Drought Variability Research Articles

Spatial and temporal variations of spring drought in Southwest China and its possible teleconnection with the global climate events

Study regionSouthwest China (97.4ºE∼112.1ºE, 21.1ºN∼34.3ºN), including Sichuan, Yunnan, Guizhou, Chongqing, and Guangxi provinces. Study focusMeteorological droughts were likely to become much more frequent and intensified, posing a huge threat to food security, drinking water supply, ecological environment security, and sustainable development of economy and society. However, the spatial and temporal variations of seasonal droughts and its possible driving forces are still not fully understood. In this work, we deeply explored the spatial and temporal variations of spring drought in Southwest China and its possible teleconnection mechanisms during 1961–2020. New hydrological insights for the regionThe rising temperature and reduced precipitation led to a significant worsen trend of spring drought in the eastern parts of Southwest China (ESWC) during 1961–2020. Significant abrupt changes of spring drought occurred in 2003, and spring drought became much more frequent and intensified especially after 2003 in ESWC. Spring drought evolutions were dominated by NAO, and were also affected by the coupling of TNA and AO in ESWC during 1961–2020. However, the significant worsen trend of spring drought during 2003–2020 in ESWC could be largely explained by the coupling influences of NAO, TNA, and PDO. These results can provide valuable information for agricultural production, water resource management, and especially the early warning and prediction of spring drought in Southwest China.

Drought variability assessment using standardized precipitation index, reconnaissance drought index and precipitation deciles across Balochistan, Pakistan.

Drought variability analysis is of utmost concern for planning and efficiently managing water resources and food security in any specific area. In the current study, drought spell occurrence has been investigated in the Balochistan province of Pakistan during the past four decades (1981-2020) using standardized precipitation index (SPI), reconnaissance drought index (RDI), and precipitation deciles (PD) at an annual timescale. Precipitation and temperature data collected from 13 synoptic meteorological stations located in Balochistan were used to calculate the SPI, the RDI, and the PD for calculation of drought severity and duration. Based on these indices, temporal analysis shows adverse impacts of drought spells in Nokkundi during 1991-1993, in Barkhan, Dalbandin, Quetta stations during 1999-2000, whereas Barkhan, Dalbandin, Lasbella, Sibi during 2002-2003, Zhob during 2010-2011, Kalat and Khuzdar during 2014-2015, and Panjgur during 2017-2018. Also, the aridity index for each station was calculated based on the UNEP method shows that major part of Balochistan lies in the arid zone, followed by the hyper-arid in the southwestern part and the semi-arid zones in the northeastern part of the province. SPI and RDI results were found more localized than PD, as PD shows extensive events. Furthermore, principal component analysis shows a significant contribution from all the indices. For SPI, RDI, and PD, the first three principal components have more than 70% share, contributing 73.63%, 74.15%, and 72.30% respectively. By integrating drought patterns, long-term planning, and preparedness to mitigate drought impacts are only possible. The RDI was found more suitable and recommended in case of temperature data availability.

Diagnosis of the Evolutionary Characteristics and Variability of Meteorological Drought in the Yellow River Basin

Frequent occurrences of meteorological droughts in the Yellow River Basin (YRB) result from the combined impact of global climate change and human activities. To address the problems of unclear evolution mechanism and difficulty in accurately determining the variability time of meteorological droughts in the basin, this study uses multi-scale Standardized Precipitation Evapotranspiration Index (SPEI) and integrates wavelet analysis with the Mann-Kendall to investigate the evolution patterns and variability characteristics of meteorological droughts in the basin. The findings indicate that: (1) Meteorological drought shows a trend of shifting from the upper to the middle and lower reaches of the river, with clear seasonal and interannual variability trends. (2) The basin experiences six primary drought periods, with durations ranging from 2 to 6 months and 10 to 18 months, the latter being particularly noteworthy. (3) The main periods of meteorological drought variability are concentrated from 03/2001 to 10/2014, from 06/2006 to 08/2006, from 10/2017 to 01/2019, and 11/2019. This study furnishes a scientific groundwork for enhancing water resource management in the YRB and elucidating the mechanisms underlying meteorological drought evolution. These insights contribute to fostering ecological preservation and facilitating high-quality development within the basin.

Comprehensive propagation characteristics between paired meteorological and hydrological drought events: Insights from various underlying surfaces

Propagation from meteorological to hydrological drought events is crucial for understanding drought variation mechanisms and their consequences. Most previous studies were implemented using various standardized drought indices at month scale, which were difficult to reveal the physical processes and insufficient to characterize the comprehensive propagation characteristics (e.g., propagation time, duration, and severity) from meteorological to hydrological drought events. Furthermore, the impact mechanisms of underlying surfaces on drought propagation remained unclear. This study identified the paired relationships between meteorological and hydrological drought events and investigated their comprehensive propagation characteristics at the hydrologic response unit scale using the Soil and Water Assessment Tool (SWAT), run theory and paired analysis. The impact of underlying surfaces (e.g., land use, soil type, and slope) on drought propagation was further assessed using the Student's t-test at the 95% confident level. The upper middle Yuanjiang River Basin in China, which is prone to drought and exhibits diverse underlying surface conditions, was selected as the study area. Results indicate that the SWAT model optimally simulates the monthly streamflow with the Nash-Sutcliffe efficiency being ≥0.75 and the RMSE-observations standard deviation ratio being ≤0.50. Four main propagation types are identified, i.e., one-to-one, many-to-one, one-to-many, and many-to-many, in which the first two types are the dominant ones, accounting for 86.7% and 13.3% of total paired events, respectively. More than 85% of the study area exhibits a propagation time of ≤2 months, especially in the headwater area and the right bank of Lvzhijiang River. Drought duration and severity are amplified during the propagation process in 60.8% and 60.3% of the study area, respectively. Drought propagation time, duration, and severity are mainly controlled by soil and slope, and are slightly affected by land use type. The propagation time is quite short in areas with a high soil infiltration rate and steep slope, and the drought duration and severity are amplified in areas with a low soil infiltration rate and gentle slope. This study aims to provide deep insights on propagation from meteorological to hydrological drought considering various underlying surfaces, and further provides a scientific basis for the drought propagation mechanism and for drought disaster prevention and adaptation.

Extratropical circulation associated with Mediterranean droughts during the Last Millennium in CMIP5 simulations

Abstract. The Mediterranean region is expected to experience significant changes in hydroclimate, reflected in increases in the duration and severity of soil moisture droughts. While numerous studies have explored Mediterranean droughts in coupled climate models under present and future scenarios, understanding droughts in past-climate simulations remains relatively underexplored. Such simulations can offer insights into long-term drought variability that observational records cannot capture. Therefore, our study investigates circulation patterns in the Euro-Atlantic domain associated with multi-year soil moisture droughts over the Mediterranean region during the last millennium (850–2005 CE) in climate simulations. For this, we use the fifth phase of the Climate Model Intercomparison Project–Paleoclimate Model Intercomparison Project Phase 3 (CMIP5–PMIP3) and the CESM Last Millennium Ensemble Project. Primarily, we examine the differences among the models in representing drought variability and related circulation patterns. For the analysis, we exclude the anthropogenic trends from 1850–2005 CE, and to detect the circulation patterns, we perform k-means clustering combined with linear correlation analyses. The findings confirm that Mediterranean drought occurrence during the last millennium is associated with internal variability in the climate system. Drought variability, the associated circulation patterns, and the frequencies of these patterns vary across the models. Some climate models exhibit a multidecadal anti-phase occurrence of some drought periods between the western and eastern Mediterranean regions, although the exact periods of coherence differ among the models. This anti-phase co-variability, which agrees with some proxy records, can be explained by the dominant circulation patterns in each region detected by the models: western Mediterranean droughts are dominated by a high-pressure system over central Europe and a North Atlantic Oscillation (NAO)-like pattern, while eastern Mediterranean droughts are linked to positive pressure anomalies in the southern and eastern Mediterranean and negative NAO, East Atlantic, and East Atlantic–western Russia-like patterns. The frequencies of these modes of climate variability are strongly model-dependent; i.e., some patterns occur more frequently or only in some models, suggesting that the main drivers of droughts differ among the models. Although it is complicated to evaluate the representation of droughts and associated circulation among the models, in general, the models with lower horizontal and vertical spatial land resolutions exhibit drought variability and patterns that distinctly differ from other models. These model differences and preferences toward some circulation patterns can be a source of uncertainties in the model–proxy comparison of Mediterranean droughts and potentially influence future climate projections.

Effect of aridity on the β-diversity of alpine soil potential diazotrophs: insights into community assembly and co-occurrence patterns.

Microbial diversity plays a vital role in the maintenance of ecosystem functions. However, the current understanding of mechanisms that shape microbial diversity along environmental gradients at broad spatial scales is relatively limited, especially for specific functional groups, such as potential diazotrophs. Here, we conducted an aridity-gradient transect survey from 60 sites across the Tibetan Plateau, the largest alpine ecosystem of the planet, to investigate the ecological processes (e.g., local species pools, community assembly processes, and co-occurrence patterns) that underlie the β-diversity of alpine soil potential diazotrophic communities. We found that aridity strongly and negatively affected the abundance, richness, and β-diversity of soil diazotrophs. Diazotrophs displayed a distance-decay pattern along the aridity gradient, with organisms living in lower aridity habitats having a stronger distance-decay pattern. Arid habitats had lower co-occurrence complexity, including the number of edges and vertices, the average degree, and the number of keystone taxa, as compared with humid habitats. Local species pools explained limited variations in potential diazotrophic β-diversity. In contrast, co-occurrence patterns and stochastic processes (e.g., dispersal limitation and ecological drift) played a significant role in regulating potential diazotrophic β-diversity. The relative importance of stochastic processes and co-occurrence patterns changed with increasing aridity, with stochastic processes weakening whereas that of co-occurrence patterns enhancing. The genera Geobacter and Paenibacillus were identified as keystone taxa of co-occurrence patterns that are associated with β-diversity. In summary, aridity affects the co-occurrence patterns and community assembly by regulating soil and vegetation characteristics and ultimately shapes the β-diversity of potential diazotrophs. These findings highlight the importance of co-occurrence patterns in structuring microbial diversity and advance the current understanding of mechanisms that drive belowground communities.IMPORTANCERecent studies have shown that community assembly processes and species pools are the main drivers of β-diversity in grassland microbial communities. However, co-occurrence patterns can also drive β-diversity formation by influencing the dispersal and migration of species, the importance of which has not been reported in previous studies. Assessing the impact of co-occurrence patterns on β-diversity is important for understanding the mechanisms of diversity formation. Our study highlights the influence of microbial co-occurrence patterns on β-diversity and combines the drivers of community β-diversity with drought variation, revealing that drought indirectly affects β-diversity by influencing diazotrophic co-occurrence patterns and community assembly.

Spatial-temporal variations and drivers of the compound dry-hot event in China

Compound extremes such as compound dry-hot events (CDHEs) have received more attention in the last decade due to their more devastating impacts than those caused by droughts or heatwaves separately. A daily-resolution CDHE index, i.e., compound dry-hot index daily (CDHId), based on the copula and conditional probability is proposed to identify dry and hot days to quantify the CDHE severity. Standardized precipitation index (SPI), standardized temperature index (STI), and CDHId are used to explore the spatial-temporal variations of droughts, heatwaves, and CDHEs in China from 1961 to 2020. Results show that CDHEs occurred more frequently after the period from the late 1970s to the early 1980s. Northeast China, Southwest China, and the Tibetan Plateau witnessed the most significant increases in CDHEs. CDHEs are further classified into two types based on the sequential order of the drought and heatwave occurrence, and the drought-preceded CDHEs accounted for 85.2% of all events, indicating that CDHEs were more likely to be induced by antecedent dry conditions. Stronger land-atmosphere coupling was observed both prior to and during CDHEs compared to periods under non-dry-hot conditions, which played a major role in the formation of CDHE at the local and short-time scale. However, the annual variation of CDHE frequency in multi-decades was dominated by heatwaves, with a more significant direct path coefficient than droughts over China. Overall, the increase and enhancement of CDHEs since the early 1980s were consistent with global warming.

FIND: A Synthetic weather generator to control drought Frequency, Intensity, and Duration

Water systems worldwide are experiencing climate change-induced shifts in drought properties like frequency, intensity, and duration, affecting water security and reliability. To develop and test effective drought preparedness plans, researchers often use synthetic weather generators to create hydrological scenarios that explore drought variability beyond historical records. Existing weather generators typically allow users to adjust streamflow statistics like percentiles or temporal correlation but do not directly control drought properties of frequency, intensity, and duration. To fill this gap, we propose FIND (Frequency, INtensity, and Duration) synthetic weather generator. FIND incorporates a standardized drought index to directly and independently control drought frequency, intensity, and duration in generated streamflow time series while preserving observed hydrological variability. Use cases for FIND include (i) water systems analysis applications that seek to train and test drought strategies under historical and plausible future drought conditions, and (ii) bottom-up vulnerability studies relating system vulnerability outcomes to specific changes in drought properties of frequency, intensity, and duration. We demonstrate FIND’s versatility through three experiments: replicating historically observed drought properties, generating streamflow scenarios for multiple sites preserving correlation between their drought conditions, and generating a set of scenarios with direct and independent changes in drought properties. FIND source code is openly available for applications beyond the scope of this paper.

Analysis of spring drought in Northeast China from the perspective of atmosphere, snow cover, and soil

Northeast China is an important grain-producing area, and spring is the sowing time for crops. Drought hinders crop germination and leads to crop failure. Spring drought analysis helps to understand the characteristics of regional spring drought and provides a reference for formulating disaster prevention and reduction measures. Considering the characteristics of seasonally frozen soil regions in northeastern China, sampling at a resolution of 0.5 degrees, accounting for the snow cover factors in the early spring, as well as precipitation, temperature, evapotranspiration, and soil moisture during the spring planting period, and uses the projection pursuit information entropy model to analyze the spatial and temporal variability of spring drought in Northeast China. In the model, a new method was proposed to calculate the cutoff radius by adjusting the radius size with the parameter. The optimal parameters were ultimately determined using the Shapiro-Wilk test, Kolmogorov-Smirnov test, and Epps-Pulley test. The results are as follows: drought is relatively severe in the eastern parts of Inner Mongolia, as well as in the northwest of Liaoning. The central and northern parts of Inner Mongolia, the northern and northeastern parts of Heilongjiang, the southeastern parts of Jilin, and the eastern parts of Liaoning are relatively humid, while the drought situation in other regions is relatively moderate. Regional spring drought shows an increasing trend, and most regions show statistical significance. Areas with high temperatures and low precipitation, as well as low snow cover in the early spring, are prone to spring drought. Moist regions are characterized by high precipitation, low evapotranspiration, and abundant snow resources.

Monitoring spatiotemporal and seasonal variation of agricultural drought in Bangladesh using MODIS-derived vegetation health index

Monitoring spatiotemporal and seasonal variation of agricultural drought in Bangladesh using MODIS-derived vegetation health index

Assessing the impact of meteorological and agricultural drought on maize yields to optimize irrigation in Heilongjiang Province, China

Agriculture is an essential support for social and economic development, most affected by weather and climate. Drought in agriculture significantly threatens food security and social stability. Understanding drought variability in the cultivated land can lay the foundation for crop management. Considering the effects of drought on the actual crop growth process and precise irrigation under limited water resources is a great challenge. In this study, standardized precipitation evapotranspiration index (SPEI) and soil water content were used to study the spatiotemporal characteristics of drought during maize growth in Heilongjiang Province. The distributed AquaCrop model and grey theory were used to study the relationship between irrigation, drought and maize yield at the grid scale, and the current irrigation effect was evaluated by simulating the comparison of crop yield under non-irrigation and irrigated conditions, so as to provide a basis for optimizing the irrigation system in the future. In addition, Future drought trends were also examined using the Mann-Kendall statistical test, Sen's slope, and Hurst index. The results are as follows: (1) Based on remote sensing inversion and distributed AquaCrop model, the relationship between drought and crop yield can be studied at grid scale, which can refine the impact of drought on crop yield in different cells. (2) Irrigation can increase crop yields by at least 20–40% in about 60% of areas in the Heilongjiang Province. (3) In response to the drought characteristics of alternating wet and dry variations or consistent wet and dry variations in different months, inter-regional water transfer can be used to cope with or ensure increased irrigation in drought-prone months (May and June) to achieve water conservation and efficiency. Evaluating the current irrigation effect by simulating crop yield under non-irrigated conditions and crop yield under irrigated conditions can provide a better theoretical basis for optimizing irrigation systems, in order to improve regional crop yields and reduce drought risks.

Spatio-temporal variation and dynamic risk assessment of drought and flood disaster (DFD) in China

It is important to understand the variations of Drought-Flood-Disaster (DFD) from the past to future for disaster management decision-making under the backdrop of global warming. This study explored the spatio-temporal variations of DFD risks in China from the past (2000–2020) to future (2020–2100) based on the natural and socio-economic datasets. The main findings include: (1) The spatial pattern of disaster vulnerability decreased from 2000 to 2100. The overall vulnerability distribution showed a spatial pattern of high east and low west, and its eastern distribution presented high north and low south. (2) The drought hazard danger degree showed a trend of decreasing first and then increasing with obvious spatial heterogeneity. The flood hazard danger degree had a decreasing spatial distribution from southeast to northwest, with an overall gradually increasing trend. (3) The DFD risks showed a spatial pattern of high east and low west, and were more closely related to disaster vulnerability. Overall, the flood and drought risks had good consistency at the highest level (VI), mainly distributed in the North China Plain, Northeast Plain, eastern Sichuan, and southern Guangdong. This level means that the most severe damage to life and property will occur in these regions. (4) The DFD showed the direction of “north(east)-south(west)”, and the main axis of the ellipse moved north eventually. The DFD hot spots were mainly distributed in North China and the middle and lower reaches of the Yangtze River. The DFD cold spots were mainly distributed in the southwest, Qinghai-Tibet region, and Gansu province.

GRACE-based groundwater drought in the Indochina Peninsula during 1979–2020: Changing properties and possible teleconnection mechanisms

Groundwater is very important for human productivity and daily life, hydrological cycle regulation, and ecosystem stability. However, due to the complex mechanisms of groundwater drought, the spatial and temporal variations of groundwater drought and its driving mechanisms are still not fully understood, especially in Indochina Peninsula. In this work, we used a reconstructed long-term terrestrial water storage dataset from the Gravity Recovery and Climate Experiment (GRACE) emission and a GRACE-based groundwater drought index to investigate the spatial and temporal characteristics of groundwater drought during 1979–2020 in the Indochina Peninsula. The possible teleconnection mechanisms between groundwater drought and the Indian Ocean Dipole (IOD), El Niño-Southern Oscillation (ENSO), and El Niño Modoki (ENSO_M) were also investigated using cross wavelet transform method. The results show that groundwater drought worsens significantly during 1979–2020, and becomes much more frequent and intensified after 2000 in the southern Indochina Peninsula. Both univariate and bivariate (logic ‘or’ and ‘and’) return periods for duration, severity, and peak of groundwater drought are short in the southern Indochina Peninsula, and thus the risk of groundwater drought is high. The IOD, ENSO, and ENSO_M can reduce the intensity of groundwater drought to a certain extent during the warm phases, but only ENSO_M tends to significantly exacerbate the intensity of groundwater drought during the cold phases in the southern Indochina Peninsula. The variations in groundwater drought are dominated by ENSO_M, and are also coupled influenced by the IOD and ENSO in the southern Indochina Peninsula. The results provide valuable information for the sustainable ecological environment and socioeconomic development, especially development of groundwater drought early warning and prediction models in the Indochina Peninsula.

Analyzing Temporal Patterns of Temperature, Precipitation, and Drought Incidents: A Comprehensive Study of Environmental Trends in the Upper Draa Basin, Morocco

Quantifying variation in precipitation and drought in the context of a changing climate is important to assess climate-induced changes and propose feasible mitigation strategies, particularly in agrarian economies. This study investigates the main characteristics and historical drought trend for the period 1980–2016 using the Standard Precipitation Index (SPI), Standard Precipitation Evaporation Index (SPEI), Run Theory and Mann–Kendall Trend Test at seven stations across the Upper Draa Basin. The results indicate that rainfall has the largest magnitude over the M’semrir and Agouim (>218 mm/pa) and the lowest in the Agouilal, Mansour Eddahbi Dam, and Assaka subregions (104 mm–134 mm/pa). The annual rainfall exhibited high variability with a coefficient of variation between 35−57% and was positively related to altitude with a correlation coefficient of 0.86. However, no significant annual rainfall trend was detected for all stations. The drought analysis results showed severe drought in 1981–1984, 2000–2001, and 2013–2014, with 2001 being the driest year during the study period and over 75% of both SPEI and SPI values returned drought. Conversely, wet years were experienced in 1988–1990 and 2007–2010, with 1989 being the wettest year. The drought frequency was low (<19%) across all the timescales considered for both SPI and SPEI, with Mansour Eddahbi Dam and Assaka recording the highest frequencies for SPI-3 and SPEI-3, respectively.

Spatiotemporal Changes and the Prediction of Drought Characteristics in a Major Grain-Producing Area of China

Understanding variations in drought characteristics is of great importance for water resource planning and agriculture risk management. Despite increasing interest in exploring spatiotemporal drought patterns, long-term drought event characteristics and their future changes are unclear in major grain-producing areas in China. In this study, we applied Run theory, Sen’s slope, the modified Mann–Kendall method, wavelet analysis, and three machine learning models to systematically examine drought variation patterns, their future trends, and agricultural exposure in Henan Province, China, from 1961 to 2019. The results indicated that the SPEI-12 showed a significant increase at a rate of 0.0017/month during 1961–1999, but this has gradually changed to a drying trend since the 21st century. Drought event characteristics shifted markedly during these two periods, with drought duration and severity gradually shifting from east to west. The BO-LSTM model performed better than the LSTM and BP models, indicating that the drought frequency, higher drought duration, and drought peak would greatly increase 1.28–3.40-fold and cropland exposure is predicted to increase 1.61-fold in the near future compared to the first two decades of the 21st century. This finding not only helps developing meteorological drought predicting models, but also provides the scientific groundwork for drought disaster prevention and mitigation in Henan Province.

Correspondence of Drought Occurrences at Multi‐Temporal Scales Between North China and Upper Hanjiang River

AbstractUsing the drought and flood grades, the historical co‐drought probabilities of the water source area (i.e., the Upper Hanjiang River or UH) and the receiving area (i.e., North China or NC) of the Middle Route of the South‐to‐North Water Diversion project from 1470 to 2017 were analyzed. It was found that there is relatively high possibility for co‐droughts to occur in the UH and NC at interannual to multi‐decadal time scales. When extreme drought occurred in NC, there was a 52% probability that the UH was on the drier side and even a 40% probability of severe drought. During the three typical severe drought events that occurred mainly in NC (i.e., 1637–1643, 1877–1878, and 1997–2002), severe droughts also appeared in the UH, with 1877–1878 even more severe than in NC. Among the seven driest years of the study period in NC (i.e., 1640, 1641, 1832, 1920, 1965, 1968, and 1997), only 1832 was wet in the UH, and 1920 even experienced the same severe region‐wide drought as NC did. Furthermore, when severe consecutive droughts occurred in NC, there was at least a 66% probability that the UH was also experiencing a drought. In addition, there were obvious cycles of drought and flood variability of around 3–6 years, 10 years, 30 years, and 55–80 years in both the UH and NC. These findings are of importance to in‐depth understanding of the regional drought variability and its mechanism at varied temporal scales and the effective management of the world‐class hydro project.

Drought variability, changes and hot spots across the African continent during the historical period (1928–2017)

AbstractThe spatiotemporal variability of meteorological droughts, its changes and hot spots location across Africa are analysed for the period spanning 1928–2017 using the Standardized Precipitation Index (SPI) applied to the precipitation products from the Climatic Research Unit (CRU), University of Delaware (UDEL) and Global Precipitation Climatology Centre (GPCC). Spatially, an analysis based on rotational empirical orthogonal function identifies five regions of similar drought variability, namely the Sahel, East Africa, East Southern Africa, West Southern Africa and the Gulf of Guinea. Temporally, the most common periods of drought occurrence are the 1970s, the 1980s and, to a lesser extent, the 1990s. Changes in drought characteristics for the intermediate past (1958–1987) and recent past (1988–2017) compared to the far past (1928–1957) indicate robust increases of drought duration, frequency and severity in the Sahel, and to a lower extent in the Gulf of Guinea, some areas of Central Africa, part of Southern Africa and over Madagascar. These changes are stronger (weaker) along the Sahel during the intermediate past (recent past) and stronger (weaker) over Central and Southern Africa and Madagascar during the recent past (intermediate past). As a consequence, drought hot spots, mostly driven by severity during the regions' wet season, are identified in areas confined in the Sahel during the intermediate past and in regions mainly over Central and Southern Africa and Madagascar during the recent past. Our results are useful for drought disaster risk management across Africa and provide a valuable reference for future drought analysis under global warming conditions.

Understanding the Contributions of Paleo‐Informed Natural Variability and Climate Changes to Hydroclimate Extremes in the San Joaquin Valley of California

AbstractTo aid California's water sector to better understand and manage future climate extremes, we present a method for creating a regionally consistent ensemble of plausible daily future climate and streamflow scenarios that represent natural climate variability captured in a network of tree‐ring chronologies, and then embed anthropogenic climate change trends within those scenarios. We use 600 years of paleo‐reconstructed weather regimes to force a stochastic weather generator, which we develop for five subbasins in the San Joaquin Valley of California. To assess the compound effects of climate change, we create temperature series that reflect projected scenarios of warming and precipitation series that have been scaled to reflect thermodynamically driven shifts in the distribution of daily precipitation. We then use these weather scenarios to force hydrologic models for each of the five subbasins. The paleo‐forced streamflow scenarios highlight periods in the region's past that produce flood and drought extremes that surpass those in the modern record and exhibit large non‐stationarity through the reconstruction. Variance decomposition is employed to characterize the contribution of natural variability and climate change to variability in decision‐relevant metrics related to floods and drought. Our results show that a large portion of variability in individual subbasin and spatially compounding extreme events can be attributed to natural variability, but that anthropogenic climate changes become more influential at longer planning horizons. The joint importance of climate change and natural variability in shaping extreme floods and droughts is critical to resilient water systems planning and management in the San Joaquin.

Spatiotemporal variations of drought and driving factors based on multiple remote sensing drought indices: A case study in karst areas of southwest China

Spatiotemporal variations of drought and driving factors based on multiple remote sensing drought indices: A case study in karst areas of southwest China

An appraisal of the local‐scale spatio‐temporal variations of drought based on the integrated GRACE/GRACE‐FO observations and fine‐resolution FLDAS model

AbstractThe gravity recovery and climate experiment (GRACE) observations have so far been utilized to detect and trace the variations of hydrological extremes worldwide. However, applying the coarse resolution GRACE estimates for local‐scale analysis remains a big challenge. In this study, a new version of the fine resolution (1 km) Famine early warning systems network Land Data Assimilation System (FLDAS) model data was integrated into a machine learning model along with the GRACE data to evaluate the subbasin‐scale variations of water storage, and drought. With a correlation of and a root mean square error (RMSE) of of its results, the downscaling model turned out to be very successful in modelling the finer resolution variations of TWSA. The water storage deficit (WSD) and Water Storage Deficit Index (WSDI) were used to determine the episodes and severity of drought events. Accordingly, two severe droughts (January 2008 to March 2009 and September 2019 to December 2020) were discerned in the Kizilirmak Basin (KB) located in Central Türkiye. The characterization of droughts was evaluated based on WSDI, scPDSI, and model‐based drought indices of the soil moisture storage percentile (SMSP) and groundwater storage percentile (GWSP). The results indicated discrepancies in the drought classes based on different indices. However, the WSDI turned out to be more correlated with GWSP, suggesting its high ability to monitor groundwater droughts as well.