Standardized Precipitation Evapotranspiration Index Research Articles

Dynamics of solar-induced chlorophyll fluorescence (SIF) and its response to meteorological drought in the Yellow River Basin

Solar-induced chlorophyll fluorescence (SIF) has been used since its discovery to characterize vegetation photosynthesis and is an effective tool for monitoring vegetation dynamics. Its response to meteorological drought enhances our comprehension of the ecological consequences and adaptive mechanisms of plants facing water scarcity, informing more efficient resource management and efforts in mitigating climate change. This study investigates the spatial and temporal patterns of SIF and examines how vegetation SIF in the Yellow River Basin (YRB) responds to meteorological drought. The findings reveal a gradual southeast-to-northwest decline in SIF across the Yellow River Basin, with an overall increase—from 0.1083 W m-2μm−1sr−1 in 2001 to 0.1468 W m-2μm−1sr−1 in 2019. Approximately 96% of the YRB manifests an upward SIF trend, with 75% of these areas reaching statistical significance. The Standardized Precipitation Evapotranspiration Index (SPEI) at a time scale of 4 months (The SPEI-4), based on the Liang-Kleeman information flow method, is identified as the most suitable drought index, adeptly characterizing the causal relationship influencing SIF variations. As drought intensified, the SPEI-4 index markedly deviated from the baseline, resulting in a decrease in SIF values to their lowest value; subsequently, as drought lessened, it gravitated towards the baseline, and SIF values began to gradually increase, eventually recovering to near their annual maximum. The key finding is that the variability of SIF with SPEI is relatively pronounced in the early growing season, with forests demonstrating superior resilience compared to grasslands and croplands. The responsiveness of vegetation SIF to SPEI can facilitate the establishment of effective drought early warning systems and promote the rational planning of water resources, thereby mitigating the impacts of climate change.

Characteristics of extreme meteorological droughts over the Brazilian Pantanal throughout the 21st century

The Brazilian Pantanal is a remarkable ecosystem, encompassing vital aspects such as fish, fruit, and grain production, greenhouse gas emission regulation, temperature and precipitation modulation, and groundwater recharge. However, 2019 and 2020 experienced prolonged and severe drought that profoundly impacted the Pantanal region. Although these impacts are still under review, their effects on wildlife, vegetation, and the local population are undeniable. To enhance our understanding of the magnitude and consequences of the 2019/2020 drought, the present study conducted a comprehensive evaluation of drought occurrences in the Pantanal biome. Utilizing two well-established drought indices, the standard precipitation index (SPI) and the standard precipitation evapotranspiration index (SPEI), we analyzed the available observational data provided by the Climate Research Unit (CRU). Additionally, we endeavored to project droughts throughout the 21st century, thereby facilitating the visualization of potential reoccurrences of hazardous events in the Pantanal area. Two regional climate model (RCM) ensembles, the Eta ensemble (E1) and CORDEX ensemble (E2), along with representative concentration pathways (RCP4.5 and RCP8.5 scenarios) were used to project the severity of droughts in the Brazilian Pantanal until 2098/2099. The findings indicate that the hydrological year of 2019/2020 was the driest on record in the Pantanal over the past 80 years. The E1 ensemble did not project such an extreme event, whereas the E2 ensemble forecasted extreme droughts before the 2040s under the RCP4.5 and RCP8.5 scenarios. Using the SPEI, both ensembles showed similar results, with extreme droughts projected toward the end of the 21st century. Notably, the SPI demonstrated effectiveness in detecting short-term droughts, while the SPEI was more efficient for long-term assessments, projecting extreme drought events for the last two decades. The SPEI, employed with the Eta and CORDEX ensembles, can provide valuable insights into drought projections. Moreover, the potential recurrence of extreme droughts, characterized by significant below-average precipitation spanning vast areas throughout the hydrological year, poses a severe threat to the Pantanal biome in this century.

Drought Risk Assessment of Winter Wheat at Different Growth Stages in Huang-Huai-Hai Plain Based on Nonstationary Standardized Precipitation Evapotranspiration Index and Crop Coefficient

Soil moisture plays a crucial role in determining the yield of winter wheat. The Huang-Huai-Hai (HHH) Plain is the main growing area of winter wheat in China, and frequent occurrence of drought seriously restricts regional agricultural development. Hence, a daily-scale Non-stationary Standardized Precipitation Evapotranspiration Index (NSPEI), based on winter wheat crop coefficient (Kc), was developed in the present study to evaluate the impact of drought characteristics on winter wheat in different growth stages. Results showed that the water demand for winter wheat decreased with the increase in latitude, and the water shortage was affected by effective precipitation, showing a decreasing trend from the middle to both sides in the HHH Plain. Water demand and water shortage showed an increasing trend at the jointing stage and heading stage, while other growth stages showed a decreasing trend. The spatial distributions of drought duration and intensity were consistent, which were higher in the northern region than in the southern region. Moreover, the water shortage and drought intensity at the jointing stage and heading stage showed an increasing trend. The drought had the greatest impact on winter wheat yield at the tillering stage, jointing stage, and heading stage, and the proportions of drought risk vulnerability in these three stages accounted for 0.25, 0.21, and 0.19, respectively. The high-value areas of winter wheat loss due to drought were mainly distributed in the northeast and south-central regions.

Wetting or greening? Probing the global trends in Vegetation Condition Index (VCI)

Vegetation Condition Index (VCI), as a widely used drought index for monitoring vegetation drought stress and estimating drought trends, is constructed by normalizing the long-term satellite-based Normalized Difference Vegetation Index (NDVI) data. However, under global greening, vegetation across different regions has shown an increasing trend in greenness, which may cause VCI to inherit the greening trend in NDVI and further hamper its ability in drought trend analysis. Therefore, this study quantitatively explored the underlying relationship among VCI, global greening, and drought from 2001 to 2021 to examine the utility of VCI in a changing environment. Multi-source indicators were employed as surrogates for vegetation greenness and drought, respectively. Particularly, the Leaf Area Index (LAI) and Net Primary Production (NPP) were used as proxies for vegetation greenness while the Root-Zone Soil Moisture (RZSM), Palmer Drought Severity Index (PDSI), and Standardized Precipitation-Evapotranspiration Index (SPEI) were used for drought indices. Based on Sen’s slope estimator, Mann-Kendall (MK) test, and partial correlation analysis, our results show that the proportion of pixels with an increasing trend in VCI is approximately 38.5%, which is similar to the greenness-related indices (i.e., NPP [26.47%] and LAI [59.14%]), and is significantly higher than the other drought indices (i.e., RZSM [19.83%], PDSI [10.38%], and SPEI [9.32%]). Furthermore, our results demonstrate that the VCI, as a drought index, exhibits a closer correlation with greenness-related indicators (LAI and NPP) than other drought indices (RZSM, PDSI, and SPEI). These results reveal the potential limitations in the practical applications of VCI and could enhance our understanding of vegetation dynamics and drought trends, especially in the current greening globe. Additionally, this study serves as a cautionary note for the scientific community involved in drought monitoring, emphasizing that the VCI may not be a suitable tool for evaluating long-term trends in drought impacts on vegetation.

Climate Change Will Aggravate South Asian Cropland Exposure to Drought by the Middle of 21st Century

AbstractDrought has a paramount impact on global agriculture and food security. However, the study on future cropland areas that can incur drought is inadequate. This paper uses input parameters from 7 CMIP6 models for 7 future scenarios (SSP1‐1.9, SSP1‐2.6, SSP4‐3.4, SSP2‐4.5, SSP4‐6.0, SSP3‐7.0, and SSP5‐8.5) to measure South Asian cropland exposure to drought and its underlying factors. Some defined epochs such as 2021–2040 (near‐term), 2041–2060 (mid‐term), 2081–2100 (long‐term), and 1995–2014 (reference period) are designed to explore diverse outlooks of the change. The Standardized Precipitation Evapotranspiration Index and the Run theory methods are applied to detect drought. Results indicate an intensified cropland (under SSP4‐3.4, SSP3‐7.0, and SSP5‐8.5) in the Indo‐Gangetic Plain region of South Asia, where mostly the variation occurs among scenarios and periods. Notably, the future cropland exposed to drought will increase in the 2021–2040, and 2041–2060 periods, but it intends to decline during the 2081–2100. Relatively, the exposed cropland will upturn highest by 49.2% (SSP3‐7.0) in the mid‐term period and decrease by −8.2% (SSP5‐8.5) in the end future. Spatially, distributed cropland in the central, south‐west, and portion of the northeast of South Asia are subjective to be exposed largely, but it can drop greatly across the eastern part by the end future. Importantly, the climate change effect plays a grounding role in future exposure change over the region during the near to mid‐term periods, while the cropland change effect is predominant in the long‐term perspectives. However, these findings signify the urgency of policymaking focusing on drought mitigation to ensure food security.

Spatiotemporal Evolution of Ecological Environment Quality and Driving Factors in Jiaodong Peninsula, China

To monitor the Ecological Environment Quality (EEQ) of the Jiaodong Peninsula and provide a scientific basis for ecological environment governance and sustainable development in the region, this study evaluates the EEQ of Jiaodong using the Remote Sensing-based Ecological Index (RSEI) model and analyzes its spatiotemporal evolution patterns, building upon single-factor correlation analysis using the Random Sample Consensus (RANSAC) algorithm, using GeoDetector to analyze the driving mechanisms of human activities and natural factors in EEQ. The results indicate the following: (1) The average RSEI values for 2000, 2010, and 2020 are 0.60, 0.57, and 0.66, with Good or Excellent areas accounting for 56.48%, 51.02%, and 67.17%. From 2000 to 2020, RSEI strong improvement areas were predominantly distributed in the eastern hilly areas of the Jiaodong Peninsula. The RSEI of the Jiaodong Peninsula showed significant spatial autocorrelation. (2) The RANSAC algorithm effectively reduces noise interference in remote sensing data, thereby improving the accuracy of single-factor correlation analysis. (3) In 2000, the importance of natural factors exceeds that of human activity factors. The Standardized Precipitation Evapotranspiration Index (SPEI) is the most important driving factor; while in 2010 and 2020, human activity factors surpass natural factors in importance, with the Land Use Composite Index (LUCI) being the most significant driving factor. The driving factors exhibited double-factor and nonlinear enhancement. The most significant interaction factors affecting the EEQ of the Jiaodong Peninsula in 2000, 2010, and 2020 are SPEI∩GDP, LUCI∩SPEI, and LUCI∩GDP.

Reconstruction of July-September Standardized Precipitation-Evapotranspiration Index (SPEI) for the Hindu Kush region of Northern Pakistan

Abstract The Prolonged drought resulting from global warming is considered an important factor affecting the Asia's socioeconomic growth of West Asia, with a significant impact on the dynamic forecasting of water supply and forest ecosystems. In such a scenario, Understanding future long-term drought (SPEI) changes is crucial for accurately forecasting regional drought shifts in the Hindukush region. In this study, a 517-year (1506-2022 CE) long tree-ring width chronology of the Himalayan Cedar (Cedrus deodara D. Don) from the eastern Hindukush has been developed. The July-September SPEI has revealed a positive and significant relationship (r = 0.633, p < 0.001) with tree growth, which leads to SPEI reconstruction from AD 1626 in the Hindu Kush Region. Our reconstruction model has explained 40.01% of the climate variance during the instrumental period from AD 1965 to 2018. Fourteen wet periods (≥ 3 years) were observed before the instrumental period, specifically in C.E. 1629–1635, 1638–1658, 1666–1674, 1680–1701, 1715–1724, 1770–1776, 1794–1797, 1802–1810, 1822–1846, 1850–1857, 1872–1881, 1883–1890, 1906–1914, and 1921–1937. Similarly, twelve dry summer periods were also observed in the past 339 years, such as C.E. 1659–1665, 1675–1679, 1702–1714, 1725–1769, 1777–1793, 1798–1801, 1811–1821, 1847–1849, 1858–1871, 1891–1905, 1915–1920, and 1938–1963. Nevertheless, AD 1663 was individually the wettest (with a value of 2.13), while AD 1754 was the driest (-0.99) year. The spatial correlation analysis and its comparisons with Karakoram-Himalayan drought and precipitation reconstructions have convincingly confirmed the reliability of our SPEI reconstruction. Consequently, this reconstruction can effectively serve as a proxy for large-scale drought variability in the Hindu Kush region of northern Pakistan. Our findings strongly suggest the considerable dendrochronological potential for further climatological studies in the western Hindu Kush Mountains System.

Spatiotemporal Analysis of Drought Characteristics and Their Impact on Vegetation and Crop Production in Rwanda

In recent years, Rwanda, especially its Eastern Province, has been contending with water shortages, primarily due to prolonged dry spells and restricted water sources. This situation poses a substantial threat to the country’s agriculture-based economy and food security. The impact may escalate with climate change, exacerbating the frequency and severity of droughts. However, there is a lack of comprehensive spatiotemporal analysis of meteorological and agricultural droughts, which is an urgent need for a nationwide assessment of the drought’s impact on vegetation and agriculture. Therefore, the study aimed to identify meteorological and agricultural droughts by employing the Standardized Precipitation Evapotranspiration Index (SPEI) and the Vegetation Health Index (VHI). VHI comprises the Vegetation Condition Index (VCI) and the Temperature Condition Index (TCI), both derived from the Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST). This study analyzed data from 31 meteorological stations spanning from 1983 to 2020, as well as remote sensing indices from 2001 to 2020, to assess the spatiotemporal patterns, characteristics, and adverse impact of droughts on vegetation and agriculture. The results showed that the years 2003, 2004, 2005, 2006, 2013, 2014, 2015, 2016, and 2017 were the most prolonged and severe for both meteorological and agricultural droughts, especially in the Southern Province and Eastern Province. These extremely dry conditions led to a decline in both vegetation and crop production in the country. It is recommended that policymakers engage in proactive drought mitigation activities, address climate change, and enforce water resource management policies in Rwanda. These actions are crucial to decreasing the risk of drought and its negative impact on both vegetation and crop production in Rwanda.

Analyzing the effects of drought at different time scales on cause-specific mortality in South Africa

South Africa (SA) is highly vulnerable to the effects of drought on the environment, economy, and society. However, its effect on human health remains unclear. Understanding the mortality risk associated with different types of droughts in different population groups and by specific causes would help clarify the potential mechanisms involved. The study aims to comprehensively assess the effect of droughts of varying time scales on cause-specific mortality (all; infectious and parasitic; endocrine, nutritional, and metabolic; cardiovascular; respiratory) in SA (from 2009–2016) and identify more vulnerable profiles based on sex and age. We also evaluated the urbanicity and district-level socioeconomic deprivation as potential risk modifiers. We used a two-stage time-series study design, with the weekly standardized precipitation-evapotranspiration index (SPEI) calculated at 1, 6, 12, and 15 months of accumulation to identify droughts of different duration (SPEI1, 6, 12, 15, respectively). We applied a quasi-Poisson regression adjusted by mean temperature to assess the association between each type of drought and weekly mortality in all district municipalities of SA, and then pooled the estimates in a meta-regression model. We reported relative risks (RRs) for one unit increase of drought severity. Overall, we found a positive association between droughts (regardless the time scale) and all causes of death analyzed. The strongest associations were found for the drought events more prolonged (RR [95%CI]: 1.027 [1.018, 1.036] (SPEI1); 1.035 [1.021, 1.050] (SPEI6); 1.033 [1.008, 1.058] (SPEI12); 1.098 [1.068, 1.129] (SPEI15)) and respiratory mortality (RRs varied from 1.037 [1.021, 1.053] (SPEI1) to 1.189 [1.14, 1.241] (SPEI15)). An indication of greater vulnerability was found in younger adults for the shortest droughts, in older adults for medium-term and long-term droughts, and children for very long-term droughts. However, differences were not significant. Further evidence of the relevance of urbanicity and demographic and socioeconomic conditions as potential risk modifiers is needed.

Meteorological disaster disturbances on the main crops in the north‒south transitional zone of China

Global climate change, with warming as its main feature, has altered the spatial-temporal evolution of factors such as precipitation and temperature that can cause meteorological disasters. The complex and changeable climate has led to frequent natural disasters, while the frequency and intensity of extreme climate events have also significantly increased, posing an enormous threat to societal production and human life. As the most important geoecological transitional zone of mainland China, the stability of agricultural production in China’s north–south transitional zone is crucial for ensuring food security under climate change. With the use of daily precipitation and potential evapotranspiration data from 1961 to 2018, this study focused on analysing disturbances such as extreme precipitation and drought disasters at different time scales during the winter wheat and summer maize growing seasons in the north–south transitional zone of China from an agricultural production perspective and attempted to answer the following questions: first, from an agricultural production perspective, what are the temporal and spatial distribution patterns of extreme precipitation and arid climate events in the north–south transitional zone? Second, which areas are at high risk of being disturbed by different types of meteorological disasters and require increased attention? The results indicated that (1) in terms of the overall temporal variation, the degree of extreme precipitation and drought stress faced by agricultural production in the region is decreasing. However, the temporal variation at each station in the north–south transitional zone was not completely consistent with the overall trend, and both increasing and decreasing trends were observed. The sites exhibiting an increase overlapped with typical regions of the north–south transitional zone to varying degrees, indicating that the typical regions represented not only theoretical potential risk areas under climate change but also suffered from meteorological disaster disturbances. (2) The precipitation distribution during the winter wheat growth period in the south–north transitional zone was uneven and varied significantly. High values of extreme precipitation indices during the winter wheat growth period were mainly concentrated in the southern part of the eastern section of the north‒south transitional zone. The precipitation distribution during the summer maize growth period significantly differed, with the highest amount of heavy rain and largest number of rainstorm days concentrated in the southeastern part of the north‒south transitional zone. The spatial distribution of the drought frequency in the north–south transitional zone, as indicated by the monthly standardized precipitation evapotranspiration index (SPEI1), showed that the areas with high total drought frequencies were mainly concentrated in northeast Jiangsu, southeast Henan, and north Anhui, which primarily experienced light drought. The central part of Jiangsu Province exhibited a high frequency of moderate drought, while southern Jiangsu Province and southwestern Shaanxi Province were prone to severe drought. Additionally, southeastern Hebei and eastern Henan were identified as areas with a high frequency of extreme drought. Finally, the central region of Sichuan Province was characterized by both severe and extreme drought conditions. Based on the SPEI12-derived spatial distribution of the drought frequency in the north–south transitional zone, the areas with a high total drought frequency were mainly concentrated in central and eastern Henan, southeast Shaanxi, southeast Shandong, and central Sichuan, which primarily experienced light to moderate drought. The northwestern part of Jiangsu, the southern part of Hebei, and the western part of Shandong are regions with a high frequency of severe drought, while the eastern part of Henan is an area with high frequencies of both severe and extreme drought. (3) High-value areas of extreme precipitation and drought disturbance in the north–south transitional zone overlapped with the edge of the transitional zone to varying degrees. Approximately 63.58% of the north‒south transitional zone of China was characterized by moderate or high stress levels, primarily concentrated along the southern boundary and central core area, and nearly 39.5% of all counties experienced two or more types of disaster stresses.

Seasonal Response of the NDVI to the SPEI at Different Time Scales in Yinshanbeilu, Inner Mongolia, China

Recently, the frequent occurrence of droughts has caused a serious impact on vegetation growth and progression. This research is based upon the normalized difference vegetation index (NDVI) from 2001 to 2020. The correlation between the NDVI and standardized precipitation evapotranspiration index (SPEI) at disparate time scales was used to assess the response of vegetation growth to drought in the Yinshanbeilu region. The drought levels of SPEI1, SPEI3, SPEI6, and SPEI12 increased prominently in the eastern region of the country, while the NDVI decreased significantly from east to west in spring, summer, and autumn but was reversed in the winter. The area with an upward trend (33.86%) was slightly lower than that with a downward trend (66.14%). The correlation coefficients between the NDVI and SPEI over the entire year increased with the SPEI timescale. The elevated values were concentrated in the southeastern and western regions of the survey region. Additionally, the best correlation timescales were SPEI6 and SPEI12. Grassland was the most sensitive vegetation type to the SPEI response in the NDVI. The correlation coefficients of NDVI and SPEI1–12 were 0.313, 0.459, 0.422, and 0.406. Both spring and summer were more responsive to SPEI12, whereas autumn and winter were more responsive to SPEI3. The correlation of disparate time scales exhibited complex soil texture features with respect to different seasonal scales, and the soil texture showed a strong response to vegetation in both summer and autumn. Loam, sandy loam, and silty loam all exhibited the highest response to SPEI12, with coefficients of 0.509, 0.474, and 0.403, respectively.

Determining the impacts of climate change and human activities on vegetation change on the Chinese Loess Plateau considering human-induced vegetation type change and time-lag effects of climate on vegetation growth

ABSTRACT Since the initiation of the Grain for Green Project (GFGP) in 1999, dramatic change in vegetation status on the Loess Plateau. Spatially, geographical detector was employed to detect dominant variables influencing the spatial arrangement of normalized difference vegetation index (NDVI). Temporally, lagged or accumulated monthly precipitation, temperature and standardized precipitation evapotranspiration indices (SPEIs) sensitive to the monthly NDVI were first detected for every individual pixel, and the correlation between the NDVI and meteorological elements with time-lag effects was established a random forest model of unchanged land cover, followed by attributing impacts of climatic alterations and human interventions through residual examination across changed land cover. The findings indicate that (1) precipitation, slope, and soil dominantly influence the spatial arrangement of the NDVI. (2) Precipitation in current the month and cumulative temperatures of the previous 1–2 months steadily affect vegetation growth significantly, the optimal accumulation time interval for SPEI around 2000 are 8 months and 4 months, respectively. (3) Increases in the average NDVI within woodland and meadow vegetation on the Loess Plateau were primarily driven by climate change before 2000, accounting for 76.2%, whereas after 2000 it was dominantly driven by human activities, accounting for 64.16%.

Dryland hydroclimatic response to large tropical volcanic eruptions during the last millennium

Drylands are highly vulnerable to climate change due to their fragile ecosystems and limited ability to adapt. In contrast to the global drying after tropical volcanic eruptions shown previously, we demonstrate that large tropical volcanic eruptions can induce significant two-year hydroclimatic wetting over drylands by employing the last millennium simulations. During this wetting period, which extends from the first to the third boreal winter after the eruption, several hydroclimatic indicators, such as self-calibrating Palmer Drought Severity Index based on the Penman-Monteith equation for potential evapotranspiration (scPDSIpm), standard precipitation evapotranspiration index (SPEI), aridity index (AI), top-10cm soil moisture (SM10cm), and leaf area index (LAI), show significant positive anomalies over most drylands. The primary contribution to the wetting response is the potential evapotranspiration (PET) reduction resulting from dryland surface cooling and reduced solar radiation, as well as a weak contribution from increased precipitation. The latter is due to the wind convergence into drylands caused by slower tropical cooling compared to drylands. The wetting response of drylands to volcanic eruptions also demonstrates some benefits over the global hydrological slowdown resulting from stratospheric aerosol injection, which replicates the cooling effects of volcanic eruptions to address global warming.

High risk, high gain? Trade-offs between growth and resistance to extreme events differ in northern red oak (Quercus rubra L.).

Information about the resistance and adaptive potential of tree species and provenances is needed to select suitable planting material in times of rapidly changing climate conditions. In this study, we evaluate growth responses to climatic fluctuations and extreme events for 12 provenances of northern red oak (Quercus rubra L.) that were tested across three trial sites with distinct environmental conditions in Germany. Six provenances each were sourced from the natural distribution in North America and from introduced stands in Germany. We collected increment cores of 16 trees per provenance and site. Dendroecological methods were used to compare provenance performance and establish climate-growth relationships to identify the main growth limiting factors. To evaluate the provenance response to extreme drought and frost events, three site-specific drought years were selected according to the Standardized Precipitation Evapotranspiration Index (SPEI) and 2010 as a year with an extreme late frost event. Resistance indices for these years were calculated and assessed in relation to overall growth performance. We observed a high variation in growth and in the climate sensitivity between sites depending on the prevailing climatic conditions, as well as a high intra-specific variation. Overall, summer drought and low temperatures in the early growing season appear to constrain the growth of red oak. The resistance of provenances within sites and extreme years showed considerable rank changes and interaction effects. We did not find a trade-off between growth and resistance to late frost, namely, fast growing provenances had a high frost hardiness. Further, there was no evidence for a trade-off between growth and drought hardiness. Still, responses to drought or late frost differ between provenances, pointing to dissimilar adaptive strategies. Provenances from introduced (i.e. German) stands represent suitable seed sources, as they combine a higher growth and frost hardiness compared to their North American counterparts. Drought hardiness was slightly higher in the slow-growing provenances. The results provide a better understanding of the variable adaptive strategies between provenances and help to select suitable planting material for adaptive forest management.

Performances of different yield-detrending methods in assessing the impacts of agricultural drought and flooding: A case study in the middle-and-lower reach of the Yangtze River, China

In evaluating the impacts of drought and flooding disasters on crop yields, accurately calculating meteorological yield (i.e., detrended yield) is an important procedure. The present work aimed to compare various yield-detrending methods in terms of characterizing the regression relationships between meteorological yield and the intensities of drought and flooding. Taking the middle-and-lower reach of the Yangtze River (MLRYR) as the study region, the intensities of drought and flooding during the growing seasons of four study crops (cotton, oilseed rape, wheat, and maize) were quantified using the standardized precipitation evapotranspiration index. Nine popular yield-detrending methods and the first-difference method were employed to determine meteorological yields. The results indicated that the examined methods consistently identified the cases with very significant yield-reducing impacts of drought and flooding. The first-difference method identified 58 significant regression relationships, outperforming the yield-detrending methods (identifying 39–44 significant regression relationships). The 20-yr moving average and the linear fitting methods performed best at the provincial level, while the cubic smoothing spline and the quadratic polynomial fitting methods performed best at the district level. Based on these best-performing methods, the average method was proposed and exhibited wider applicability and better performance than the individual methods. In terms of meteorological yield losses, cotton was the most affected crop (35% of all districts experienced severe cotton yield loss) and Anhui was the most affected region (with an average crop yield loss of 14.06%). The yield-reducing impact of flooding was significant in 41 districts; in comparison, the impact of drought was significant only in 7 districts. Additionally, oilseed rape was the crop most affected by drought and flooding. These results can provide guidance for assessing agricultural drought and flooding disasters under climate change.

Projected climatic drought events in drought-prone cities: Insights from high-resolution downscaled CMIP6 data

This study investigated the drought trends, frequency, and duration in three drought-prone cities in Northwest China under various Shared Socioeconomic Pathways (SSPs) climate scenarios from 2015 to 2099. Utilizing a two-step downscaling method, we generated high-resolution (1 km) temperature and precipitation projections for the cities using multiple global climate model (GCM) data. The Standardized Precipitation Evapotranspiration Index (SPEI) was then calculated to assess drought conditions. Our results revealed that under the influence of global climate change, the 12-month SPEI exhibited a significant increasing trend for all three cities, indicating a shift towards a more humid climate. The influence of climate change on drought trends was more pronounced at higher latitudes. Additionally, the occurrence and duration of severe droughts (3-month SPEI < -1.5) were higher in the near future (2015–2056) compared to the far future (2057–2099), suggesting time-lagged and cumulative effects of global climate change on drought. Spatial variations within each city were also observed, with the western mountainous regions of Xi'an showing a more pronounced decrease in drought frequency under higher emission scenarios. Under the influence of different projected scenarios, the variations in drought characteristics across cities exhibited significant spatial heterogeneity. This study highlights the importance of understanding local and inter-regional drought characteristics in the context of climate change, and the need for targeted management policies to effectively cope with climate anomalies and associated disasters in different regions.

Detecting the interactions between vegetation greenness and drought globally

Drought changes can profoundly influence vegetation growth while vegetation, in turn, may impact drought by modulating water and energy exchanges between the land and atmosphere. Previous studies have primarily focused on the unidirectional effects of drought on vegetation dynamics. However, the impacts of vegetation on drought and their bidirectional dependencies have remained underexplored. In this paper, we employ the Leaf Area Index (LAI) and two drought indices (the Standardized Precipitation Index, SPI, and, the Standardized Precipitation Evapotranspiration Index, SPEI) to investigate the interaction between vegetation greenness and drought globally over the period 2001 to 2020. The results demonstrate a statistically significant and consistent trend between LAI and SPI (SPEI) in 66.9% (54.01%) of global vegetated lands. SPI commonly displays a 2-month delayed response to LAI, whereas SPEI shows no evident lag, implying a more rapid response of SPEI to LAI compared to SPI. A substantial proportion of global vegetated areas, around 66% for LAI-SPI and 52% for LAI-SPEI, exhibit a significant positive relationship. The Granger causality test reveals a bidirectional causal relationship between vegetation greenness and drought across approximately 20% of global vegetated areas. Vegetation greenness is identified as the Granger cause of SPI (SPEI) in >60% (30%) of global vegetated lands, providing statistical observational evidence indicating that vegetation can influence drought in many regions within terrestrial ecosystems. Interestingly, the ratio of areas where LAI serves as the Granger cause of SPI is more extensive than the corresponding ratio where SPI is identified as the Granger cause of LAI, a pattern opposite to that observed with SPEI. Overall, our investigation into the interactions between vegetation greenness and drought holds significance for enhancing our understanding of land-atmosphere interplays in the context of climate change and contributes to advancing sustainable development for ecosystem services.

Evaluation of models and drought-wetness factors contributing to predicting the vegetation health index in Dak Nong Province, Vietnam

Monitoring and predicting vegetation health are essential for agricultural activities and food security. This study aimed to select a model and evaluate the factors contributing to predicting the vegetation health index (VHI) in the Dak Nong Province, Vietnam. Machine learning algorithms were evaluated, including multiple linear regression, xGBoost, and artificial neural networks (ANN). The input variables of the models included the standardized precipitation evapotranspiration index (SPEI), soil moisture (SM), and VHI in the previous periods. Research results showed that the ANN model gave the best prediction results. The accuracy of prediction results depended on the season of the year, in which the dry season gave a result with high accuracy. The results also indicated that SM from one to two previous months, SPEI1 from one to three previous months, SPEI3 and SPEI5 from three to six previous months, and VHI from one previous month contributed mainly to the prediction model. The relative contribution of SM and SPEI ranged from 42% to 52% in the last 4 months of the dry season. In addition, land use type also affected prediction quality.

Delineating the predominant impact of rising temperature on the enhancement of severity in compound drought-hot events in China: An empirical Copula and path analysis-based approach

Study regionChina Study focusCompound drought-hot events (CDH) inflict serious socio-economic damages on our society and the natural environment. Given the inverse relationship between average summer temperature and precipitation, this investigation introduces an innovative empirical copula-based compound drought-hot index (CDHI). This index is crafted from the joint distribution of the standardized precipitation evapotranspiration index (SPEI) and standardized temperature index (STI). While previous research has documented a rising trend in these complex events on both regional and global stages, scrutiny into their escalating severity remains limited. To highlight the critical role of climbing temperatures in the increasing severity of CDH events within China, our research utilizes the CDHI in tandem with a path analysis to precisely assess severity shifts in CDH occurrences during the warm season from 1901 to 2022. New hydrological insights for the regionThis study used an empirical copula-based CDH index and implemented the path analysis to quantify the response of severity changes of compound drought-hot events to shifts of summer mean temperature and water deficit from the historical perspective. Our findings reveal a marked escalation in CDH severity across much of China. Path analysis divulges that the influence of rising summer temperatures on CDH severity has seen a significant uptick in the last 60 years (1962–2022), displaying a more considerable contribution rate than the earlier 60-year span (1901–1961). This points to the changing impact of temperature on CDH events over recent decades. During the initial interval (1901–1961), we saw a 0.7% and 1.7% per-decade increase in areas affected by severe and moderate CDH events, respectively. Contrastingly, the subsequent period (1962–2022) experienced a more significant rise, with the area affected by severe and moderate events expanding over twice as much. Totally speaking, this exploration enhances our comprehension of the intensification in CDH event severity and the role of climatic drivers. These insights can contribute to improved risk assessments and the development of tailored adaptation and mitigation strategies in the face of ongoing climate change.

Characteristics of propagation from meteorological drought to ecological drought in China: Lag and cumulative effects

The increasing frequency and severity of droughts will seriously impact agricultural production and the ecological environment. Studying the drought lag (DL) and drought cumulative (DC) effects of propagation between meteorological drought to ecological drought can help to enhance the capacity of ecological drought monitoring. Therefore, in this study, the meteorological drought index (non-stationary standardized precipitation evapotranspiration index, NSPEI) and ecological drought index (vegetation condition index, VCI) were obtained using ERA5 reanalysis data and MODIS vegetation index data, respectively. The purpose of this study was to reveal the DL and DC effects of the propagation of meteorological drought to ecological drought and investigate the spatial heterogeneity of drought propagation in different underlying surfaces and climate zones. The results indicated that: 1) Northern China is more vulnerable to severe and extreme droughts, and 68% of the region has significantly slower ecological droughts. 2) The western temperate zone, highland climate zone, and subtropical zone have shorter DL times for subtropical drought and longer DL times for eastern temperate zones. 3) DC and DL effects have similar spatial distributions. However, the DC duration of grassland and bare ground is shorter in the northwest and south, and longer in grassland and farmland in northern China. 4) China overall is more affected by the DC effect, while the DL effect is more significant in southern temperate zone.