Months Of Drought Research Articles

Resilience to drought and climate change disasters and its determinants in the heterogeneous pastoral Ethiopia

Disastrous livestock losses have been documented over long periods in pastoral Ethiopia, and this challenge has remained unresolved. Nevertheless, this issue has received less attention than it deserves. This study estimated resilience of households to drought and climate change using survey data collected from 2756 households in the four pastoral regions of Ethiopia. A two-step approach, along with factor analysis, was followed to estimate resilience by household categories, intervention groups, and regions. Following this, tobit model was estimated to identify factors influencing resilience. The results indicated, (1) the average resilience estimated for treated and untreated groups range from 0.32 to 0.90 and from 0.32 to 0.55, respectively. (2) The components of income and food-access, public services, social safety net, and liquid and non-liquid assets boosted the estimated resilience. To those components, daily per-capita income and expenditure, food-insecurity, health-post, mobility, time-efficient food-aid, livestock-size and diversity, and irrigated land contributed most. (3) The estimated tobit model indicated months of drought, whether households produce or purchase grain for consumption, among others, significantly influenced resilience. To improve resilience, the study advises diversified income, school-feeding, market access, water points, and timely food-aid. Over time, transformative investments in road and irrigation, augmented by technology and training for forage and crop production require attention.

Spatiotemporal variability of rainfall and drought characterization in Kaduna, Nigeria

Rainfall variability and drought events can affect food security globally. This study aimed to assess the spatial and temporal trends and variability of rainfall in Kaduna State, Nigeria. Gridded rainfall data were obtained from the Climate Research Unit (CRU_TS 4.07) (1952–2022) for Birnin Gwari, Kaduna, Kafanchan and Zaria towns. The rainfall data were subjected to the Anderson‒Darling normality test and found to be normally distributed. The data were analysed using the coefficient of variation (CV), rainfall anomaly index (RAI) and precipitation concentration index (PCI). The trend was assessed using the Mann‒Kendall trend test, and finally, meteorological drought was computed using the standardized precipitation index (SPI). The results revealed that all four locations had low to moderate variability, with CVs < 15%. The rainfall anomaly index revealed that 1983 was the driest year for Birnin Gwari, Kaduna and Kafanchan, with RAI values of − 4.863, − 4.474 and − 4.316, respectively, while in Zaria, the driest year was 1974, with a RAI value of − 4.065. The PCI showed that there was a high concentration of rainfall in Birnin Gwari, Kaduna, and Kafanchan. However, Zaria experienced 41 years of high concentrations and 30 years of very high concentrations of precipitation. The Mann‒Kendall trend test revealed that all four locations experienced a significant downward trend in rainfall within the study period. The Z statistics for Birnin Gwari, Kaduna, Kafanchan and Zaria were − 1.112, − 0.357, − 0.556 and − 0.764, respectively, all indicating decreasing rainfall amounts. Finally, the SPI Birnin Gwari and Kaduna experienced 18 months of severe drought, with maximum intensities of − 2.671 and − 3.111, respectively. Kafanchan experienced 25 months of drought with a maximum intensity of − 2.643, while Zaria experienced 30 months of drought with a maximum intensity of − 3.069. These severe droughts occurred from the 1970s to the 1990s. The study concluded that rainfall concentrations were mostly high and very high, and severe, catastrophic drought events occurred in the 1970s and 1980s.

Estimating Drainage from Forest Water Reclamation Facilities Based on Drain Gauge Measurements

A growing human population requires sustainable solutions to regulate and dispose of municipal wastewater. Water treatment facilities in northern Idaho are permitted to apply reclaimed wastewater to forest land during the growing season at specified monthly hydraulic loading rates. We assessed the spatial and temporal variability of drainage below the rooting zone between non-irrigated (control) and irrigated (effluent) stands during the growing and dormant seasons in 2021. No drainage was observed during the two months of annual seasonal drought, but large magnitudes of drainage were recorded during the dormant season (38–94 cm), which was consistent with seasonal precipitation. The overall effect of effluent treatment on the drain gauge measurements did not differ from the controls, as effluent only increased the drainage at some facilities. The measured drainage averaged from 35 to 62 cm among facilities. We then used the drainage measurements to calibrate hydrological models (Hydrus-1D and Water Erosion Prediction Project [WEPP]) and predict the drainage in 50 measurement plots distributed evenly among five forest water reclamation facilities. As with the observed drainage, there were no statistically significant growing season differences in the predicted monthly drainage during the growing season between the effluent and control plots, suggesting the successful use of hydrologic models to support the measured drainage findings. While both models struggled to accurately predict the quantity of drainage during the dormant season, they both successfully predicted that drainage would continue through May. WEPP also successfully predicted that the treated plots began to drain in September and October following late-season irrigation at some facilities. The models showed that the prescribed crop coefficient used by the Idaho Department of Environmental Quality was adequate in avoiding drainage during the peak summer months.

Spatiotemporal dynamics of meteorological and agricultural drought, part of Manbhum-Singhbhum Plateau (India): Four decades study using NASA POWER and MODIS data

Drought is an extremely hazardous situation that predominantly affects ecosystems, hydrological systems, and agricultural mechanisms in different pockets of the world. Management of water resources in dry and semi-arid environments has become a critical challenge in the last few decades. The principal objectives of this study are (i) to categorize the severity and frequency of drought events using the Reconnaissance Drought Index and Rainfall Deviation Index and ii) to evaluate the spatial extension of drought in particular drought times of severe and extreme droughts through Remote Sensing Drought Indices (RSDIs). This drought monitoring index is commonly used index for its high degree of resilience and sensitivity to droughts. The result shows that severe to extreme drought occurred in Bero, Tulin, Sirkabad, Manbazar and Bundwan which are 22, 28, 23, 14 and 25 months correspondingly based on RDI3 whereas RDI12 values indicated 26, 47, 42, 22 and 38 months in the study period (1981 to 2021). Bundwan area faced the most extreme drought occurrence in May month of 1996 with −3.58 values followed by Sirkabad, Bero, Manbazar and Tulin. Manbazar is going through severe to extreme drought months (for short time) whereas ‘extreme drought’ frequency (1.67 % to 1.05 %) is higher in the western part mainly in Jhalda I, Jhalda II, Bagmundi, and Arsha blocks of Purulia district (part of Manbhum Singhbhum Plateau). Additionally, the recurrence of ‘moderate drought’ is much greater in Balarampur along with some portions of Purulia I block. The whole study can be summarized as the northeastern portion being challenged with moderate or severe drought conditions while mild or severe drought is a considerable recurrence in the northern section. The outcome of this study will be helpful for local planners and management officials during implementation strategies related to water resource management.

Enhancing a machine learning model for predicting agricultural drought through feature selection techniques

This study aims to determine the crucial variables for predicting agricultural drought in various climates of Iran by employing feature selection methods. To achieve this, two databases were used, one consisting of ground-based measurements and the other containing six reanalysis products for temperature (T), root zone soil moisture (SM), potential evapotranspiration (PET), and precipitation (P) variables during the 1987–2019 period. The accuracy of the global database data was assessed using statistical criteria in both single- and multi-product approaches for the aforementioned four variables. In addition, five different feature selection methods were employed to select the best single condition indices (SCIs) as input for the support vector regression (SVR) model. The superior multi-products based on time series (SMT) showed increased accuracy for P, T, PET, and SM variables, with an average 47%, 41%, 42%, and 52% reduction in mean absolute error compared to SSP. In hyperarid climate regions, PET condition index was found to have high relative importance with 40% and 36% contributions to SPEI-3 and SPEI-6, respectively. This suggests that PET plays a key role in agricultural drought in hyperarid regions because of very low precipitation. Additionally, the accuracy results of different feature selection methods show that ReliefF outperformed other feature selection methods in agricultural drought modeling. The characteristics of agricultural drought indicate the occurrence of drought in 2017 and 2018 in various climates in Iran, particularly arid and semi-arid climates, with five instances and an average duration of 12 months of drought in humid climates.

Development of a probabilistic agricultural drought forecasting (PADF) framework under climate change

Drought has significant impacts on human survival and social development, particularly on crop production. Agricultural drought is the most direct consequence of drought on crops. In this study, a Probabilistic Agricultural Drought Forecasting (PADF) framework was developed to employ the Ensemble Bayesian Least Square Support Vector Machine (EBLSSVM) method for bias correction in precipitation and temperature projections from multiple Regional Climate Models (RCMs). Vine Copula-Based Projection Model (VCPM) was then developed for accurate agricultural drought projections, providing deterministic results and valuable 90 % predictive intervals. The results indicate that the EBLSSVM method can generate better climate projections than the original outputs from RCMs and bias-corrected results from other bias-correction techniques. Based on the projection results from VCPM, the study found that drought will be a significant concern in Fujian province, especially in the southeast coastal region. Drought conditions are projected to be more severe in the 2050s than in the 2080s, under both RCP4.5 and RCP8.5. The average SSI values during months with a wet trend ranged from 0.1 to 0.3, whereas months with a drought trend predominantly exhibited average SSI values exceeding -0.5. Notably, SSI values as low as -2.0 were observed during wet trend months, underscoring the urgency of addressing future drought, particularly in coastal regions. However, even during wet periods, at least one extreme drought month is expected, suggesting that extreme drought conditions will become more severe in the future. CMIP5 and CMIP6 predictions showed good consistency in temporal and spatial dimensions, with CMIP6 indicating more significant and consistent future drought changes compared to CMIP5.

Propagation Dynamics from Meteorological Drought to GRACE-Based Hydrological Drought and Its Influencing Factors

Gaining a comprehensive understanding of the characteristics and propagation of precipitation-based meteorological drought to terrestrial water storage (TWS)-derived hydrological drought is of the utmost importance. This study aims to disentangle the frequency–time relationship between precipitation-derived meteorological and TWS-based hydrological drought from June 2002 to June 2017 based on the Standardized Precipitation Index (SPI) and Standardized Terrestrial Water Storage Index (STI) by employing wavelet coherence rather than a traditional correlation coefficient. The possible influencing factors on drought propagation in 28 regions across the world are examined. The results show that the number of drought months detected by the STI is higher than that detected by the SPI worldwide, especially for slight and moderate drought. Generally, TWS-derived hydrological drought is triggered by and occurs later than precipitation-based meteorological drought. The propagation characteristics between meteorological and hydrological droughts vary by region across the globe. Apparent intra-annual and interannual scales are detected by wavelet analysis in most regions, but not in the polar climate region. Drought propagation differs in phase lags in different regions. The phase lag between hydrological and meteorological drought ranges from 0.5 to 4 months on the intra-annual scale and from 1 to 16 months on the interannual scale. Drought propagation is influenced by multiple factors, among which the El Niño–Southern Oscillation, North Atlantic Oscillation, and potential evapotranspiration are the most influential when considering one, two, or three factors, respectively. The findings of this study improve scientific understanding of drought propagation mechanisms over a global scale and provide support for water management in different subregions.

Spatiotemporal assessment of rainfall and drought projection for integrated dam management in Benut River Basin, Malaysia under CMIP6 scenarios

This study assesses the influence of climate change on rainfall and drought in the Benut River Basin (BRB) to support the integrated management of Machap dam. The study seeks to reshape dam safety components in the near future through a technical focus group discussion (FGD) with key stakeholders. Utilizing the Coupled Model Intercomparison Project Phase 6 (CMIP6) dataset for the immediate future (2020–2040) under various scenarios (SSP1–2.6, SSP2–4.5, SSP3–7.0, and SSP5–8.5), historical Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) rainfall datasets (1981 to 2021) are employed. A multi-filtration process ranks twenty-three Global Climate Models (GCMs) using seven relative importance metrics (RIMs). This work's novelty lies in a focused GCM evaluation through individual contributions quantified with RIMs, providing a refined ranking that address the limitations of traditional metrics. Then, the Compromise Programming Index (CPI) aggregates the ranked models, with the top subset selected through Jenks Optimised Classification (JOC), identifying ACCESS-ESM1–5 and CMCC-ESM2 as top models. The selected GCMs were bias-corrected using the linear scaling method and validated before ensembled, effectively replicating the probability distribution function (PDF) of CHIRPS data, as confirmed by a Taylor diagram indicating the closest agreement. The study reveals a generally wetter tendency in the northernmost area of Machap dam under all SSPs, with 5–9 % maximum increasing percentages. Conversely, downstream areas anticipate decreasing rainfall. June (6–22 %) and July (7–22 %) project higher rainfall, indicating increased water availability in a relatively dry period, while December (3–11 %) suggests increasing flood risk. The South West monsoon (SWM) anticipates lower rainfall in early March (3–7 %) and more severe dry periods in August (8–11 %). Future drought occurrences are projected homogeneously across scenarios, with drought months ranging from 15 % to 19 % of the 252 months under all severity classifications. In particular, the study enhances myDAMS by proposing continuous development of the guideline under diverse scenario for Machap dam's overall management and sustainability. Projected scenarios, coupled with outcomes from FGD, can inform basin-scale dam management, aiding risk mitigation for critical dam infrastructure.

Spatial–temporal characterization of droughts in Angola

AbstractThis study presents a scientific study conducted in Angola, focusing on the impact and characteristics of drought events in the country. The research endeavours to assess the primary climatic conditions linked to drought events within Angola, including an investigation into their spatiotemporal patterns. To achieve this, an evaluation of drought events’ frequency, duration and intensity has been carried out employing the Standardized Precipitation Index (SPI). Furthermore, the extent of affected regions has been determined using the Integrated Drought Index (IDI). For this, the frequency, duration and intensity of drought events are evaluated using the Standardized Precipitation Index (SPI). The assessment of the affected areas was carried out using the Integrated Drought Index (IDI). The results showed that Angola was repeatedly affected by drought events. The longest drought events were identified in the South and Center regions of the country. In the South region, the longest drought occurred from 1992 to 1997, totaling 83 consecutive months of drought in the region, in the Center the longest event occurred during the years 1994 to 1997, and in the North region between 2003 and 2005, totaling 46 and 23 months, respectively. The climatic conditions evaluated for the drought events studied (1989/1990, 1994/1995, 2014/2015 and 2018/2019) showed that most drought events in the country are associated with the variation of sea surface temperatures in the South Atlantic Ocean. The analysis of the drought category showed that during the years analysed, about 29.7% of the territorial extension of Angola were affected by drought events in the severe to exceptional category.

Potential for Saving Drinking Water Through the Use of Rainwater in Social Housing in Viçosa-Brazil

[Objective] The main objective of this research was to evaluate the potential for saving drinking water by using rainwater as a source of supply for non-potable purposes in two neighborhoods with social housing in the municipality of Viçosa, Minas Gerais, Brazil. [Methodology] The consumption statistics for each month of 2020 were used for each of the homes comprising the Benjamin José Cardoso and Sol Nascente Housing Complexes, and the fraction of drinking water that is destined in homes for non-potable purposes was estimated. The information corresponding to the monthly rainfall records of the last 50 years was analyzed and the monthly volume of rainwater that could be harvested in each house was calculated. [Results] The average monthly volume of rainwater that could be captured through the roof area of each dwelling is 3.39 m3. During the rainy months of the year, it would be feasible to save a higher percentage of water than that allocated for non-potable purposes. Sizing a rainwater reservoir that exceeds the monthly needs for non-potable purposes would allow the surplus of collected water to supply the liquid during the dry season. [Conclusions] Since the average percentage of savings in drinking water for both neighborhoods exceeded 53%, the saving of the monthly consumption can contribute to the reduction of payments for the drinking water service and the consumption of the liquid in the municipality, particularly during drought months.

Increased drought and extreme events over continental United States under high emissions scenario

The frequency, severity, and extent of climate extremes in future will have an impact on human well-being, ecosystems, and the effectiveness of emissions mitigation and carbon sequestration strategies. The specific objectives of this study were to downscale climate data for US weather stations and analyze future trends in meteorological drought and temperature extremes over continental United States (CONUS). We used data from 4161 weather stations across the CONUS to downscale future precipitation projections from three Earth System Models (ESMs) participating in the Coupled Model Intercomparison Project Phase Six (CMIP6), specifically for the high emission scenario SSP5 8.5. Comparing historic observations with climate model projections revealed a significant bias in total annual precipitation days and total precipitation amounts. The average number of annual precipitation days across CONUS was projected to be 205 ± 26, 184 ± 33, and 181 ± 25 days in the BCC, CanESM, and UKESM models, respectively, compared to 91 ± 24 days in the observed data. Analyzing the duration of drought periods in different ecoregions of CONUS showed an increase in the number of drought months in the future (2023–2052) compared to the historical period (1989–2018). The analysis of precipitation and temperature changes in various ecoregions of CONUS revealed an increased frequency of droughts in the future, along with longer durations of warm spells. Eastern temperate forests and the Great Plains, which encompass the majority of CONUS agricultural lands, are projected to experience higher drought counts in the future. Drought projections show an increasing trend in future drought occurrences due to rising temperatures and changes in precipitation patterns. Our high-resolution climate projections can inform policy makers about the hotspots and their anticipated future trajectories.

Two Large-Scale Meteorological Patterns are Associated with Short-Duration Dry Spells in the Northeastern United States

Abstract Large-scale meteorological pattern (LSMP)–based analysis is used in a novel way to understand meteorological conditions before and during short-duration dry spells over the northeastern United States. These LSMPs are useful to assess models and select better-performing models for future projections. Dry-spell events are identified from histograms of consecutive dry days below a daily precipitation threshold. Events lasting 12 days or longer, which correspond to ∼10% of dry-spell events, are examined. The 500-hPa streamfunction anomaly fields for the first 12 days of each event are time averaged, and k-means clustering is applied to isolate the dry-spell-related LSMPs. The first cluster has a strong low pressure anomaly over the Atlantic Ocean, southeast of the region, and is more common in winter and spring. The second cluster has strong high pressure over east-central North America and is most common during autumn. Over the region, both clusters have negative specific humidity anomalies, negative integrated vapor transport from the north, and subsidence associated with a midlatitude jet stream dipole structure that reinforces upper-level convergence. Subsidence is supported by cold-air advection in the first cluster and the location on the east side of the lower-level high pressure in the second cluster. Extratropical cyclone storm tracks are generally shifted southward of the region during the dry spells. Individual events lie on a continuum between two distinct clusters. These clusters have similar local, but different remote, properties. Although dry spells occur with greater frequency during drought months, most dry spells occur during nondrought months. Significance Statement This study examines the large-scale weather patterns and meteorological conditions associated with dry-spell events lasting at least 2 weeks while affecting the northeastern United States. A statistical approach groups events together on the basis of similar atmospheric features. We find two distinct sets of patterns that we call large-scale meteorological patterns. These patterns reduce moisture, foster localized sinking, and shift the storm track southward along the Atlantic seaboard, all of which reduce precipitation. Besides greater understanding, knowing the meteorological patterns during short-term dryness in the region provides an important tool to assess how well atmospheric models reproduce these specific patterns. More dry spells occur in nondrought months than in drought months, which means that dry spells can occur without preexisting drought conditions.

Potential for reuse of sanitary sewage combined with air conditioning water disinfected by the SODIS process: a case study

The objectives for sustainable development goals (SDGs) are present in the development plans of several educational institutions, aiming to integrate into the world panorama of the collective journey for the development of innovative and transformative actions to build a fairer and more sustainable society. In this sense, the present study is aimed at promoting the objective “Sustainable cities and communities”, in order to evaluate the potential for wastewater reuse and the reduction of surface water exploitation on the Gurupi campus of the Federal University of Tocantins. In this way, this work aims to establish a low-cost way of reuse by combining wastewater from air conditioning and sanitary sewage from the campus, post-treated by the SODIS process. The results showed that reuse in combination requires dilutions with volumes of less than 10% of sanitary sewage and with sun exposure time more than 6 hours at solar intensities above 900 W/m2. The use of air conditioning water disinfected by the SODIS process has greater advantages compared to the combined process in terms of reuse possibilities. So, this study is of great relevance, especially during the six months of drought in the region, which severely compromises the availability of water for irrigation activities, as well as the volume of water in the lake located on the campus.

Cumulative effects of drought have an impact on net primary productivity stability in Central Asian grasslands

Global warming has exacerbated the threat of drought in Central Asia, amplifying its ecological implications within the region's grassland ecosystems. This has become an increasingly prominent issue that requires attention and action. The temporal link between grassland development and drought is asymmetric. However, a quantitative assessment of the temporal effects of multiscale drought on Central Asian grasslands has yet to be explored. Based on correlation analysis and the coefficient of variation method, this study analysed the cumulative and lag effects of multitimescale drought on grassland NPP (net primary productivity) under different climatic zones, altitudes and water availabilities in Central Asia from 1982 to 2018, and discussed the impact of temporal effects on grassland NPP stability. Our results on the cumulative effects of drought on grasslands indicate the 6.72 months preceding NPP measurement was the duration for which, on average, drought was most strongly correlated with NPP. Additionally, we found a mean lagged effect of 5.36 months, meaning that the monthly drought 5.36 months prior to NPP measurement was, on average, most strongly correlated with NPP. The degree to which grassland NPP was affected by cumulative drought at a given level of water availability was inversely proportional to the number of cumulative drought months. Under different water availabilities, the lagged effect of grassland NPP was stronger in dry areas than in wet areas, and the number of lag months tended to decrease and then increase as the water availability increased. The percentage of areas where grassland NPP was dominated by the cumulative and lagging effects of drought was 30.02% and 69.98%, respectively. The stability of grassland NPP was adversely affected by the drought accumulation effect. The findings of this study contribute to a deeper understanding of the long-term effects of drought on grassland ecosystems. Additionally, it will aid in the development of strategies for mitigating and adapting to drought events, thereby minimizing their negative impacts on agriculture, livestock, and ecosystems.

Dry and Wet Period Analysis using Meteorological Drought Indices in Sabarkantha district Gujarat, India

Drought assessment is very important to manage water resources in lean period. In the present study, identification of drought years and extent of deficit of annual rainfall is accomplished by use of three meteorological based drought indices like the Standardized Precipitation Evapotranspiration index (SPEI), China-Z index (CZI) and Modified China-Z index (MCZI) on 1, 3, 6, 9 and 12 month (short term and long term) timescales using monthly precipitation and temperature data from 1901 to 2002 at Sabarkantha to specify the drought conditions in present study area. The analysis of multiple time steps in drought indices make it harder to decide the best time step to show the drought conditions. The months of January, March, November and December have been identified 76, 79, 77 and 80 times as drought months respectively in the 20th century, indicating that these months must be provided with assured Irrigation. It is observed that 1904, 1911, 1915, 1923, 1974, 1987 and 2002 affected by severe drought condition in SPEI-12. The China Z Index and Modified China Z index shows that’s 1904, 1911, 1915, 1918, 1923, 1948, 1951, 1965, 1968, 1969, 1972, 1974, 1985, 1987, 1991, 1995 and 2002 affected by extreme drought. The study also reveals that only 1% year obtain as extreme wet conditions. From result it shows that 23% years are categorised into moderate to extreme drought years, which includes 15% Moderate dry, 8% severe dry years.

Projected increases in extreme drought frequency and duration by 2040 affect specialist habitats and species in Scotland

Abstract Climate‐driven increases in drought occurrence are an overlooked risk in temperate climates, which may be less resilient to water scarcity than arid habitats. Scotland provides an example of a temperate oceanic climate in which drought risk is understudied, but could have substantial ecological impacts, particularly in combination with additional stressors. We modelled changes to risk of extreme drought occurrence in Scotland, and considered potential impacts of these changes on two key habitats, ombrotrophic (precipitation fed) wetlands and temperate rainforest. Using temperature and precipitation data from the UK Climate Projections 2018 and the drought index Standardized Precipitation‐Evapotranspiration Index, we calculated and mapped likely changes in extreme drought for the near future (2021–2040) in comparison to a baseline (1981–2001). We found likelihood of extreme drought events increased from an average of one event every 20 years in the baseline period, to one event every 3 years by 2040. Typical events were projected to be up to 2–3 months longer, with an average of 11 extra drought months per decade. Increases were projected throughout the country, but the effect was most severe in the east, and during autumn. Ombrotrophic wetlands have some level of adaptive resilience to drought, but are considered at high risk as several key sites are in drought hotspot areas. In contrast, Scotland's temperate rainforest is located in lower risk areas, but is typically less drought resilient. Potential impacts on these habitats include reductions in ecosystem services including carbon capture, reduced breeding success for multiple taxa and increased competition among plant communities, which threatens drought‐sensitive species. These projections suggest that climate‐driven drought risk is a significant and imminent threat, even in wet climates. In Scotland, the results can direct mitigation and management actions to areas likely to be at greatest risk, as well as informing conservation interventions that can cope with drought. Additionally, other areas with a temperate oceanic climate may be at risk of extreme drought and could experience similar consequences. Therefore, these results have implications both for facilitating improved resilience to extreme drought in Scotland and for potentially overlooked impacts of drought in oceanic climates elsewhere.

Meteorological Drought Variability over Africa from Multisource Datasets

This study analyses the spatiotemporal variability of meteorological drought over Africa and its nine climate subregions from an ensemble of 19 multisource datasets (gauge-based, satellite-based and reanalysis) over the period 1983–2014. The standardized precipitation index (SPI) is used to represent drought on a 3-month scale. We analyse various drought characteristics (duration, events, frequency, intensity, and severity) for all drought months, and moderate, severe, and extreme drought conditions. The results show that drought occurs across the continent, with the equatorial regions displaying more negative SPI values, especially for moderate and severe droughts. On the other hand, Eastern Sahara and Western Southern Africa portray less negative SPI values. The study also reveals that extreme drought months have the largest interannual variability, followed by all drought months and severe drought months. The trend analysis of SPI shows a significantly increasing trend in drought episodes over most regions of Africa, especially tropical areas. Drought characteristics vary greatly across different regions of Africa, with some areas experiencing longer and more severe droughts than others. The equatorial region has the highest number of drought events, with longer durations for severe and extreme drought months. The Eastern Sahara region has a low number of drought events but with longer durations for moderate, severe, and extreme drought months, leading to an overall higher drought severity over the area. In contrast, Western Southern Africa and Madagascar display a consistently low drought severity for all categories. The study demonstrates the importance of conducting drought analysis for different drought levels instead of using all drought months. Drought management and adaptation strategies need to enhance community resilience to changing drought situations and consider drought variability in order to mitigate different impacts of drought across the continent.

Attribution of air temperature and precipitation to the future global drought events

Quantifying the contributions of air temperature and precipitation changes to drought events can inform decision-makers to mitigate the impact of droughts while existing studies focused mainly on long-term dryness trends. Based on the latest Coupled Model Intercomparison Project (CMIP6), we analyzed the changes in drought events and separated the contributions of air temperature and precipitation to the risk of future drought events. We found that drought frequency, duration, severity, and month will increase in the future (56.4%, 63.5%, 82.9%, and 58.2% of the global land area in SSP245, and 58.1%, 67.7%, 85.8%, and 60.5% of the global land area in SSP585, respectively). The intermediate scenario has a similar pattern to the most extreme scenario, but low emission was found to mitigate drought risk. Globally, we found that air temperature will have a greater impact than precipitation on intensifying drought. Increasing precipitation will mitigate drought risks in some middle and high northern latitudes, whilst the trend in increasing air temperature will counter the effects of precipitation and increase the impact of droughts. Our study improves the understanding of the dynamics of future devastating drought events and informs the decision-making of stakeholders.

Staged and repeated drought-induced regulation of phenylpropanoid synthesis confers tolerance to a water deficit environment in Camellia sinensis

This year, more than four months of extreme drought caused a nearly 30% yield reduction in Chinese tea (Camellia sinensis, Theaceae) plantations. The related dicot plants potato (Solanum tuberosum, Solanaceae) and apple (Malus pumila, Rosaceae) deploy species specific, specialized metabolites as core stress defenses. In contrast, the specialized chemical defenses in tea plants are largely unknown. The high levels of polyphenols and theanine in tea plants are potential drought-resistant substances. Stress-related overreduction is known to cause a passive accumulation of plant metabolites to dissipate excess energy. To investigate specialized metabolic drought responses, we integrated tea plant physiological, transcriptomic, and metabolite analyses with different stress modes of staged and repeated drought. Under staged drought, tea leaves were subjected to more severe oxidative stress and photosynthetic system disruption after long-term drought. However, differentially expressed genes in response to the Calvin cycle and energy metabolism were significantly increased compared with short-term drought. Tea plants that experienced three rounds of drought exhibited more robust antioxidant defense and photosynthetic efficiency and lower energy requirements than those in their first drought. Metabolomic analyses identified carbohydrates, amino acids, and phenylpropanoid compounds that accumulated significantly in tea plants after drought. Consistent with altered transcriptomics, tea plants in the two drought modes were significantly enriched in 'phenylpropanoid biosynthesis', and several phenolic acid compounds exhibited significant accumulation. Exogenous irrigation of tea plants before drought with phenylpropanoid derivatives (tea polyphenols) extracted from tea leaves significantly reduced the malonaldehyde content in the roots. In summary, the passive transfer of metabolites and upregulation of biosynthesis rates combined to regulate metabolite levels in tea plants under drought, ultimately reducing the levels of toxic oxygen radicals.

Spatiotemporal Variation Characteristics of Droughts and Their Connection to Climate Variability and Human Activity in the Pearl River Basin, South China

Droughts have damaging impacts on human society and ecological environments. Therefore, studying the impacts of climate variability and human activity on droughts has very important scientific value and social significance in order to understand drought warnings and weaken the adverse impacts of droughts. In this study, we used a combined drought index based on five Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On solutions to characterize droughts in the Pearl River basin (PRB) and its sub-basins during 2003 and 2020. Then, we accurately quantified the impact of climate variability and human activity on droughts in the PRB and seven sub-basins by combining the hydrometeorological climate index and in situ human activity data. The results show that 14 droughts were identified in the PRB, particularly the North River basin with the most drought months (52.78%). The El Niño-Southern Oscillation and the Indian Ocean Dipole were found to have important impacts on droughts in the PRB. They affect the operation of the atmospheric circulation, as well as the East Asia summer monsoon, resulting in a decrease in precipitation in the PRB. This impact shows a significant east–west difference on the spatial scale. The middle and upper reaches of the PRB were found to be dominated by SM, while the lower reaches were found to be dominated by GW. Human activity was found to mainly exacerbate droughts in the PRB, but also plays a significant role in reducing peak magnitude. The sub-basins with a higher proportion of total water consumption experienced more droughts (more than 11), and vice versa. The Pearl River Delta showed the highest drought intensification. Reservoir storage significantly reduces the drought peak and severity, but the impact effect depends on its application and balance with the total water consumption. Our study provides a reference for analyzing the drought characteristics, causes, and impacts of sub-basins on a global scale.