Drought Variability Research Articles

Concurrent trend turnings of drought severity across Afro-Eurasian continent since 1950

Rapidly intensifying global land drought poses severe threats to human societies, economies, and ecosystems. While previous studies have primarily investigated long-term drought trends, the frequency and concurrence of trend turnings have been largely neglected. In this study, we address this gap by employing the Running Slope Difference (RSD)-t-test to quantify trend turning frequency in Afro-Eurasian drought severity. Based on Palmer Drought Severity Index (PDSI), our analysis indicates that the PDSI trend in most parts of the Afro-Eurasian continent has experienced two turnings since 1950, although, the types of trend turnings vary regionally. The concurrence of these PDSI trending turnings is further investigated. Around 1985, a dipole pattern emerged - Eastern Europe experiences a drying trend turning, accompanied by decreased P-E and intensified drought, while Sahel exhibits a wetting trend turning, with increased P-E and mitigated drought. Around 2000, a tripole pattern is observed in Eastern Eurasia: The Russian Far East and South Asia experienced a drying trend turning, with reduced P-E and intensified drought, while Northeast Asia exhibited a further wetting trend, characterized by increased P-E and mitigated drought. We further investigate the influence of large-scale circulation changes. The enhanced Northern Hemisphere warming trend before and after 1985 contributes to increased land surface high pressure and an amplified meridional temperature gradient, favoring cross-equatorial water vapor transport. This mechanism potentially drives the dipole pattern of trend turning observed around 1985. Additionally, the North Pacific Ocean Sea Surface Temperature (SST) exhibited an enhanced North Pacific Gyre Oscillation (NPGO) pattern around 2000, which induced a tripole atmospheric circulation pattern over East Asia, corresponding to the observed tripole pattern of PDSI trend turnings. The identified dipole and tripole patterns of drought trend turnings, and their potential links to large-scale atmospheric circulation changes, provide insights into the complex dynamics of land drought variability across Afro-Eurasian.

A Coupled Model for Forecasting Spatiotemporal Variability of Regional Drought in the Mu Us Sandy Land Using a Meta-Heuristic Algorithm

Vegetation plays a vital role in terrestrial ecosystems, and droughts driven by rising temperatures pose significant threats to vegetation health. This study investigates the evolution of vegetation drought from 2010 to 2024 and introduces a deep-learning-based forecasting model for analyzing regional spatial and temporal variations in drought. Extensive time-series remote-sensing data were utilized, and we integrated the Temperature–Vegetation Dryness Index (TVDI), Drought Severity Index (DSI), Evaporation Stress Index (ESI), and the Temperature–Vegetation–Precipitation Dryness Index (TVPDI) to develop a comprehensive methodology for extracting regional vegetation drought characteristics. To mitigate the effects of regional drought non-stationarity on predictive accuracy, we propose a coupling-enhancement strategy that combines the Whale Optimization Algorithm (WOA) with the Informer model, enabling more precise forecasting of long-term regional drought variations. Unlike conventional deep-learning models, this approach introduces rapid convergence and global search capabilities, utilizing a sparse self-attention mechanism that improves performance while reducing model complexity. The results demonstrate that: (1) compared to the traditional Transformer model, test accuracy is improved by 43%; (2) the WOA–Informer model efficiently handles multi-objective forecasting for extended time series, achieving MAE (Mean Absolute Error) ≤ 0.05, MSE (Mean Squared Error) ≤ 0.001, MSPE (Mean Squared Percentage Error) ≤ 0.01, and MAPE (Mean Absolute Percentage Error) ≤ 5%. This research provides advanced predictive tools and precise model support for long-term vegetation restoration efforts.

Differential impacts of fire and inundation on a wetland plant community after wildfire

Context Understanding fire and inundation impacts on wetland vegetation communities is crucial for effective post-fire wetland management. Aims We aimed to determine the impact of post-fire inundation on plant community structure and seedling germination and establishment after a large wildfire. We asked two questions, namely (1) did fire, drought or inundation affect plant communities the most; and (2) did fire or inundation affect seedling germination and establishment? Methods Using a before–after–control–impact (BACI) design, we monitored vegetation changes in water-couch wetland communities before and after a wildfire. Also, soil samples were collected from burnt and unburnt sites and assessed for impacts of fire and post-fire inundation regimes on seed germination and seedling establishment. Key results Inundation variables had more pronounced and more consistent impacts on vegetation measures than did fire or drought variables. Fire impacts were mainly short-term, with impact thresholds at 72 and 143 days after fire. Low germination levels and zero seedling survival were observed without inundation. Conclusions Fire was a major but short-term contributor to wetland vegetation change, whereas drought had longer-term impacts, and inundation regimes had the greatest impacts. Implications Providing a range of inundation conditions post-fire may enhance wetland vegetation recovery and have modifying effects on invasive species.

Phasic and periodic change of drought under greenhouse effect

Purpose Drought is the primary disaster that negatively impacts agricultural and animal husbandry production. It can lead to crop reduction and even pose a threat to human survival in environmentally sensitive areas of China (ESAC). However, the phases and periodicity of drought changes in the ESAC remain largely unknown. Thus, this paper aims to identify the periodic characteristics of meteorological drought changes. Design/methodology/approach The potential evapotranspiration was calculated using the Penman–Monteith formula recommended by the Food and Agriculture Organization of the United Nations, whereas the standardized precipitation evaporation index (SPEI) of drought was simulated by coupling precipitation data. Subsequently, the Bernaola-Galvan segmentation algorithm was proposed to divide the periods of drought change and the newly developed extreme-point symmetric mode decomposition to analyze the periodic drought patterns. Findings The findings reveal a significant increase in SPEI in the ESAC, with the rate of decline in drought events higher in the ESAC than in China, indicating a more pronounced wetting trend in the study area. Spatially, the northeast region showed an evident drying trend, whereas the southwest region showed a wetting trend. Two abrupt changes in the drought pattern were observed during the study period, namely, in 1965 and 1983. The spatial instability of moderate or severe drought frequency and intensity on a seasonal scale was more consistent during 1966–1983 and 1984–2018, compared to 1961–1965. Drought variation was predominantly influenced by interannual oscillations, with the periods of the components of intrinsic mode functions 1 (IMF1) and 2 (IMF2) being 3.1 and 7.3 years, respectively. Their cumulative variance contribution rate reached 70.22%. Research limitations/implications The trend decomposition and periods of droughts in the study area were analyzed, which may provide an important scientific reference for water resource management and agricultural production activities in the ESAC. However, several problems remain unaddressed. First, the SPEI considers only precipitation and evapotranspiration, making it extremely sensitive to temperature increases. It also ignores the nonstationary nature of the hydrometeorological water process; therefore, it is prone to bias in drought detection and may overestimate the intensity and duration of droughts. Therefore, further studies on the application and comparison of various drought indices should be conducted to develop a more effective meteorological drought index. Second, the local water budget is mainly affected by surface evapotranspiration and precipitation. Evapotranspiration is calculated by various methods that provide different results. Therefore, future studies need to explore both the advantages and disadvantages of various evapotranspiration calculation methods (e.g. Hargreaves, Thornthwaite and Penman–Monteith) and their application scenarios. Third, this study focused on the temporal and spatial evolution and periodic characteristics of droughts, without considering the driving mechanisms behind them and their impact on the ecosystem. In future, it will be necessary to focus on a sensitivity analysis of drought indices with regard to climate change. Finally, although this study calculated the SPEI using meteorological data provided by China’s high-density observatory network, deviations and uncertainties were inevitable in the point-to-grid spatialization process. This shortcoming may be avoided by using satellite remote sensing data with high spatiotemporal resolution in the future, which can allow pixel-scale monitoring and simulation of meteorological drought evolution. Practical implications Under the background of continuous global warming, the climate in arid and semiarid areas of China has shown a trend of warming and wetting. It means that the plant environment in this region is getting better. In the future, the project of afforestation and returning farmland to forest and grassland in this region can increase the planting proportion of water-loving tree species to obtain better ecological benefits. Meanwhile, this study found that in the relatively water-scarce regions of China, drought duration was dominated by interannual oscillations (3.1a and 7.3a). This suggests that governments and nongovernmental organizations in the region should pay attention to the short drought period in the ESAC when they carry out ecological restoration and protection projects such as the construction of forest reserves and high-quality farmland. Originality/value The findings enhance the understanding of the phasic and periodic characteristics of drought changes in the ESAC. Future studies on the stress effects of drought on crop yield may consider these effects to better reflect the agricultural response to meteorological drought and thus effectively improve the tolerance of agricultural activities to drought events.

Assessment of Meteorological Drought in a Changing Environment: An Example in the Upper Yangtze River

AbstractRecent studies have suggested that drought projections using Palmer drought severity index (PDSI) and standardized evapotranspiration precipitation index (SPEI) may overestimate drought severity. This overestimation occurs because the potential evapotranspiration (PET) calculations fail to consider the interactive effects of vegetation responses such as increased leaf area index (LAI) and constrained stomatal conductance, which are influenced by elevated atmospheric CO2 concentrations ([CO2]). To address this issue, our study replaced the traditional Penman‐Monteith (PM) equation with a recently proposed PET equation that includes the effects of changing [CO2] and LAI to assess droughts at monthly scale in the Upper Yangtze River basin, which experiences the vegetation greening. The findings indicated a consistent increasing trend in drought conditions with minimal discrepancy between the two equations over the historical period (1986–2017). This consistency arises because the water‐saving effects of increased [CO2] and the greening effects of rising LAI largely counterbalance each other. However, for the future period (2018–2100), projections using PM equation predicted an intensification of drought conditions. In contrast, the improved SPEI indicated no significant drought variations, and the improved PDSI suggested a wetting trend. This divergence can be attributed to the water‐saving effects increasingly outweighing the greening effects, as PET shows a decreasing sensitivity to LAI with LAI increasing, but maintains a near‐constant sensitivity to elevated [CO2]. Consequently, the indices based on PM equation tend to overestimate future drought severity. Overall, this study demonstrates that the new PET estimation method is more capable of responding to the changing environment.

Multi-scale drought variability over West Africa and the associated large-scale circulation patterns

This study addresses the critical research gap in understanding regional drought dynamics in West Africa (WA) using advanced multivariate wavelet coherence (MWC) techniques, revealing critical insights into the complex interplay between large-scale climate indices and regional drought patterns. Utilizing the Standardized Precipitation Evapotranspiration Index (SPEI) and self-calibrating Palmer Drought Severity Index (scPDSI), we examined drought characteristics across WA from 1950 to 2018. Our analysis revealed significant drying trends across all seasons, with the Arid zone experiencing the most severe and prolonged drought (158 months) from August 1981 to September 1994, affecting 79.77% of the area. The entire WA region faced its most extensive drought during this period, impacting over 60% of the study area. MWC analysis demonstrated enhanced drought predictability when combining climate indices, particularly the Southern Oscillation Index with the Atlantic Multidecadal Oscillation, yielding high Average Wavelet Coherence values of 0.52 (SPEI) and 0.53 (scPDSI), with substantial Percentage Area of Significant Coherence of 40.19% and 43.68%, respectively. These findings highlight the crucial role of oceanic-atmospheric interactions in modulating drought conditions across WA. Our results provide valuable insights for improving drought forecasting and management strategies in the region, emphasizing the need for integrated approaches that consider multiple climate indices and their combined effects on drought dynamics.

Environmental impacts of the billion tree Tsunami project in Khyber Pakhtunkhwa on the dynamics of Agro-Meteorological Droughts

Changes in forest cover are closely associated with the variability in meteorological and hydrological variables. Therefore, this study delves into investigating how forest cover changes impact the environment (i.e., hydro-meteorological variables, including precipitation, streamflow, relative humidity (RH), evapotranspiration (ET), and temperature) using Trend Projection (TP) methods during 1980–2019. The study is carried out in the Khyber Pakhtunkhwa (KP) province of Pakistan, which witnessed deforestation between 1980 and 2010 followed by afforestation (through billion tree tsunami project, BTTP) initiated in 2014. A new drought index, named as agro-meteorological drought index (AMDI), is developed in this study using the remotely sensed data to analyze the impact of forest cover on drought severity. The robust least square regression (RLSR) model is used to regress the normalized difference vegetation index (NDVI) with AMDI at various time scales to investigate the impact of forest cover on drought severity. The RLSR and paired t-test are used to quantify the impact of forest cover and BTTP, in particular, on the environment. Land use maps prepared for KP province over a span of the past four decades revealed significant deforestation during 1985–2005, transitioning gradually to afforestation in the past decade. Results indicated a decline in streamflow throughout different seasons with an increase in forest cover, particularly during the period of afforestation (i.e., 2015–2019). The precipitation, RH (maximum/minimum), and ET displayed an increasing trend over time, whereas a decrease trend is observed in Tmax/Tmin and streamflow at most of the stations. The trend analyses depicted a significant change before and after the BTTP. The paired t-test results revealed that BTTP has statistically significant impact on the environmental variables. Furthermore, the time series plots of AMDI at different time scales indicated that drought events were frequent and severe prior to 2003, whereas significant decrease in both the frequency and severity of drought was observed in the last decade (2010–2019). The RLSR results at pixel scales demonstrated the crucial role of forest covers in alleviating both the frequency and severity of drought events. The elasticities revealed that increase in the forest cover resulted in substantial increase/decrease in each hydro-meteorological variable. Overall, the results highlighted a positive and statistically significant impact of forest cover (i.e., BTTP) on both the environment and drought variability.

Emergency constraint-based CMIP6 predictions for future droughts on the Mongolian Plateau

Accurate predictions of future drought changes in the context of warming play an important role for both human social and ecological environments. This study aims to predict future droughts on the Mongolian Plateau using the latest Coupled Model Comparison Project dataset. First, the historical and future relationships of 17 Global Climate Models (GCMs) were constrained using the emergent constraints method to establish new predictions for future droughts under SSP2-4.5 and SSP5-8.5 scenarios. Based on two scenarios, spatial and temporal variations of future droughts on the Mongolian Plateau were analyzed. Future droughts will be worse compared to historical periods. In the SSP2-4.5 scenario, the future drought intensity shows an increasing trend, the frequency of drought gradually increases, and the spatial variation of both decreases gradually from the southwest to the northeast. Under the SSP5-8.5 scenario, the intensity and frequency of droughts increases from 2020 to 2060; from 2061 to 2100, the intensity and frequency of droughts show a decreasing trend. The spatial variation is uniform, with high values in the southwest and low values in the northeast.

Enhancing Drought Risk Assessment in the Punjab, Pakistan: A Copula-Based Modeling Approach for Future Projections

Abstract Drought is one of the most complicated and challenging natural hazards, which occurs nearly in every part of the world and poses recurring challenges to agriculture, food security, livestock, human health, and water management. Pakistan has a long history of drought; however, this study focuses on drought analysis and projection in the province of Punjab, Pakistan, as it provides around 60% of the country’s food product, significantly contributing to the national food supply and economy. This study utilized the previous 56 years (1962–2017) of climate data to calculate the reconnaissance drought index (RDI) and then extracted the drought variables of durations and severity for each meteorological station. The best-fit marginal probability distribution and copula models were chosen for the stations based on numerical as well as graphical evaluation. Lognormal and exponential probability distributions, as well as Gumbel, are selected as the best-fit probability distributions for both drought characteristics and bivariate copula model, respectively, for projections. From the projections, we can infer that the smaller return periods indicate high vulnerability while longer return periods with low vulnerability. The results suggest that Faisalabad, Bahawalpur, Bahawalnagar, and Multan stations have the lowest return periods, indicating high vulnerability, and may experience drought more frequently in the future. Mianwali, Khanpur, Lahore, and Sialkot stations may have an intermediate vulnerability to drought events. The stations of Jhelum, Murree, and Sargodha have larger return periods, implying lower susceptibility to drought events in the future. The projected results provide insights for policymakers and stakeholders to optimize the risk of droughts on agriculture production, livestock, water management, human health, and food security in Punjab, Pakistan.

Remotely Sensed Comparative Spatiotemporal Analysis of Drought and Wet Periods in Distinct Mediterranean Agroecosystems

Drought is a widespread natural hazard resulting from an extended period of reduced rainfall, with significant socioeconomic and ecological consequences. Drought severity can impact food security globally due to its high spatial and temporal coverage. The primary objective of this paper consists of a comparative spatiotemporal analysis of environmental extremes (drought/wetness) through the estimation of a twelve-month Standardized Precipitation Index (SPI12) between three distinct vulnerable agricultural regions in the Mediterranean basin (i.e., Spain, Lebanon and Tunisia), under a climate change environment in the last 38 years (1982–2020). The added value of this paper lies in the simultaneous estimation of temporal and spatial variability of drought and wetness periodic events, paying special attention to the geographical patterns of these extremes both in annual and interannual (seasonal) time scales. The results indicated that Spain and Tunisia (western Mediterranean) exhibit similar patterns over the studied period, while Lebanon demonstrates contrasting trends. Comparing the two extreme dry hydrological years, the Spanish study area faced the highest drought intensity, areal extent and duration (SPI12 = −1.18; −1.84; 28–78%; 9–12 months), followed by the Lebanese (SPI12 = −1.28; −1.39; 37–50%; 7–12 months) and the Tunisian ones (SPI12 = −1.05; −1.08; 10–34%; 8 months). Concerning the wettest hydrological years, the Lebanese study domain has recorded the highest SPI12 values, areal extent and duration (SPI12 = 1.58; 2.28; 66–83%; 8–11 months), followed by the Tunisian (SPI12 = 1.55; 1.79; 49–73%; 7–10 months) and Spanish one (SPI12 = 1.07; 1.99; 21–73%; 4–11 months). The periodicity of drought/wetness episodes is about 20 years in Spanish area and 10 years in the Lebanese area (for drought events), whereas there seems no periodicity in the Tunisian one. Understanding the spatial distribution of drought is crucial for targeted mitigation strategies in high-risk areas, potentially avoiding broad, resource-intensive measures across entire regions.

Assessing the Impact of Agricultural Practices and Urban Expansion on Drought Dynamics Using a Multi-Drought Index Application Implemented in Google Earth Engine: A Case Study of the Oum Er-Rbia Watershed, Morocco

Drought monitoring is a critical environmental challenge, particularly in regions where irrigated agricultural intensification and urban expansion pressure water resources. This study assesses the impact of these activities on drought dynamics in Morocco’s Oum Er-Rbia (OER) watershed from 2002 to 2022, using the newly developed Watershed Integrated Multi-Drought Index (WIMDI), through Google Earth Engine (GEE). WIMDI integrates several drought indices, including SMCI, ESI, VCI, TVDI, SWI, PCI, and SVI, via a localized weighted averaging model (LOWA). Statistical validation against various drought-type indices including SPI, SDI, SEDI, and SMCI showed WIMDI’s strong correlations (r-values up to 0.805) and lower RMSE, indicating superior accuracy. Spatiotemporal validation against aggregated drought indices such as VHI, VDSI, and SDCI, along with time-series analysis, confirmed WIMDI’s robustness in capturing drought variability across the OER watershed. These results highlight WIMDI’s potential as a reliable tool for effective drought monitoring and management across diverse ecosystems and climates.

A novel framework for assessing the joint and relative impacts of precipitation and groundwater on ecological drought processes in Northwest China

AbstractEcological drought has emerged as a critical research topic within eco‐hydrology, driven by the increased drought risk associated with global warming. This study aims to unravel the hydrological processes driving ecological drought in Northwest China by (1) constructing standardized indices for precipitation, groundwater storage anomaly, and ecological water deficit to detect variation across different hydrological components; (2) developing a framework to assess the joint and relative impacts of precipitation and groundwater variations on ecological drought; and (3) identifying the primary hydrological drivers of ecological drought across different regions. The results indicate that the joint impact of precipitation and groundwater on ecological drought variation dominates approximately 60% of the area, primarily in arid and semi‐arid regions. The average contribution of this joint impact to the alleviation of ecological drought ranges between 0.26 and 0.43 across all seasons. Notably, groundwater scarcity, rather than precipitation variation, is the primary driver of ecological drought in regions such as southern Shaanxi, southeastern Gansu, and southern Qinghai, accounting for 12.7% to 21.8% of the total area. These insights into the complex hydrological processes underlying ecological drought have significant implications for water resource management and ecosystem conservation in drought‐prone regions. This research provides valuable information for mitigating drought impacts and protecting vulnerable ecosystems in Northwest China and similar regions worldwide.

Spatiotemporal variability of hydro-meteorological droughts over the Arabian Peninsula and associated mechanisms

This study examines the spatiotemporal variability of drought and associated physical processes over the Arabian Peninsula (AP). For this purpose, we computed the standardized precipitation evapotranspiration index (SPEI) for the period 1951–2020 using the Climate Research Unit and fifth generation ECMWF atmospheric reanalysis datasets. By applying rotated empirical orthogonal function analysis on the SPEI data, we identified four homogeneous and coherent drought regions. The droughts in the northern regions follow a relatively similar temporal evolution as compared to those in the southern region. All four sub-regions of the AP exhibit a significant drying trend (p < 0.01) with an abrupt acceleration in drought frequency and intensity over the last two decades. The increase in droughts is associated with the reduction of synoptic activity and an increase in the high pressure over the AP. Seasonally, potential evapotranspiration is the dominant driver of summer droughts in the AP, whereas both precipitation and temperature are important for driving winter droughts. The summer droughts, mainly over the northern AP, are due to the occurrence of an anomalous equivalent barotropic high associated with anomalous dry and hot conditions. However, anomalous dry conditions in winter are a result of an anomalous paucity of winter storms caused by the weakening of the sub-tropical jets.

Space-Time Variability of Drought in Tay Nguyen Provinces, Vietnam Using Satellite-Based Vegetation Time Series from 2000 to 2023

Space-Time Variability of Drought in Tay Nguyen Provinces, Vietnam Using Satellite-Based Vegetation Time Series from 2000 to 2023

Spatial and temporal variability of meteorological droughts including atmospheric circulation in Central Europe

Drought is one of the natural phenomena influencing many aspects of human activities like water scarcity, food production, agriculture, industry and ecological conditions of the environment. For decades, drought has caused huge financial losses in Europe and around the world. In the area of the Polish Carpathians, there are periods with a deficit of rainwater and increasing frequency of dry months especially in the cold half-year. However, only a limited number of studies exist about the spatial and temporal variability of meteorological drought and the main mechanisms determining its performance in Central Europe. The aim of this work is to perform the spatial and temporal analysis of drought, expressed as SPI, in a heterogenous area of the Polish Carpathian and the highland region in the East-Central part of Europe based on long-term precipitation data. Moreover, for the first time in this work drought characteristics assessed by means of the SPI were discussed considering the atmospheric circulation calendar. In this work monthly precipitation from 55 rainfall stations were analysed from 1961 to 2022. The 3-, 6-, 9-, and 12-month Standardized Precipitation Index (SPI) was used as indicators of meteorological drought. For the 3-month SPI, the main climatic mechanisms determining extreme droughts were defined based on the calendar of synoptic circulations. The Mann-Kendall test was used to detect the trend of extreme droughts. Statistically significant trends of SPI were observed on 52.7% of all analyzed stations and, in most cases, a positive trend was observed, indicating an increase in water resources in the Upper Vistula Basin. Statistically significant trends were more frequently observed in stations located in the western part of the analyzed region. Long-term droughts, represented by the 12-month SPI, occurred in all stations but not in all years. Short-term droughts (3-month SPI) were most frequent in the winter season, 6- and 9-month SPI in winter and spring, and 12-month SPI in winter and autumn. The spatial distribution of droughts was highly diverse. The most intensive drought occurred in 1984, with the 6-month SPI covering 98% of the analyzed region, and the 9- and 12-month SPI covering 90% of the entire region. Droughts exhibit a seasonal pattern, with a dominant 10-year periodicity for all analyzed variants of SPI. Additionally, Fourier analysis revealed a 2-year periodicity for the 3-, 6-, and 9-month SPI and a 31-year periodicity for the 12-month SPI. The results provide insights into the typical climatic conditions in Poland, with strong seasonality in precipitation. The study highlighted that short-term extreme droughts, represented by the 3-month SPI, are often caused by anticyclonic situations with high-pressure wedges Ka and Wa, as observed in 52.3% of cases. These findings are crucial for understanding the spatial and temporal variability of short and long-term extreme droughts in Central Europe, particularly for the agriculture sector which is dominant in the northern part of the analyzed region, where drought frequency is highest.

Increasing drought frequency in the central Zagros Mountains of western Iran over the past two centuries

The Zagros region in western Iran has experienced prolonged drought, significantly impacting water resource and forest ecosystems over the past few centuries. Understanding historical prolonged drought is crucial for making precise forecasts of shifts in regional drought in the Zagros region. Due to the lack of comprehensive historical records, the use of proxy records is considered a valuable tool for reconstructing past drought variations. We aimed to construct a tree-ring chronology of Juniper (Juniperus polycarpus) in the central Zagros region to comprehend its growth response to climate variables. We cored 25 J. polycarpus trees from the Keygooran forest reserve in western Iran and developed the tree ring chronology (1802–2022) using dplR. The relationships between tree growth and climate variables of monthly mean temperature, precipitation, PDSI (Palmer Drought Severity Index), and SPEI (Standardized Precipitation Evapotranspiration Index) were examined. The analysis revealed a strong positive correlation between tree growth and SPEI March-September of 1990–2018 on a 48-month timescale with a 2-year lag (r = 0.61, p < 0.05) which was included in the transfer model. Consequently, the SPEI-48 March-September was reconstructed for the period 1802–2022. On this reconstruction, several extremely dry years in 1832, 1867, and 1876 and extremely wet years in 1807, 1814, 1838, 1850, 1907, and 1908 years were identified, some of them aligning with historical records in Iran. Furthermore, there was a relationship between SPEI-48 March-September and teleconnection events suggesting that certain drought occurrences in the area were associated with the El Niño-Southern Oscillation (ENSO). Consequently, this reconstruction can serve as a reliable proxy for large-scale drought variability in the Zagros region of western Iran. Moreover, our research underscores the utility of SPEI in reconstructing the history of semi-arid climate conditions.

50-year seasonal variability in East African droughts and floods recorded in central Afar lake sediments (Ethiopia) and their connections with the El Niño–Southern Oscillation

Abstract. Understanding past and present hydrosystem feedbacks to global ocean–atmospheric interactions represents one of the main challenges to preventing droughts, extreme events, and related human catastrophes in the face of global warming, especially in arid and semiarid environments. In eastern Africa, the El Niño–Southern Oscillation (ENSO) was identified as one of the primary drivers of precipitation variability affecting water availability. However, the northern East African Rift System (EARS) still suffers from the underrepresentation of predictive and ENSO teleconnection models because of the scarcity of local to regional historical or palaeo-data. In this paper, we provide a 50-year seasonal flood and drought chronicle of the Awash River catchment from the study of laminated sediment from Gemeri and Afambo lakes (central Afar region, Ethiopia) with the aim of reconstructing the magnitude of regional hydroclimatic events. Pluricentimetric micro-laminated lithogenic facies alternating with plurimillimetric carbonate-enriched facies are investigated in both lakes. We couple dating methods including radiocarbon, short-lived radionuclides, palaeomagnetic field variations, and varve counting on both lake deposits to build a high-resolution age model and to discuss the regional hydrosedimentary dynamics of the Awash River over the last ∼ 700 years with a focus on the last 50 years. Using a multiproxy approach, we observe that following a multicentennial enhanced hydrological period, the two lakes have experienced a gradual decrease in river load inflow since 1979 CE, attaining extreme drought and high evaporative conditions between 1991 and 1997 CE. In 2014, the construction of a dam and increased agricultural water management in the lower Awash River plain impacted the erodibility of local soils and the hydrosedimentary balance of the lake basins, as evidenced by a disproportionate sediment accumulation rate. Comparison of our quantitative reconstruction with (i) lake water surface evolution, (ii) the interannual Awash River flow rates, and (iii) the El Niño 3.4 model highlights the intermittent connections between ENSO sea surface temperature anomalies, regional droughts, and hydrological conditions in the northern EARS.

Trivariate copula functions for constructing a comprehensive atmosphere-land surface-hydrology drought index: A case study in the Yellow River basin

The current univariate and multivariate drought indices cannot fully reflect the multiple processes of meteorological-hydrological-agricultural drought. So it is important to construct a comprehensive drought index for drought monitoring in a changing environment from the perspective of the whole process of the natural water cycle “atmosphere-land surface-hydrology”. In this study, based on the standardized indices (SCI) framework and trivariate Copula functions, a multi-scale comprehensive drought index (SPERSI) integrating rainfall, temperature, runoff and soil moisture is proposed, which can synthetically reflect meteorological, hydrological and agricultural droughts. The spatial and temporal variations of drought in the Yellow River Basin (YRB) from 1961 to 2019 were investigated, and then the links between SPERSI and some remotely correlated factors were revealed by using the multiple cross wavelet transform technique. Results show that: (1) the SPERSI constructed by fusing rainfall-temperature-runoff-soil moisture information can sensitively and effectively capture the onset, persistence and termination of drought; (2) the SPERSI exhibits good performance in detecting integrated drought events in the YRB with probability of detection (POD) > 0.75, false alarm rate (FAR) < 0.04 and critical success index (CSI) > 0.73; (3) From 1961 to 2019, drought in different time scales of above Longyangxia (AL) and Longyangxia to Lanzhou (LL) zones in the YRB both show a slight mitigation trend, while the drought in remaining subzones show a trend of intensification; (4) Multiple cross-wavelet results indicate that AO is the dominant factor of drought in the Yellow River Basin, followed by ENSO. In general, SPERSI results are reliable and can provide basis for drought decision-making.

Drought variability in Pakistan: Navigating historical patterns in a changing climate with global teleconnections

Drought variability in Pakistan: Navigating historical patterns in a changing climate with global teleconnections

Impact of extreme seasonal drought on ecosystem carbon‒water coupling across China

Water use efficiency (WUE) is a critical evaluation indicator of ecosystem responses to climate change and its extremes. However, the influence of the timing of extreme drought on the variation of ecosystem WUE under severe water stress has not been studied extensively. In particular, the modulation of drought impacts on WUE under regional hydro-climatic conditions and biome types is poorly understood. Considering observation-based ecosystem flux and drought index datasets, this study examined the impact of extreme seasonal drought on WUE in China and attempted to reveal the underlying drivers of seasonal variations in drought impacts. Results showed that the direction and magnitude of drought impacts on WUE depend on the occurrence time of extreme drought and the seasonal dynamics of regional ecological and climatic conditions. Across the vegetated regions in China, the most widespread reduction in WUE under extreme drought conditions was observed in summer, whereas approximately 60% of the study area showed positive changes in WUE under extreme drought conditions in spring. Furthermore, the co-regulation of drought characteristics and background environmental conditions in determining the impacts of extreme seasonal drought on ecosystem WUE is highlighted. Classification and regression tree analysis results illustrate that leaf area index (LAI) and drought timing dominated ecosystem WUE variation in response to extreme drought in China. Regions with lower LAI experienced more serious reductions in WUE under extreme drought. These findings indicate the importance of accounting for the interaction between drought seasonality and biome features in assessing drought impacts, thus contributing to improving the modelling of terrestrial ecosystem responses to climate extremes under global warming.