assessment may be us...
In this study, 91 years (1923-2013) monthly rainfall dataset of Almora district of Uttarakhand
was analyzed with the help of different drought indices namely, Dependable Precipitation Index (DPI),
Precipitation Departure Index (PDI), Standard Index of Anomaly Precipitation (SIAP) and Standardized
Precipitation Index (SPI). In addition to this, the...
Near-real-time drought monitoring can provide decision-makers with valuable
information for use in several areas, such as water resources management, or
international aid. One of the main constrains of assessing the current
drought situation is associated with the lack of reliable sources of observed
precipitation on a global scale available in nea...
Citations
... The SPEI incorporates the potential evapotranspiration (PET) as a driving factor of water availability and the calculation is similar to that of SPI, and it has been claimed to have combined the advantages of the two previous indices: the PDSI and the SPI [15,20,28,29]. The SPEI has been widely used in recent years, and the performance has been proven to be satisfactory in diverse studies [30][31][32][33][34][35][36][37]. ...
Jiangsu is an important agricultural province in China. Winter wheat, as the second major grain crop in the province, is greatly affected by moisture variations. The objective of this study was to investigate whether there were significant trends in changes in the moisture conditions during wheat growing seasons over the past decades and how the wheat yields responded to different moisture levels by means of a popular drought index, the Standardized Precipitation Evapotranspiration Index (SPEI). The study started with a trend analysis and quantification of the moisture conditions with the Mann-Kendall test and Sen’s Slope method, respectively. Then, correlation analysis was carried out to determine the relationship between de-trended wheat yields and multi-scalar SPEI. Finally, a multivariate panel regression model was established to reveal the quantitative yield responses to moisture variations. The results showed that the moisture conditions in Jiangsu were generally at a normal level, but this century appeared slightly drier in because of the relatively high temperatures. There was a significant correlation between short time scale SPEI values and wheat yields. Among the three critical stages of wheat development, the SPEI values in the late growth stage (April-June) had a closer linkage to the yields than in the seedling stage (October-November) and the over-wintering stage (December-February). Moreover, the yield responses displayed an asymmetric characteristic, namely, moisture excess led to higher yield losses compared to moisture deficit in this region. The maximum yield increment could be obtained under the moisture level of slight drought according to the 3-month SPEI at the late growth stage, while extreme wetting resulted in the most severe yield losses. The moisture conditions in the first 15 years of the 21st century were more favorable than in the last 20 years of the 20th century for wheat production in Jiangsu.
... Stott et al., 2004; Elsner et al., 2008; Min et al., 71 2011; Sheffield et al., 2012; Dai, 2004 Dai, , 2013 Trenberth et al., 2013; IPCC, 2014). Among all 72 the extremes, droughts are believed to be the most damaging natural disasters [1995; Romm, 2011], which affects more people 74 than any other forms of devastating meteorological hazards (Wilhite, 2000; Yu et al., 2014Barriopedro et al., 2012). Consequently, numerous studies have focused on the drought 79 variations and its adverse impacts in the background of changing and even exacerbating 80 climate on both global and regional scales (Palmer, 1965; Mckee et al., 1993; Wells et al., 2004; 81 Vicente-Serrano et al., 2010; Vergni and Todisco, 2011; Sheffield et al., 2012; Choi et al., 82 2013; Dai, 2011 Dai, , 2013 Kogan et al., 2013; Li et al., 2013; Trenberth et al., 2013; Zhang and 83 Jia, 2013; Qin et al., 2015b). ...
... For example, Dai (2013) stated that drought would increase under 84 the global warming based on instrumental observations and numerical simulations. However, 85 Trenberth et al. (2013) 92 Huang et al., 2006; Qian et al., 2011; Lü et al., 2012; Yu et al., 2014]. For 93 instance, Yu et al. (2014) found that severe and extreme droughts have become more serious 94 since late 1990s throughout China (with an increase of dry area by ~3.72% per decade) based 95 on Standardized Precipitation-Evapotranspiration Index (SPEI). ...
... However, 85 Trenberth et al. (2013) 92 Huang et al., 2006; Qian et al., 2011; Lü et al., 2012; Yu et al., 2014]. For 93 instance, Yu et al. (2014) found that severe and extreme droughts have become more serious 94 since late 1990s throughout China (with an increase of dry area by ~3.72% per decade) based 95 on Standardized Precipitation-Evapotranspiration Index (SPEI). identified 96 ...
Under the exacerbation of climate change, climate extreme events, especially for drought, happened frequently and intensively across the globe with greater spatial differences. We used the Standardized Precipitation-Evapotranspiration Index (SPEI) computed from the routine meteorological observations at 269 sites in Southwest China (SWC) to study the drought characteristics (e.g., extent, duration and intensity) and their decadal variations during 1971-2012. It was revealed that the drought, in responses to the coupling between decadal precipitation and potential evapotranspiration (PET) anomalies, differed among regions and periods. For the entire SWC, droughts in 1970s and 2000s+ was generally stronger than in 1980s and 1990s with respect to their spatial extent, duration and intensity, especially in 2000s+. It was well-known that drought was closely related with a lack of precipitation; however, the impact of atmospheric demand of evaporation [reflected by PET here] on drought (e.g., duration and intensity) was rarely paid enough attentions. To that end, a spatial multi-linear regression approach was proposed in this study for quantifying the contributions of decadal PET and precipitation variations to drought duration and intensity. We have found that the contributions of decadal PET anomalies to drought duration and intensity could exceed those of precipitation, e.g., during 1980s and 1990s in SWC. Additionally, despite the strongest droughts in 2000s+, it was suggested that PET could exert comparable impacts on drought anomalies as precipitation. All these findings implied that PET plays a critical role in drought event, which acts to amplify drought duration and intensity. To sum up, this study stressed the need for enough attentions for PET processes in drought studies.
This study uses remote sensing and GIS techniques to examine the intensity and dynamics of land use/cover change and environmental indices across a four-decade period in the Chingola district of Zambia, from 1972 to 2020 using five classification stages (1972, 1992, 2001, 2013, and 2020). A total of 10 key climate change detection monitoring indices were generated using RClimDex to examine the implications of land degradation on the bioclimatic factors from 1983 to 2020. The findings revealed a significant expansion in Built-ups (7.3%/year), farmlands (3.18%/year), and mining areas (0.82%/year) at the expense of natural resources. The highest human pressure was exerted on Savannah woodlands (−0.78), through agriculture (0.76) and infrastructure development (0.44) between 1992 and 2001.The analysis of the bioclimatic indices revealed a significant decline in rainfall quantity and intensity, and a rising in temperature (warmer days and nights). The Annual rainfall has decreased by −3.25%, while the potential evapotranspiration has increased by 0.04% from 1983 to 2020, resulting in an Aridity Index of 0.60 and a moisture deficit index of −0.42. To offset agriculture’s propensity to spatially expand and further encroach into savannah woodlands and forests, urban containment policies and programs that stimulate agricultural intensification are needed to reduce urban sprawl and protect the city’s remaining forestlands.
This study was to determine the spatiotemporal characteristics of historical and projected drought events throughout Isiolo County, Kenya, through using self-calibrating Palmer drought severity index (scPDSI). The scPDSI is a complex and robust drought index that applies the water balance model by incorporating the role played by evapotranspiration and soil properties on drought analysis therefore making it appropriate to identify the linkages between meteorological, agricultural and hydrological droughts. The historical scPDSI was computed at a monthly timescale using a 39-year long monthly mean precipitation data from Climate Hazard Group Infrared Precipitation with Station (CHIRPS) and monthly average temperature data from the Climate Research Unit (CRU). The climatological (1950-1996) available water holding capacity (AWHC) of the soil was obtained from Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC) for biochemical dynamics at a spatial resolution of 1 o x 1 o . The projected scPDSI under Representative Concentration Pathways (RCPs) was computed using bias corrected monthly temperature and precipitation model output data from Coordinated Regional Climate Downscaling Experiment (CORDEX). The datasets were extracted for ten grid points in the County. The scPDSI was used to assess the historical and projected duration, severity, and intensity of droughts. The major significant historical and projected drought events and their characteristics were clearly identified using the run theory. ScPDSI runs have shown that more severe drought events dominated the period between 1980 and 2000. ScPDSI had the longest dry event duration of 61 months and a severity of 126.412 with adverse effects on the eastern locations. The projected drought events identified Mar 2046 –Mar 2048 under RCP4.5 to be the most severe drought lasting for 25 months with severity of 59.292 while under RCP8.5 run Nov 2042 – Nov 2046 is identified as the most severe, 114.362 with the duration of water stress anticipated to last for 49 months. To examine the spatial variability of the drought events in the County, the Empirical Orthogonal Analysis (EOF) was applied to the historical and projected scPDSI time series. The EOF results indicated that the two leading eigen vectors accounted for over 85% of the spatial variability for both historical and projected droughts under the RCPs. Subsequently, the Mann-Kendall (MK) test was applied to the projected scPDSI, temperature and precipitation timeseries in order to determine the local expected drought trends. The MK test of the identified significant increase in trend for temperatures under RCP8.5 and precipitation under RCP4.5 towards the end of the last decade under the study period considered. Both scenarios showed a decline in trends of drought events in Isiolo County from 2020-2050.
In the context of sustainable agricultural management, drought monitoring plays a crucial role assessing the vulnerability of agriculture to drought occurrence. Drought events are very frequent in the Iberian Peninsula (and in Portugal in particular) and an increase of frequency of these extreme events are expected in a very near future. Therefore, the quantitative assessment of the natural ecosystems vulnerability to drought is still very challenging, mainly due to the difficulties of having a common definition of vulnerability. Consequently, several methods have been proposed to assess agricultural vulnerability. In this work, a principal component analysis (PCA) was performed based on the components which characterize the Exposure, Sensitivity and Adaptative Capacity of the agricultural system to drought events with the aim of generating maps of vulnerability of agriculture to drought in Portugal. Several datasets were used to describe these components, namely drought indicators, vegetation indexes and soil characterization variables. A comparison between the PCA-based method and a subjective non-automatic categorical method using the same indicators was performed. Results show that both methods identify Minho and Alentejo as regions of low and extreme vulnerability, respectively. The results are very similar between the two methods, with small differences on certain vulnerability class. However, the PCA method has some advantages over the categorical method, namely the ability to identify the sign of the indicators, not having to use the indicator-component subjective relationship, nor calculating weights. Furthermore, the PCA method is fully statistical and presents results according to a prior knowledge of the region and the data used.
