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The division and evaluation of data series used in monitoring drought into different time intervals is a practical approach to detecting the spatial and temporal extent of drought spread. This study aimed to determine meteorological drought's spatial and temporal distribution using overlapping and consecutive periods and cycles of the standardized precipitation index (SPI) time series in the Mediterranean region, Turkey. In the scope of the research, SPI values for the SPI12, SPI6 (1), and SPI6 (2) seasons were calculated for consecutive and overlapping hydrological years (1978-1998/21 years, 1978-2008/31 years, and 1978-2018/41 years) at 28 meteorological stations. Autocorrelation, Mann-Kendall, and Sen slope trend tests were applied at a 5% significance level for each season (SPI12, SPI6 (1), and SPI6 (2)) and different time scales (21, 31, and 41 years). For each season and period, maps of the SPI drought class, average formation of drought class, Mann-Kendall (MK) trend, and Sen's slope (SS) trend test statistics for the Mediterranean region were obtained, and the spatial distribution rate of trends was determined by drawing hypsometric curves. Changes in drought occurrence at different time scales were thoroughly evaluated with the changing length of data recording. Consequently, it was determined that the mild wet (MIW) and mild drought (MID) classes dominate the study area in the Mediterranean region. Significant and nonstationary changes detected in extreme wet and drought occurrences (extreme wet, EW; severe wet, SW; extreme drought, ED; severe drought, SD) were found to pose a risk in the study area. It was observed that there were spatially and temporally insignificant decreasing drought trends in the Mediterranean basin, considering that the time scales of these trends slowed down. Despite a nonsignificant trend from the MID drought class to the MIW drought class, it is predicted that the MIW and MID classes will maintain their dominance in the Mediterranean region. The central part of the study area (central Mediterranean basin) is the region with the highest drought risk., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

The interplay between population dynamics and the environment has long interested demographers. Although studies have explored how climate patterns affect macrolevel population processes, such as mortality and migration, little is known about their impact on individual-level demographic behaviors. This study fills this research gap by examining the linkages between exposure to drought and women's fertility preferences and contraceptive behaviors in sub-Saharan Africa. We analyze data from the Demographic and Health Surveys Program, focusing on 17 countries in East, Southern, and West Africa. We investigate whether women's recent exposure to drought episodes in their community affects their fertility preferences and modern contraceptive use. Generally, the findings show that drought is relevant to understanding women's fertility preferences and behaviors in the vast majority of countries; however, drought exposure has variable impacts. Moreover, whereas in some countries, drought exposure encourages contraceptive behaviors that align with women's preferences, in select countries it is associated with behavior that is misaligned with women's stated preferences. Overall, the study emphasizes the importance of examining climate events as complex forces that have localized meanings for demographic outcomes., (© 2024 The Population Council, Inc.)

Given the context of significant global warming and the intensification of extreme climate events in the last century, large-scale reforestation and afforestation have been recognized as effective strategies to mitigate the climate crisis. Since the 1970s, China has launched several afforestation programs aimed at regional ecological protection, playing an important role in reaching carbon neutrality by 2060. This study provided a detailed analysis of the growth suitability of the main planted conifers (Pinus sylvestris var. mongolica and Pinus tabulaeformis) and broadleaves (Populus spp., Robinia pseudoacacia) in the semi-arid northern China. We compared the radial growth trends of plantations and their responses to extreme droughts from 1980 to 2018. Growth of most plantations has significantly increased over time, but broadleaves showed recent growth reductions in the past decade, which may be related to tree age and reduced soil moisture. Nevertheless, under warmer climate scenarios, the growth of plantations is forecasted to continue increasing. Broadleaves showed a better post-drought recovery, probably linked to their anisohydric behavior, than conifers, which presented a better resistance to drought. Growth of conifers depended more on warmer temperature and better precipitation conditions during the growing season, whereas broadleaves mainly reacted to warm temperature. Additionally, pre-drought growth levels weakened resilience components, while post-drought precipitation compensated for drought-induced growth deficit. Growth and resilience were negatively related to tree age, while higher stand density reduced growth. This assessment and projections of growth and drought resilience indicate the sustainability of most plantations in semi-arid regions, but future warmer and drier conditions may lead to an uncertain future regarding forest health and reduce their carbon sink potential., (© 2024 John Wiley & Sons Ltd.)

The Horn of Africa Drylands are increasingly experiencing severe droughts, which impose a threat on traditional livelihood strategies. Understanding adaptation behavior in rural communities is key to helping reduce the impact of these droughts. We investigate adaptation behavior by assessing four established economic and social psychological theories on decision making under risk: expected utility theory (EUT), rank dependent utility theory (RDU), protection motivation theory (PMT), and theory of planned behavior (PMT). To measure adaptation behavior and the theory constructs, we conducted a household survey in Kenya (N = 502). Regression analysis shows that the economic theories (EUT and RDU) have the best fit for our data. Risk and time preferences are found to play an important role in adaptation decisions. An analysis of differences in decision making for distinct types of adaptation measures shows that risk averse (agro-)pastoralists are more likely to implement adaptation measures that are adjustments to their current livelihood practices, and less willing to invest in adaptation measures that require a shift to other livelihood activities. Moreover, we find significant effects for elements of the social psychological theories (PMT and TPB). A person's belief in their own ability to implement an adaptation measure (perceived self-efficacy) and adaptation by family and friends are important factors in explaining adaptation decisions. Finally, we find that the type of adaptation measures that people implement is influenced by, among others, gender, education level, access to financial resources, and access to government support or aid. Our analysis gives insights into the drivers of individual adaptation decisions, which can enhance policies promoting adaptation of dryland communities., (© 2023 The Authors. Risk Analysis published by Wiley Periodicals LLC on behalf of Society for Risk Analysis.)

This study provides a method for analyzing the drought-vulnerability index (DVI) from a multidimensional perspective that includes biophysical and social aspects, considering the Intergovernmental Panel on Climate Change's (IPCC) assessment. The proposed method generates the "exposure index (EI)", "sensitivity index (SI)", and "adaptive capacity index (ACI)" components of the proposed DVI using nine sub-indicators and 29 proxy variables. By using it throughout all of Turkey's provinces, the performance of the developed index was evaluated. In this study, the decision matrices were built utilizing expert knowledge, and the weights of the indicators and variables were obtained by using the Analytical Hierarchy Process (AHP) technique. Moreover, the values of these four indices were classified as "very high, high, moderate, low, and very low," and their geographical distribution across the country was drawn, as well as relevant patterns retrieved. The study's major results show that 17 of the 81 provinces are classified as "very high," 16 as "high," 15 as "moderate," 17 as "low," and the remaining 16 as "very low" drought vulnerable. Another significant result is that the majority of people in the country's south, center, and southeast rely on agriculture and are thus more vulnerable to drought due to socioeconomic underdevelopment in those regions., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Semiarid regions are often affected by water scarcity and poor water quality. Seasonal changes in precipitation and drought events increase the pressure of use on water bodies and their pollution. In Central Northern Namibia, a high seasonal intra- and inter-annual variability of precipitation caused a 5-year lasting drought period. In the semiarid region, ephemeral channels and water pans represent the main water source, besides the institutionalized water supply. No systematic analysis of its quality has been conducted so far. The states of the surface waters at the end of the dry season in 2017 and the end of the rainy seasons in 2018 and 2019 were characterized by the analysis of physical-chemical parameters, focusing on usability. The first results show coarse contamination of the waters, which results in high turbidity values. Salt concentrations, such as Ca 2+ and Na + , greatly increased due to evaporation. Al is present in high concentrations in solid and liquid phases, which indicates direct anthropogenic pollution. Spatial differences are evident in the study area and based on the precipitation gradient, land use, and population density. The waters cannot be used as drinking water without prior treatment., (© 2023. The Author(s).)

The incidence and severity of global mangrove mortality due to drought is increasing. Yet, little is understood of the capacity of mangroves to show long-term acclimation of leaf water relations to severe drought. We tested for differences between mid-dry season leaf water relations in two cooccurring mangroves, Aegiceras corniculatum and Rhizophora stylosa before a severe drought (a heatwave combined with low rainfall) and after its relief by the wet season. Consistent with ecological stress memory, the legacy of severe drought enhanced salinity tolerance in the subsequent dry season through coordinated adjustments that reduced the leaf water potential at the turgor loss point and increased cell wall rigidity. These adjustments enabled maintenance of turgor and relative water content with increasing salinity. As most canopy growth occurs during the wet season, acclimation to the 'memory' of higher salinity in the previous dry season enables greater leaf function with minimal adjustments, as long-lived leaves progress from wet through dry seasons. However, declining turgor safety margins - the difference between soil water potential and leaf water potential at turgor loss - implied increasing limitation to water use with increasing salinity. Thus, plasticity in leaf water relations contributes fundamentally to mangrove function under varying salinity regimes., (© 2023 The Authors. Plant, Cell & Environment published by John Wiley & Sons Ltd.)

In the Southern Central Highlands of Vietnam, droughts occur more frequently, causing significant damage and impacting the region's socio-economic development. During the dry season, rivers, streams, and reservoirs often face limited water availability, exacerbated in recent years by increasing drought severity. Recognizing the escalating severity of droughts, the study offers a novel contribution by conducting a comprehensive analysis of surface water resource distribution in Lam Dong province, focusing on assessing water demand for agricultural production, a crucial factor in ensuring sustainable crop growth. Two scenarios, Current-2020 (SC1) and Climate Change-2025 (SC2), are simulated, with SC2 based on climate change and sea level rise scenarios provided by the Ministry of Natural Resources and Environment (MONRE). These scenarios are integrated into the MIKE-NAM and MIKE-HYDRO basin models, allowing for a thorough assessment of the water balance of Lam Dong province. Furthermore, the study utilizes the Keetch-Byram Drought Index (KBDI) to measure drought severity, revealing prevalent dry and moderately droughty conditions in highland districts with rainfall frequency ranging from 50 to 85%. Severe drought conditions occur with a rainfall frequency of 95%, indicating an increased frequency and geographic scope of severe droughts. Additionally, the study highlights that under abnormally dry conditions, water demand for the winter-spring crop is consistently met at 100%, decreasing to 85%, 80%, and less than 75% for moderate, severe, and extreme droughts, respectively. These findings offer insights into future drought conditions in the Lam Dong province and their potential impact on irrigation capacity, crucial for adaptation strategies., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Climate change is increasing the frequency of droughts and the risk of severe wildfires, which can interact with shrub encroachment and browsing by wild ungulates. Wild ungulate populations are expanding due, among other factors, to favorable habitat changes resulting from land abandonment or land-use changes. Understanding how ungulate browsing interacts with drought to affect woody plant mortality, plant flammability, and fire hazard is especially relevant in the context of climate change and increasing frequency of wildfires. The aim of this study is to explore the combined effects of cumulative drought, shrub encroachment, and ungulate browsing on the fire hazard of Mediterranean oak woodlands in Portugal. In a long-term (18 years) ungulate fencing exclusion experiment that simulated land abandonment and management neglect, we investigated the population dynamics of the native shrub Cistus ladanifer, which naturally dominates the understory of woodlands and is browsed by ungulates, comparing areas with (no fencing) and without (fencing) wild ungulate browsing. We also modeled fire behavior in browsed and unbrowsed plots considering drought and nondrought scenarios. Specifically, we estimated C. ladanifer population density, biomass, and fuel load characteristics, which were used to model fire behavior in drought and nondrought scenarios. Overall, drought increased the proportion of dead C. ladanifer shrub individuals, which was higher in the browsed plots. Drought decreased the ratio of live to dead shrub plant material, increased total fuel loading, shrub stand flammability, and the modeled fire parameters, that is, rate of surface fire spread, fireline intensity, and flame length. However, total fuel load and fire hazard were lower in browsed than unbrowsed plots, both in drought and nondrought scenarios. Browsing also decreased the population density of living shrubs, halting shrub encroachment. Our study provides long-term experimental evidence showing the role of wild ungulates in mitigating drought effects on fire hazard in shrub-encroached Mediterranean oak woodlands. Our results also emphasize that the long-term effects of land abandonment can interact with climate change drivers, affecting wildfire hazard. This is particularly relevant given the increasing incidence of land abandonment., (© 2024 The Authors. Ecological Applications published by Wiley Periodicals LLC on behalf of The Ecological Society of America.)

Drought is a natural and complex climatic hazard. It has both natural and social connotations. The purpose of this study is to use machine learning methods (MLAs) for drought vulnerability (DVM) in Uttar Pradesh, India. There were 18 factors used to determine drought vulnerability, separated into two groups: physical drought and meteorological drought. The study found that the eastern part of Uttar Pradesh is high to very highly prone to drought, which is approximately 31.38% of the area of Uttar Pradesh. The receiver operating characteristic curve (ROC) was then used to evaluate the machine learning models (artificial neural networks). According to the findings, the ANN functioned with AUC values of 0.843. For policy actions to lessen drought sensitivity, DVMs may be valuable. Future exploration may involve refining machine learning algorithms, integrating real-time data sources, and assessing the socio-economic impacts to continually enhance the efficacy of drought resilience strategies in Uttar Pradesh., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: Homeodomain-leucine ZIPper (HD-ZIP) transcription factors play crucial roles in plant growth, development, and stress responses. The HD-ZIP family is categorised into four groups (HD-ZIP I-IV). While extensive genome-wide studies have been conducted on the HD-ZIP I, III, and IV subfamily in Nicotiana tabacum (tobacco), comprehensive reports on the HD-ZIP II subfamily genes are limited., Methods: Bioinformatics resources and tools were utilised to analyse molecular characteristics, phylogenetic homology, and protein interactions. Expression pattern analyses in various tissues and the relative expression of NtHD-ZIP II genes under drought and GA 3 treatment were assessed by qRT-PCR., Results: In this study, 24 HD-ZIP II members were systematically identified and categorised into seven independent clades through phylogenetic analysis involving tobacco and other plant species. We found that 19 NtHD-ZIP II genes exhibited tissue-specific expression. The transcripts of NtHD-ZIPII3, 4, 14, 23, 24 were notably induced under the drought treatments, while those of NtHD-ZIPII7, 11, 12, 20 were suppressed. Furthermore, NtHD-ZIPII15 transcripts decreased following GA 3 treatment, whereas the transcripts of NtHD-ZIPII7, 8, 11, 12 were induced after GA 3 treatment. Notably, an increase in trichomes was observed in tobacco leaves treated with GA 3 and subjected to drought., Conclusions: The expression levels of some HD-ZIP II genes were altered, and an increase in glandular trichomes was induced under GA 3 and drought treatments in tobacco. Overall, our findings provide insights into the expression patterns of NtHD-ZIP II genes and will facilitate their functional characterisation in future studies., (© 2024. The Author(s), under exclusive licence to Springer Nature B.V.)

Although many drought indices have been developed to monitor drought conditions, their applicability differs across climatic regions, which results in different characteristics of drought index assessments at different timescales and over different record lengths. Therefore, the applicability of precipitation-based and precipitation-evapotranspiration/temperature-based drought indices was examined in this study using the Generalized Extreme Value Index (GEVI), Homogeneity Index (HI) of precipitation and temperature, K index (K), precipitation anomaly percentage (Pa), Standardized Precipitation Evapotranspiration Index (SPEI), Standardized Precipitation Index (SPI), and China-Z Index (CZI) over different record lengths and at a timescale range of 1-24 months. In addition, the results that were obtained using these indices were compared with the Self-Calibrating Palmer Drought Severity Index (scPDSI). The stability, accuracy, and consistency of the different drought indices were evaluated using precipitation and evapotranspiration/temperature data (1-24 months) collected from different climatic regions in the arid area of northwest China in the 1961-2017 period. The results indicated that the Pa, CZI, K, and SPEI were more stable; the SPI, SPEI, and HI were more accurate; and the GEVI, SPI, HI, and SPEI were more consistent with the scPDSI. In addition, the results indicated that it is more appropriate to select a long record length (> 35 years) to monitor drought when sufficient data are available. However, defining constant drought classes may not be appropriate for all drought timescales. In fact, precipitation and evapotranspiration data from different timescales had different optimal distribution functions. The drought indices also demonstrated that they were applicable to a temperate arid area in the study region. In addition, the HI and SPEI better captured the precipitation and evapotranspiration/temperature characteristics, while the CZI, K, and Pa overestimated or underestimated the frequency of different drought classes at different timescales to some extent in the study region. The results of this study suggest that greater priority should be given to the precipitation-evapotranspiration-based indices. In addition, it is suggested to change the drought index class thresholds in future related studies on drought event recognition at different timescales to ensure more accurate drought monitoring., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Agriculture, meteorological, and hydrological drought is a natural hazard which affects ecosystems in the central India of Maharashtra state. Due to limited historical data for drought monitoring and forecasting available in the central India of Maharashtra state, implementing machine learning (ML) algorithms could allow for the prediction of future drought events. In this paper, we have focused on the prediction accuracy of meteorological drought in the semi-arid region based on the standardized precipitation index (SPI) using the random forest (RF), random tree (RT), and Gaussian process regression (GPR-PUK kernel) models. A different combination of machine learning models and variables has been performed for the forecasting of metrological drought based on the SPI-6 and 12 months. Models were developed using monthly rainfall data for the period of 2000-2019 at two meteorological stations, namely, Karanjali and Gangawdi, each representing a geographical region of Upper Godavari river basin area in the central India of Maharashtra state which frequently experiences droughts. Historical data from the SPI from 2000 to 2013 was processed to train the model into machine learning model, and the rest of the 2014 to 2019-year data were used for testing to forecast the SPI and metrological drought. The mean square error (MSE), root mean square error (RMSE), adjusted R 2 , Mallows' (Cp), Akaike's (AIC), Schwarz's (SBC), and Amemiya's PC were used to identify the best combination input model and best subregression analysis for both stations of SPI-6 and 12. The correlation coefficient ([Formula: see text]), mean absolute error (MAE), root mean square error (RMSE), relative absolute error (RAE), and root relative squared error (RRSE) were used to perform evaluation for SPI-6 and 12 months of both stations with RF, RT, and GPR-PUK kernel models during the training and testing scenarios. The results during testing phase revealed that the RF was found as the best model in forecasting droughts with values of [Formula: see text], MAE, RMSE, RAE (%), and RRSE (%) being 0.856, 0.551, 0.718, 74.778, and 54.019, respectively, for SPI-6 while 0.961, 0.361, 0.538, 34.926, and 28.262, respectively, for SPI-12 scales at Gangawdi station. Further, the respective values of evaluators at Karanjali station were 0.913 and 0.966, 0.541 and 0.386, 0.604 and 0.589, 52.592 and 36.959, and 42.315 and 31.394 for PUK kernel and RT models, respectively, during SPI-6 and SPI-12. Machine learning models are potential drought warning techniques because they take less time, have fewer inputs, and are less sophisticated than dynamic or scientific models., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Objectives: Arid pastoralism is often understood as an adaptive strategy to marginal environments. As pastoralists become increasingly market integrated, novel dietary preferences and access to low quality market foods can erode traditional diets. These market-based dietary shifts are particularly problematic during sustained drought, where reductions in traditional foods make pastoralists increasingly reliant on a cash economy. Among the Himba of the Kunene region in Namibia, colonial policies prohibiting access to livestock markets inhibit access to a cash-based economy, leaving them vulnerable to food insecurity when nontraditional foods are needed to supplement traditional lifeways during drought. To understand the impacts of long-term drought on diet and food insecurity, we collected longitudinal survey data on diet breadth and food insecurity across 4 years during a multi-year drought., Methods: Participants completed a five-item food insecurity survey and recalled diet breadth survey over the course of 4 years (N = 191-234). Additionally, women completed a short survey of recent stressors, including health and resource stressors (N = 127). We used a set of multilevel models to estimate changes in food insecurity items and diet breadth changes over the course of the study period., Results: Multilevel models predicted score outcomes, as well as individual item responses, by year of data collection. Results indicate a 43% increase in average food insecurity and a 15% decline in average diet breadth over the study period. Dietary recall indicates that drought caused a reduction in sour milk intake, and an increase in nontraditional foods, but no change in meat or maize consumption., Conclusions: Sustained drought in the Kunene region is having long-term impacts on food insecurity, which could result in dietary shifts that outlast the current period of drought. We consider the implications of this change, especially as it relates to increasing market integration and reliance on a cash-based over a subsistence-based economy., (© 2022 Wiley Periodicals LLC.)

This document provides summaries of three research papers that focus on the impact of drought on plant communities. The first paper introduces a simulation method for studying the growth and interactions of annual plants in arid regions. The second paper presents the GIID model, which examines how plant communities respond to drought and the role of species diversity in their resilience. The third paper develops a mathematical model to predict changes in plant communities during drought cycles, considering spatial dimensions. These papers offer valuable insights into the effects of drought on plant communities and emphasize the importance of biodiversity in their ability to withstand drought. The article discusses various mathematical models and simulations used to understand the changing patterns and viability of plant communities in drought-stricken areas. It also suggests ways to improve the resilience of plant communities under drought conditions. [Extracted from the article]

This study analyzed the meteorological and hydrological droughts in a typical basin of the Brazilian semiarid region from 1994 to 2016. In recent decades, this region has faced prolonged and severe droughts, leading to marked reductions in agricultural productivity and significant challenges to food security and water availability. The datasets employed included a digital elevation model, land use and cover data, soil characteristics, climatic data (temperature, wind speed, solar radiation, humidity, and precipitation), runoff data, images from the MODIS/TERRA and AQUA sensors (MOD09A1 and MODY09A1 products), and soil water content. A variety of methods and products were used to study these droughts: the meteorological drought was analyzed using the Standardized Precipitation Index (SPI) derived from observed precipitation data, while the hydrological drought was assessed using the Standardized Soil Index (SSI), the Nonparametric Multivariate Standardized Drought Index (NMSDI), and the Parametric Multivariate Standardized Drought Index (PMSDI). These indices were determined using water balance components, including streamflow and soil water content, from the Soil Water Assessment Tool (SWAT) model, and evapotranspiration data from the Surface Energy Balance Algorithm for Land (SEBAL). The findings indicate that the methodology effectively identified variations in water dynamics and drought periods in a headwater basin within Brazil's semiarid region, suggesting potential applicability in other semiarid areas. This study provides essential insights for water resource management and resilience building in the face of adverse climatic events, offering a valuable guide for decision-making processes., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Uncertainty and uneven distribution of monsoonal rainfall and its consequences on crop production is a matter of serious concern in India, specifically, in the Indo-Gangetic plain region. In this study, drought patterns were investigated through standardised precipitation index (SPI) of varying timescales, using the India Meteorological Department (IMD) precipitation data (1901-2021). We analysed the spatio-temporal pattern of different drought characteristics (frequency, duration, severity, intensity) of the Indian Gangetic basin using run theory. The bivariate copula method has been incorporated to combine two drought properties (severity and duration). Copula integrates multivariate distribution and considers the dependency rate among the variables. The five most widely used copulas from various copula families, elliptical (normal, t-copula) and Archimedean (Clayton, Gumbel, Frank), were estimated for modelling, and the best fit copula was selected. The study revealed that seasonal drought is more frequent and intense in the Upper and Middle Gangetic Plain, whereas annual drought is quite scattered in nature. It is worthy to mention that downward drought trends were observed in this agricultural belts significantly after 1965; specifically, in the Upper, Middle, and Trans Gangetic Plain regions. With increasing drought duration and severity, the drought return period raised, but the frequency decreased gradually. Most of the droughts characterised by less duration and severity occurred with a return period below 10 years for the whole region. The major 100 + years return period droughts were to be found after 1960 and their frequencies were significantly higher after 2000. The most recent remarkable droughts with more than 100 years of return occurred during 2008-2011 and 2016-2018 in the Upper and Middle Gangetic plains, whereas in the Lower Gangetic plain, a hundred-year return period drought was occurred during 2010-2013. This study provides agroclimatic-zones-wise significant information of drought characteristics and its nature of occurrence in the Indian Ganga Basin. The results enhance the understanding of drought management and formulation of adaptive strategies to mitigate the adverse impact of droughts., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

As the backbone of Vietnam's economy, the country has recently established a number of policies for promoting and investing in smart agriculture in the Mekong Delta, the country's largest agricultural hub, to foster overall socio-economic development. However, water remains a critical constraint for crop production, with progress being hindered by water scarcity and quality issues, and compounded by socio-economic transformation and climate change. Considering these challenges, this study used the CROPWAT model and a wide spectrum of climate change scenarios to investigate future total water demands in the 2030s and 2050s as well as drought levels in two underdeveloped semi-mountainous reservoir catchments, i.e., O Ta Soc and O Tuk Sa in An Giang province. The results suggest that the usable storage capacity of the O Ta Soc reservoir will increase to 650,000 m 3 to meet water supply demands under all climate change scenarios and the medium-term, moderate drought conditions. The useable storage capacity of the O Tuk Sa reservoir will also be increased to 880,000 m 3 and the irrigation area would see a marked 70% reduction compared to its design irrigation. Under these circumstances, the O Tuk Sa reservoir will continue to supply water under all climate change scenarios and medium-term droughts. As a core element for strategic planning and to ensure efficient management of water resources, the results highlight the importance of estimating potential runoff and rainfall in semi-mountainous reservoir catchments under various drought conditions in order to propose the suitable expansion of the useable water storage capacities., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Precipitation studies have a crucial role in deciphering climate change and monitoring natural disasters such as droughts. Such studies lead to better assessment of rainfall amounts and spatial variabilities; and have a vital role in impact assessment, mitigation, and prediction of occurrence. Thus, this study has been undertaken in the Subarnarekha River basin using Climate Hazards group Infrared Precipitation with Stations (CHIRPS) dataset. Precipitation datasets helped in deriving hydrometeorological indices such as the Rainfall Anomaly Index (RAI) and Standardized Precipitation Index (SPI) for the identification of drought occurrences. The core objective was to infer spatio-temporal drought scenarios and their trend characterization covering four decades over the years 1981 to 2020. Quantitative drought assessment was done using run theory for identifying the Drought Duration (DD), Drought Severity (DS), Drought Intensity (DI), and Drought Frequency (DF). Mann-Kendall (MK) test was performed to understand the precipitation and drought trends at annual and seasonal scales. Eight severe drought events were identified in the Subarnarekha River basin for the past 40 years and the average DI value of 0.8 was recorded. MK test results for the precipitation showed a significant positive trend (95% confidence level) for pre-monsoon periods. However, for SPI, a significant positive trend was observed over the intervals of 3 (SPI3), 6 (SPI6), and 12 (SPI12) months respectively at an annual timescale, suggesting wetter conditions within the study area. Moreover, there had been insignificant negative trends for SPI1 and SPI3 during winter. It indicates that during the short-term SPI scale, i.e., 1 month (SPI1) and 3 months (SPI3), the instances of negative SPI values inferred were high, which point to the increasing incidences of meteorological drought possibly due to deficient soil moisture. Thus, the results indicated that the CHIRPS precipitation product-derived hydrometeorological indices could act as a valuable tool for assessing the past spatio-temporal drought conditions of the Subarnarekha River basin. This may further be helpful in planning for sustainable water resource management of such river basins., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Responding to disasters triggered by natural hazards is a deeply political process, but it is usually presented by practitioners as an apolitical endeavour. This is striking when disasters occur in authoritarian and politically highly polarised conflict-affected settings. Although the literature provides leads as to why and how humanitarians depoliticise aid, there has been little empirical research on the implications of depoliticisation, especially at the community level. Based on qualitative fieldwork that focused on the drought responses that overlapped with the 2016-19 sociopolitical crises in Zimbabwe, this paper details the practices, motivations, and implications of humanitarian depoliticisation. It differentiates between strategic, coerced, and routine managerial depoliticisation, and argues that, in an authoritarian conflict-affected setting, depoliticisation strategically allows state and non-state actors to defuse sensitive issues and actor relations and to remain safe. However, depoliticisation can also have implications for information management, monitoring, accountability, and protection, and thus ultimately for upholding humanitarian principles., (© 2021 The Authors Disasters © 2021 ODI.)

Drought tolerance varies greatly across Vitis vinifera cultivars, depending on physiological responses and structural and morphological adaptations. In this study, responses to water stress were examined in three extensively cultivated varieties from Northern Italy. Over the course of two seasons, mature potted vines were subjected to a 12 or 13-day period of water restriction. Vine water relations were investigated using measures of water potential, gas exchanges, and leaf ABA content. Leaf angle response to increasing water stress was analysed in the four cultivars as a mechanism that improves stress tolerance. Different physiological responses were observed among cultivars, suggesting a near-isohydric water-use strategy for Moscato and a near-anisohydric one for Garganega, Glera and Merlot. Results of leaf ABA analysis highlighted a variability among the studied varieties, indicating higher contents and lower sensitivity to ABA for the anisohydric ones. In all varieties, a similar increase in midday leaf inclination was observed in response to decreasing stem water potentials, indicating that leaf angle adjustments may represent a common adaptive response to drought. These findings increase the understanding of the leaf physiological and structural mechanisms that contribute to water stress tolerance in grapevine, supporting a more efficient cultivar selection to cope with the expected changes in Mediterranean climate., (© 2023 Scandinavian Plant Physiology Society.)

In the present study, the spatiotemporal evaluation of the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) satellite precipitation product is performed in capturing meteorological drought over different climatic regions of Iran. The performance of the product as a high spatial resolution dataset in monitoring drought is evaluated against the 68 meteorological stations from short to long scale (i.e., SPI1, SPI3, SPI6, SPI9, and SPI12) in the period of 1987 to 2017. Besides, the capability of the CHIRPS in detecting drought events is assessed in different drought classes. The results suggest that the climate type, the time scale, and the drought class affect the quality of the CHIRPS performance. The CHIRPS offers the best performance in the detection of all drought events with SPI <  - 1 over the SPI1 (0.69 < POD < 0.85). However, the product provides the worst performance for SPI12 (0.50 < POD < 0.70). At the country level, the highest agreement between the CHIRPS- and observation data-based SPI is found over the SPI6 (CC = 0.56), while the lowest is observed over the SPI12 (CC = 0.47). Based on the temporal evaluation, the G6 (0.18 < CC < 0.44, 1.06 < RMSE < 1.28) and G8 (0.17 < CC < 0.43, 1.06 < RMSE < 1.29) regions located in the southern coast of the Caspian Sea have an inadequate performance. However, the southern parts (G4 region) (0.38 < CC < 0.65, 0.83 < RMSE < 1.27) and the northwestern area (G3 region) (0.53 < CC < 0.62, 0.87 < RMSE < 0.97) of the country offer the best performance. The spatial evaluation describes the high accuracy (CC > 0.7, RMSE < 0.5) in some regions, including the western parts of G1, the northern area of G3, and the southern parts of G4. The research findings provided an important opportunity to advance the understanding of drought monitoring over the different climatic regions based on the high-resolution satellite precipitation products., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Drought is one of the natural disasters that causes a great damage to human life and natural ecosystems. The main differences are in the gradual effect of drought over a relatively long period, impossibility of accurately determining time of the beginning and end of drought, and geographical extent of the associated effects. On the other hand, lack of a universally accepted definition of drought has added to the complexity of this phenomenon. In the last decade, due to increasing frequency of drought in Iran and reduction of water resources, its consequences have become apparent and have caused problems for planners and managers. So in this research, regional frequency analysis using L-moments methods was performed to investigate severity and duration of Standardized Precipitation Index (SPI), Standardized Evapotranspiration Index (SEI), Standardized Runoff Index (SRI), and Standardized Soil Moisture Index (SSI) and to study of meteorological, agricultural, and hydrological droughts in Karkheh River Basin in Iran. Using K-means clustering method, basin was divided into four homogeneous areas. Uncoordinated stations in each cluster were removed. The best regional distribution function was selected for each homogeneous region, and it was found that Pearson type (3) has the highest fit on the data set in the basin. Based on Hosking and Wallis heterogeneity test, Karkheh Basin with H 1  < 1 was identified as acceptable homogeneous in all clusters. The results showed that hydrological drought occurs with a very short time delay in Karkheh River Basin after the meteorological drought, and two indicators show meteorological and hydrological drought conditions well. Agricultural drought occurs after meteorological and hydrological drought, respectively, and its severity and duration are less than the other indicators. Meteorological, hydrological, and agricultural droughts do not occur at the same time in all of the years. In general, the SPI drought index shows the most severe droughts compared with the other three indices. By this way, in 5- to 20-year return period with severity of 3SPI and in 20- to 100-year return period with severity of 7SPI, region IV or the western and northwestern areas of the basin has been affected by severe meteorological drought. By using the regional standardized quantities, it is possible to estimate the probability of drought in any part of the catchment that does not have sufficient data for hydrological studies., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Multi-purpose crops as maize, rice, soybean, and wheat are key in the debate concerning food, land, water and energy security and sustainability. While strong evidence exists on the effects of climate variability on the production of these crops, so far multifaceted attributes of droughts-magnitude, frequency, duration, and timing-have been tackled mainly separately, for a limited part of the cropping season, or over small regions. Here, a more comprehensive assessment is provided on how droughts with their complex patterns-given by their compound attributes-are consistently related to negative impacts on crop yield on a global scale. Magnitude and frequency of both climate and yield variability are jointly analysed from 1981 to 2016 considering multiscale droughts, i.e., dry conditions occurring with different durations and timings along the whole farming season, through two analogous and standardized indicators enabling comparison among crops, countries, and years. Mainly winter wheat and then spring wheat, soybean and the main maize's season reveal high susceptibility of yield under more complex drought patterns than previously assessed. The second maize's season and rice present less marked and more uncertain results, respectively. Overall, southern and eastern Europe, the Americas and sub-Saharan Africa presents multi-crop susceptibility, with eastern Europe, Middle East and Central Asia appearing critical regions for the most vulnerable crop, which is wheat. Finally, yield losses for wheat and soybean clearly worsen when moving from moderate to extreme multiscale droughts., (© 2022. The Author(s).)

Drought is defined as a period of time characterized by below-normal water availability, which may affect crops, animals and the environment. Recently, drought was shown to be more frequent and more intense, implying thereby the need for monitoring and analysis of this natural hazard. The present study aims to examine the spatial extent and temporal variation of droughts in the Merguellil watershed, located in central Tunisia. This contribution was mainly based on the analysis of annual and monthly rainfall time series recorded over the period (1983-2018) in 19 stations spread throughout the study watershed. Rainfall trend was first examined using the Mann-Kendall statistical test. Then, statistical (standard precipitation index (SPI) and Palmer drought severity index (PDSI)), spectral (continuous wavelet transform (CWT)) and mapping (geographical information system (GIS)) techniques were used to identify extreme dry events and to characterize their severity and their spatial and temporal extents. The results obtained revealed the recurrence and frequency of drought conditions in the Merguellil watershed over the study period. Seven drought sequences (1983-1984, 1986-1989, 1992-1995, 1999-2002, 2007-2009, 2013-2015 and 2017-2018), with different levels of severity, were distinguished based on the computed SPI and PDSI values. Spectral analysis of rainfall data also showed the occurrence of significant droughts in recent years. The period starting from 2010 was shown to be marked by recurrent episodes of drought in the Merguellil watershed. Extreme drought events mapping over this period confirmed drought severity at both time and space scales. All of these findings may be helpful for developing programs of water resource management in the study watershed., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Due to global warming, droughts have become one of the focal points of researchers in the field of climate and water, all over the world. The analyses in this paper include spatial pattern and temporal trend for the territory of Serbia, over the 1949-2016 period. The De Martonne aridity index and the Ped drought index have been applied. Eighteen pairs of temperature and precipitation stations all over the country have been analyzed. The obtained results show a tendency toward a drier condition, which are not yet drastic. Drought areas for the territory of Serbia are increasing, but drought intensity and frequency should certainly be lower than those predicted for the Mediterranean coastal area, except in regions with very high human water use. Comparing the obtained results from stations at the original altitude and calculated data for the same stations at fixed virtual altitudes has shown that the natural direction of drought, which decreases from west to southeast, has shifted to a north to south direction., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Plants cannot move, so they must endure abiotic stresses such as drought, salinity and extreme temperatures. These stressors greatly limit the distribution of plants, alter their growth and development, and reduce crop productivity. Recent progress in our understanding of the molecular mechanisms underlying the responses of plants to abiotic stresses emphasizes their multilevel nature; multiple processes are involved, including sensing, signalling, transcription, transcript processing, translation and post-translational protein modifications. This improved knowledge can be used to boost crop productivity and agricultural sustainability through genetic, chemical and microbial approaches., (© 2021. Springer Nature Limited.)

Central Malawi has intensely been subjected to different climate-related shocks such as floods, dry spells, and droughts, resulting in decreases in crop yields. Due to their recurrence arising from the effects of climate change, drought characterization, monitoring, and prediction are crucial in guiding agriculture-water users and planners to prepare drought risk management plans and early warning systems. This research analyzed droughts, using multiple drought indices and their impacts on dominant crops over Central Malawi. Forty years of hydro-meteorological data (1977-2017) from nine rain-gauging stations and crop yield data from 1983 to 2017 from four districts were analyzed. The study discovered that drought events in the Agricultural Development Division (ADD) are highly a function of rainfall deficit and high temperatures. The results highlighted that the rainfall patterns in the area are not dependable, calling for the utilization of climate-smart irrigation systems such as drip irrigation and rainwater harvesting technologies. Furthermore, we achieved that crops such as cassava and groundnuts must be promoted to withstand the long water stress duration. These crops also have a multiplier effect; hence, they can enhance food security in the region. This study recommends that using more robust variables in drought analysis studies is necessary for effective drought monitoring and early warning systems. In corroboration with disaster management NGOs, it is recommended that the government should be proactive in developing integrated drought management policies and planning strategies for drought adaptation and mitigation., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

The intensity and frequency of diverse hydro-meteorological disasters viz., extreme droughts, severe floods, and cyclones have increasing trends due to unsustainable management of land and water resources, coupled with increasing industrialization, urbanization and climate change. This study focuses on the forecasting of drought using selected Artificial Neural Network (ANN)-based models to enable decision-makers to improve regional water management plans and disaster mitigation/reduction plans. Four ANN models were developed in this study, viz., one conventional ANN model and three hybrid ANN models: (a) Wavelet based-ANN (WANN), (b) Bootstrap based-ANN (BANN), and (c) Wavelet-Bootstrap based-ANN (WBANN). The Standardized Precipitation Evapotranspiration Index (SPEI), the best drought index identified for the study area, was used as a variable for drought forecasting. Three drought indices, such as SPEI-3, SPEI-6 and SPEI-12 respectively representing "short-term", "intermediate-term", and "long-term" drought conditions, were forecasted for 1-month to 3-month lead times for six weather stations over the study area. Both statistical and graphical indicators were considered to assess the performance of the developed models. For the hybrid wavelet model, the performance was evaluated for different vanishing moments of Daubechies wavelets and decomposition levels. The best-performing bootstrap-based model was further used for analysing the uncertainty associated with different drought forecasts. Among the models developed for drought forecasting for 1 to 3 months, the performances of the WANN and WBANN models are superior to the simple ANN and BANN models for the SPEI-3, SPEI-6, and SPEI-12 up to the 3-month lead time. The performance of the WANN and WBANN models is the best for SPEI-12 (MAE = 0.091-0.347, NSE = 0.873-0.982) followed by SPEI-6 (MAE = 0.258-0.593; NSE = 0.487-0.848) and SPEI-3 (MAE = 0.332-0.787, NSE = 0.196-0.825) for all the stations up to 3-month lead time. This finding is supported by the WBANN analyze uncertainties as narrower band width for SPEI-12 (0.240-0.898) as compared to SPEI-6 (0.402-1.62) and SPEI-3 (0.474-2.304). Therefore, the WBANN model is recommended for the early warning of drought events as it facilitates the uncertainty analysis of drought forecasting results., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Drought is a gradual phenomenon that occurs slowly and directly impacts human life and agricultural products. Due to its significant damage, comprehensive studies must be conducted on drought events. This research employs precipitation and temperature from a satellite-based gridded dataset (i.e., NASA-POWER) and runoff from an observation-based gridded dataset (i.e., GRUN) to calculate hydrological and meteorological gical droughts in Iran during 1981-2014 based on the Standardised Precipitation-Evapotranspiration Index (SPEI) and Hydrological Drought Index (SSI) indices, respectively. In addition, the relationship between the meteorological and hydrological droughts is assessed over various regions of Iran. Afterward, this study employed the Long Short-Term Memory (LSTM) method to predict the hydrological drought based on the meteorological drought over the northwest region of Iran. Results show that hydrological droughts are less dependent on precipitation in the northern regions and the coastal strip of the Caspian Sea. These regions also have a poor correlation between meteorological and hydrological droughts. The correlation between hydrological and meteorological drought in this region is 0.44, the lowest value among the studied regions. Also, on the margins of the Persian Gulf and southwestern Iran, meteorological droughts affect hydrological droughts for 4 months. Besides, except the central plateau, most regions experienced meteorological and hydrological droughts in the spring. The correlation between droughts in the center of the Iranian plateau, which has a hot climate, is less than 0.2. The correlation between these two droughts in the spring is stronger than in other seasons (CC = 0.6). Also, this season is more prone to drought than other seasons. In general, hydrological droughts occurred one to two months after the meteorological drought in most regions of Iran. LSTM model for northwest Iran showed that the predicted values had a high correlation with the observed values, and their RMSE was less than 1 in this region. CC, RMSE, NSE, and R-square of the LSTM model are 0.7, 0.55, 0.44, and 0.6, respectively. Overall, these results can be used to manage water resources and allocate water downstream to deal with hydrological droughts., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The future risk for droughts and water shortages calls for substantial efforts by authorities to adapt at local levels. Understanding their perception of drought hazards, risk and vulnerability can help to identify drivers of and barriers to drought risk planning and management in a changing climate at the local level. This paper presents a novel interdisciplinary drought case study in Sweden that integrates soft data from a nationwide survey among more than 100 local practitioners and hard data based on hydrological measurements to provide a holistic assessment of the links between drought severity and the perceived levels of drought severity, impacts, preparedness, and management for two consecutive drought events. The paper highlights challenges for drought risk planning and management in a changing climate at the local level and elaborates on how improved understanding of local practitioners to plan for climate change adaptation can be achieved., (© 2023. The Author(s).)

There is generally a trade-off in the resistance to drought and to waterlogging. However, several species are sequentially subjected to both stressors in many environments. We evaluated the ecophysiological strategies to cope with multiple sequential stress of waterlogging and drought (W + D) of three taxa differing in stress resistance and root morphology: the phreatophic Eucalyptus camaldulensis (Ec) and two shallow-rooted willow clones: Salix matsudana x Salix alba (SmxSa) and Salix nigra (Sn4). Individuals of the three taxa were grown in pots and assigned to either of four treatments: Control (well-watered plants), well-watered followed by drought (C + D); waterlogged for 15 days followed by drought (W15d + D) and waterlogged for 30 days followed by drought (W30d + D). Biomass allocation, growth (diameter, height, length of leaves, and roots), specific leaf area, stomatal conductance, water potential, hydraulic conductivity of roots and branches, leaf C 13 and root cortical aerenchyma formation were determined at different stages of the experiment. Ec growth was not affected by W + D, developing tolerance strategies at leaf and whole plant levels. Differential effects of W + D were observed in both Salix clones depending on the time of waterlogging. In Sn4 and SmxSa, the root biomass was affected in W15d + D treatment, but a root tolerance response (aerenchyma and adventitious root formation) was observed in W30d + D. In the three taxa, and contrary to expectations, the previous exposure to a waterlogging period did not increase the susceptibility of the plants to a subsequent drought event. On the contrary, we found tolerance, which depended on the time of waterlogging exposure., (© 2023 Scandinavian Plant Physiology Society.)

Rajasthan state of India is prone to recurrent droughts; hence, exploring drought severities over the semi-arid Sahibi river basin is crucial for drought management. To investigate drought severity, the Rainfall Anomaly Index (RAI) was applied at two time spans, such as annual (January to December) and the monsoon season (June to September), using long-term daily rainfall data (1961-2017) for nine rain gauge stations. Similarly, for the examination of various drought characteristics like magnitude, duration and intensity, run theory analysis was used. Trends in rainfall, drought severity, magnitude, duration and intensity were computed by employing both parametric (simple linear regression) and non-parametric (Mann-Kendall and Sen's slope) tests, while spatial pattern maps of rainfall and drought characteristics were prepared using geographical information system. The analysis of rainfall records revealed a declining trend in eastern and central parts, whereas remaining areas of the basin witnessed an increasing trend during two time spans. During the study period, drought occurrence varied both geographically and temporally. The extreme, severe and moderate drought events were more common during monsoon season. Amongst the stations, Tapukara, Bairath and Mundawar rain gauge stations experienced the largest number of drought events compared to other stations. At both time scales, the most extreme droughts in the Sahibi basin occurred in 1979, 1986, 1987, 1989 and 2002. At the annual time span, the basin had the longest drought duration of 300 days, with a drought magnitude of - 758.3 mm. Likewise, the Tapukara rain gauge station had the longest dry spell of 310 days, followed by Behrod and Kotkasim (306 days each), Kotputli and Tijara (305 days each) and Mundawar (303 days). Finally, the findings of this study are expected to be useful to agricultural scientists, policymakers and water resource managers., (© 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Ducrosia anethifolia (DC.) Boiss. is an aromatic medicinal plant that has been traditionally used as an analgesic to treat headaches, backaches, colic, and cold. This study evaluated the yield, physiological, and phytochemical traits of 24 populations for 2 consecutive years under the water stress condition. The seed yield and physiological traits demonstrated the highest values in the first and second year, respectively. Hydrogen peroxide (H 2 O 2 ), proline, malondialdehyde (MDA), and antioxidant activity enzymes were elevated, while chlorophyll, carotenoids, relative water content (RWC), and yield decreased under drought stress. High-performance liquid chromatography (HPLC) was also applied to assess the changes in some polyphenolic compounds in response to water stress. The increase in some phenolic compounds, such as p-coumaric acid, was recorded due to drought stress, while there was a decrease in flavonoids, that is luteolin and quercetin. Among the populations, Abarkuh2 indicated the highest increase in p-coumaric acid (96%) in response to drought stress. In general, high diversity among the studied populations provides new insights into choosing the beneficial populations for medicinal and food purposes. HIGHLIGHTS: • Changes in polyphenolics of Moshgak populations were obtained in response to water stress. • Gallic acid, ferulic acid, p-coumaric acid and vanillic acid were the major components. • The phenolic compounds was increased due to drought stress while flavonoids were decreased High variation was obtained between Moshgak populations., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.)

Tropical forest function is of global significance to climate change responses, and critically determined by water availability patterns. Groundwater is tightly related to soil water through the water table depth (WT), but historically neglected in ecological studies. Shallow WT forests (WT < 5 m) are underrepresented in forest research networks and absent in eddy flux measurements, although they represent c. 50% of the Amazon and are expected to respond differently to global-change-related droughts. We review WT patterns and consequences for plants, emerging results, and advance a conceptual model integrating environment and trait distributions to predict climate change effects. Shallow WT forests have a distinct species composition, with more resource-acquisitive and hydrologically vulnerable trees, shorter canopies and lower biomass than deep WT forests. During 'normal' climatic years, shallow WT forests have higher mortality and lower productivity than deep WT forests, but during moderate droughts mortality is buffered and productivity increases. However, during severe drought, shallow WT forests may be more sensitive due to shallow roots and drought-intolerant traits. Our evidence supports the hypothesis of neglected shallow WT forests being resilient to moderate drought, challenging the prevailing view of widespread negative effects of climate change on Amazonian forests that ignores WT gradients, but predicts they could collapse under very strong droughts., (© 2022 The Authors. New Phytologist © 2022 New Phytologist Foundation.)

Drought is the most widespread natural disaster in the world. How to monitor regional drought scientifically and accurately has become a hot topic for many scholars. In this paper, Geographically Integrated Dryness Index (GIDI) was integrated from an assortment source including Precipitation Condition Index (PCI), Temperature Condition Index (TCI), Soil Moisture Condition Index (SMCI), Vegetation Condition Index (VCI), and Standardized Precipitation Evapotranspiration Index (SPEI) (as the dependent variable) based on geographically weighted regression method. Besides, the comprehensive drought situation and changing trends in China from 2001 to 2019 were also examined. The results showed that (1) GIDI has excellent performance in monitoring medium- and long-term droughts and the monitoring results shows 2003, 2016, and 2019 were relatively wet years, while 2007, 2009, and 2011 were major drought years, and spring and March were the most frequent droughts season and month, respectively, and (2) except for the middle and upper reaches of the Yellow River and Northeastern China, which have a tendency to become wet, other places have a tendency to fluctuating dry. This study took advantage of simple and efficient methods to integrate existing indices to obtain a new index for monitoring a wider range of droughts, taking into account the physical mechanism of drought formation and the time scale of drought development, so it can scientifically evaluate the spatial and temporal distribution characteristics of drought and changes., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

We report on survival and growth of ponderosa pines (Pinus ponderosa Douglas ex P. Lawson & C. Lawson) 2 decades after forest restoration treatments in the G. A. Pearson Natural Area, northern Arizona. Despite protection from harvest that conserved old trees, a dense forest susceptible to uncharacteristically severe disturbance had developed during more than a century of exclusion of the previous frequent surface-fire regime that ceased upon Euro-American settlement in approximately 1876. Trees were thinned in 1993 to emulate prefire-exclusion forest conditions, accumulated forest floor was removed, and surface fire was re-introduced at 4-years intervals (full restoration). There was also a partial restoration treatment consisting of thinning alone. Compared with untreated controls, mortality of old trees (mean age 243 years, maximum 462 years) differed by <1 tree ha -1 and old-tree survival was statistically indistinguishable between treatments (90.5% control, 92.3% full, 82.6% partial). Post-treatment growth as measured by basal area increment of both old (pre-1876) and young (post-1876) pines was significantly higher in both treatments than counterpart control trees for more than 2 decades following thinning. Drought meeting the definition of megadrought affected the region almost all the time since the onset of the experiment, including 3 years that were severely dry. Growth of all trees declined in the driest 3 years, but old and young treated trees had significantly less decline. Association of tree growth with temperature (negative correlation) and precipitation (positive correlation) was much weaker in treated trees, indicating that they may experience less growth decline from warmer, drier conditions predicted in future decades. Overall, tree responses after the first 2 decades following treatment suggest that forest restoration treatments have led to substantial, sustained improvement in the growth of old and young ponderosa pines without affecting old-tree survival, thereby improving resilience to a warming climate., (© 2022 The Ecological Society of America.)

A major goal in ecology is to make generalizable predictions of organism responses to environmental variation based on their traits. However, straightforward relationships between traits and fitness are rare and likely to vary with environmental context. Characterizing how traits mediate demographic responses to the environment may enhance the predictions of organism responses to global change. We synthesized 15 years of demographic data and species-level traits in a shortgrass steppe to determine whether the effects of leaf and root traits on growth and survival depended on seasonal water availability. We predicted that (1) species with drought-tolerant traits, such as lower leaf turgor loss point (TLP) and higher leaf and root dry matter content (LDMC and RDMC), would be more likely to survive and grow in drier years due to higher wilting resistance, (2) these traits would not predict fitness in wetter years, and (3) traits that more directly measure physiological mechanisms of water use such as TLP would best predict demographic responses. We found that graminoids with more negative TLP and higher LDMC and RDMC had higher survival rates in drier years. Forbs demonstrated similar yet more variable responses. Graminoids grew larger in wetter years, regardless of traits. However, in both wet and dry years, graminoids with more negative TLP and higher LDMC and RDMC grew larger than less negative TLP and low LDMC and RDMC species. Traits significantly mediated the impact of drought on survival, but not growth, suggesting that survival could be a stronger driver of species' drought response in this system. TLP predicted survival in drier years, but easier to measure LDMC and RDMC were equal or better predictors. These results advance our understanding of the mechanisms by which drought drives population dynamics, and show that abiotic context determines how traits drive fitness., (© 2022 The Ecological Society of America.)

Shifts in flowering phenology are important indicators of climate change. However, the role of precipitation in driving phenology is far less understood compared with other environmental cues, such as temperature. We use a precipitation reduction gradient to test the direction and magnitude of effects on reproductive phenology and reproduction across 11 plant species in a temperate grassland, a moisture-limited ecosystem. Our experiment was conducted in a single, relatively wet year. We examine the effects of precipitation for species, functional types, and the community. Our results provide evidence that reduced precipitation shifts phenology, alters flower and fruit production, and that the magnitude and direction of the responses depend on functional type and species. For example, early-blooming species shift toward earlier flowering, whereas later-blooming species shift toward later flowering. Because of opposing species-level shifts, there is no overall shift in community-level phenology. This study provides experimental evidence that changes in rainfall can drive phenological shifts. Our results additionally highlight the importance of understanding how plant functional types govern responses to changing climate conditions, which is relevant for forecasting phenology and community-level changes. Specifically, the implications of divergent phenological shifts between early- and late-flowering species include resource scarcity for pollinators and seed dispersers and new temporal windows for invasion., (© 2022 The Authors. New Phytologist © 2022 New Phytologist Foundation.)

Drought is considered among the most perilous events with catastrophic consequences, particularly from the agro-economic point of view. These consequences are expected to exacerbate under the increasing meteorological aberrations due to changing climate, which necessitates investigating drought variabilities. This study presents a thorough spatiotemporal assessment of drought trends and variabilities over the agriculture-dominated Marathwada Region, Maharashtra, India. The precipitation data is extracted from the India Meteorological Department (IMD) gridded product, whereas actual evapotranspiration (ET) and Evaporative Stress Index (ESI) are obtained from Global Land Evaporation Amsterdam Model (GLEAM) datasets. Standardized Precipitation Index (SPI) is used to characterize drought occurrences at multiple time frames, whereas non-parametric tests, i.e., modified Mann-Kendall (MMK) and Sen's slope (SS) tests, are employed to detect trends. The results reveal the region to be prone to droughts, and SPI at a longer time frame (i.e., 12-monthly moving frame) can capture drought occurrences better than the shorter time frames, which can be attributed to the lesser randomness in the time series in the longer frame. A mix of positive/negative trends of SPI series are found for the monsoonal months; however, they are relatively more concentrated towards negative Z MMK . Hence, the Marathwada Region can be inferred to have exhibited a relatively increased tendency towards drought occurrences. The seasonal differences in mean values and trends of rainfall, ET, and ESI are discussed in detail. Since the Marathwada Region has a monsoon-dominated climate with high agricultural importance, the information reported in this study will help in devising water management strategies to minimize the repercussions of droughts., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Drought episodes across the Himalayas are inevitable due to rapidly increasing atmospheric temperatures and uncertainties in rainfall patterns. Tarai of Nepal is a tropical region located in the foothills of the Central Himalaya as a country's food granary with a contribution of over 50% to the entire country's agricultural production. However, there is a lack of detailed studies exploring the spatiotemporal occurrence of drought in these regions under the changing climate. In this study, we used the ensemble of nine climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) under two shared socio-economic pathways (SSPs), namely SSP245 (an intermediate development pathway) and SSP585 (a high development pathway), to assess anticipated drought during the mid-century. We used bias-corrected gridded data from the Worldclim to project drought events by the end of the mid-century based on the historical period (1989-2018). We computed historical and projected Thornthwaite moisture index (TMI) to evaluate soil moisture conditions on a seasonal scale for the Tarai region's Eastern, Central, and Western parts. The model ensemble projected a significant increase in precipitation and temperature for the entire Tarai by the end of mid-century. However, the winter and spring seasons are projected to suffer precipitation deficiency and a temperature rise. Our results indicated that the Eastern Tarai would likely experience a decrease in winter precipitation. We emphasize that the presented spatiotemporal pattern of the MI will be instrumental in addressing the irrigation facility's needs, choice, and rotation of crops under the changing climate scenarios and in improving our mitigation measures and adaptation plans for sustainability of the agriculture in drought-prone areas., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Drought is an extreme event and its frequency is expected to increase in future under the imminent threats of climate change. The areas vulnerable to drought are increasing due to increase in the spatial extent and severity of droughts. This necessitates the need for development of an integrated framework for assessment of drought vulnerability, which will be vital for water resources management policies focused towards such vulnerable areas. An integrated drought vulnerability assessment framework has been developed considering the physical indicators that vary spatially, social indicators that vary spatially but their temporal variation may be at longer time-frames, and spatio-temporal drought indicators that vary spatially and temporally during various months during drought years. This framework has been tested for Bina basin located in the drought prone Bundelkhand region of Madhya Pradesh. The drought indicators used in the study include (i) Standardized Precipitation Index (SPI) for evaluating meteorological drought characteristics, (ii) Surface water Drought Index (SDI) for evaluating streamflow drought characteristics, and (iii) Groundwater Drought Index (GDI) for evaluating groundwater drought characteristics. Groundwater levels are being observed at quarterly (3 monthly) time step only. So the relationships between GDI and 3-m SPI, 6-m SPI, and 12-m SPI have been investigated. Based on the best correlation, the 12-m SPI can be used to represent the groundwater drought in Bina basin and has therefore been used to assess the monthly variability in the groundwater drought characteristics. The spatially varying physical indicators including basin reach (elevation band), land use pattern and soil type; the spatio-temporal drought indicators including soil moisture drought, surface water drought and groundwater drought, rainfall departure and number of consecutive dry days; and the spatially varying social indicators including infants and young children, illiterate population, marginal workers and rural population have been used for the development of a Drought Vulnerability Index (DVI). The integrated drought vulnerability assessment framework has been conceptualized on the basis of DVI. Four vulnerability classes have been defined and the study area falls in mild to moderate vulnerable class, based on the analysis carried out for the various drought years in the basin. Appropriate drought management plans and mitigation strategies need to be developed to target these vulnerable areas in Bina basin., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

With the intensification of global warming, frequency of floods and droughts has been increasing. Understanding their long-term characteristics and possible relationship with large-scale meteorological factors is essential. In this study, we apply signal denoising, dimensionality reduction technique, and wavelet transform to study the spatiotemporal distribution pattern of drought/flood and its teleconnection with large-scale climate indices. Based on the precipitation data of 63 hydrological stations in the Taihu Lake Basin (TLB) for 54 years from 1965 to 2018, the standard precipitation index (SPI) was used as an indicator. The ensemble empirical mode decomposition (EEMD) and empirical orthogonal function (EOF) methods were used to explore the spatiotemporal evolution characteristics of droughts and floods. In addition, the cross-wavelet transform (XWT) method was used for teleconnection analysis. The results indicated that during 1965-2018, the SPI of the TLB showed quasiperiodic oscillations dominated by interannual oscillations (52.5%). Except for the trend of drought in spring, the basin showed a wetter trend at annual, summer, autumn, and winter scales. There were two main spatial modes (total 78.48% contribution) in the TLB, consistent across the region and reverse distributed from south to north. The dry areas were mainly in southern Zhexi and the northern Huxi sub-regions; the Hangjiahu and Yangchengdianmao sub-regions were prone to flooding. In addition, SPI was correlated with various large-scale meteorological factors, but the strength of the correlation had specific temporal and spatial heterogeneity. The research results can provide TLB reference values for water resource management and flood/drought disaster control., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

In recent decades, climatic pressures have altered the forested landscape of Bavaria. Widespread loss of trees has unevenly impacted the entire state, of which 37% is covered by forests (5% more than the national average). In 2018 and 2019—due in large part to drought and subsequent insect infestations—more tree-covered areas were lost in Bavaria than in any other German state. Moreover, the annual crown condition survey of Bavaria has revealed a decreasing trend in tree vitality since 1998. We conducted a systematic literature review regarding the remote sensing of forests in Bavaria. In total, 146 scientific articles were published between 2008 and 2023. While 88 studies took place in the Bavarian Forest National Park, only five publications covered the whole of Bavaria. Outside of the national park, the remaining 2.5 million hectares of forest in Bavaria are understudied. The most commonly studied topics were related to bark beetle infestations (24 papers); however, few papers focused on the drivers of infestations. The majority of studies utilized airborne data, while publications utilizing spaceborne data focused on multispectral; other data types were under-utilized- particularly thermal, lidar, and hyperspectral. We recommend future studies to both spatially broaden investigations to the state or national scale and to increase temporal data acquisitions together with contemporaneous in situ data. Especially in understudied topics regarding forest response to climate, catastrophic disturbances, regrowth and species composition, phenological timing, and in the sector of forest management. The utilization of remote sensing data in the forestry sector and the uptake of scientific results among stakeholders remains a challenge compared to other heavily forested European countries. An integral part of the Bavarian economy and the tourism sector, forests are also vital for climate regulation via atmospheric carbon reduction and land surface cooling. Therefore, forest monitoring remains centrally important to attaining more resilient and productive forests. [ABSTRACT FROM AUTHOR]

Drought has broad and deep impacts on vegetation. Studies on the effects of drought on vegetation have been conducted over years. Recently, the cumulative effect of drought is recognized as another key factor affecting plant growth. However, global-scale studies on this phenomenon are still lacking. Thus, based on new satellite based gross primary productivity (GPP) and multi-temporal scale Standardized Precipitation Evapotranspiration Index data sets, we explored the cumulative effect duration (CED) of drought on global vegetation GPP and analyzed its variability across elevations and climatic zones. The main findings were as follows: (1) The cumulative effect of drought on GPP was widespread, with an average CED of 4.89 months. (2) CED of drought on GPP varied among vegetation types. Specifically, grasslands showed the longest duration, with an average value of 5.28 months, followed by shrublands (5.09 months), wetlands (5.03 months), croplands (4.85 months), savannas (4.58 months), and forestlands (4.57 months). (3) CED of drought on GPP changes with climate conditions. It decreased with the decrease of precipitation in the driest month (P dry ) and mean annual precipitation in tropical and arid climate zones, respectively. In both temperate and cold climate zones, CED of drought on GPP was shorter in areas with dry winter than that in areas with dry summer. It increased with the decrease of mean annual air temperature in tropical climate zones and decreased with the increase of summer temperature in temperate and cold climatic zones. (4) With increasing elevation, CED of drought on GPP showed a pattern of increasing (0-3000 m), then decreasing (3000-5000 m), and increasing again (>5000 m). Our findings highlight the heterogeneity of CED of drought on GPP, owing to differences in vegetation types, long-term hydrothermal conditions, elevation, etc. The results could deepen our understanding of the effects of drought on global vegetation., (© 2022 John Wiley & Sons Ltd.)

Global warming is expected to enhance drought extremes in the United States throughout the twenty-first century. Projecting these changes can be complex in regions with large variability in atmospheric and soil moisture on small spatial scales. Vapor Pressure Deficit (VPD) is a valuable measure of evaporative demand as moisture moves from the surface into the atmosphere and a dynamic measure of drought. Here, VPD is used to identify short-term drought with the Standardized VPD Drought Index (SVDI); and used to characterize future extreme droughts using grid dependent stationary and non-stationary generalized extreme value (GEV) models, and a random sampling technique is developed to quantify multimodel uncertainties. The GEV analysis was performed with projections using the Weather Research and Forecasting model, downscaled from three Global Climate Models based on the Representative Concentration Pathway 8.5 for present, mid-century and late-century. Results show the VPD based index (SVDI) accurately identifies the timing and magnitude short-term droughts, and extreme VPD is increasing across the United States and by the end of the twenty-first century. The number of days VPD is above 9 kPa increases by 10 days along California's coastline, 30-40 days in the northwest and Midwest, and 100 days in California's Central Valley., (© 2022. The Author(s).)

A study on the reaction to the extreme drought in 2021 of the German plum cultivars, such as Topgigant plus; Topking; Top 2000; Topfive; Topend plus; Top; Topper; p 33-6-94; Topstar plus; Tophit, was conducted, analyzing the climate factors temperature and precipitation amount, compared to the last 20 years (base climate period). The reproductive manifestations of the cultivars and the chemical composition of fruit were monitored. The colour characteristics and density (firmness) of fresh fruit were reported. The lowest annual (606.1 mm) and vegetation (285 mm) amount of precipitation was registered in 2021 compared to the last 20 years (base climate period). The prolonged drought resulted in smaller fruit weight from 5-10 g to 30 g in the case of the large-fruited Topgigant plus compared to the previous year. The highest qualitative indicator of colour tone is registered for Topgigant plus (a/b=0.77) fruit, and fruit flesh in Topstar plus (a/b=0.06). In p 33-6-94, drought had the least impact on reproductive, chemical and colour indicators, compared to the other studied cultivars. [ABSTRACT FROM AUTHOR]

Our limited understanding of the impacts of drought on tropical forests significantly impedes our ability in accurately predicting the impacts of climate change on this biome. Here, we investigated the impact of drought on the dynamics of forest canopies with different heights using time-series records of remotely sensed Ku-band vegetation optical depth (Ku-VOD), a proxy of top-canopy foliar mass and water content, and separated the signal of Ku-VOD changes into drought-induced reductions and subsequent non-drought gains. Both drought-induced reductions and non-drought increases in Ku-VOD varied significantly with canopy height. Taller tropical forests experienced greater relative Ku-VOD reductions during drought and larger non-drought increases than shorter forests, but the net effect of drought was more negative in the taller forests. Meta-analysis of in situ hydraulic traits supports the hypothesis that taller tropical forests are more vulnerable to drought stress due to smaller xylem-transport safety margins. Additionally, Ku-VOD of taller forests showed larger reductions due to increased atmospheric dryness, as assessed by vapor pressure deficit, and showed larger gains in response to enhanced water supply than shorter forests. Including the height-dependent variation of hydraulic transport in ecosystem models will improve the simulated response of tropical forests to drought., (© 2021 John Wiley & Sons Ltd.)