Search

The Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI), two drought indices, have been compared for interchangeability and reliability under various climatic conditions in Gujarat, India. As the quality of the input is crucial for the accuracy of the index, weather records from surface observatories are preferable over grid and reanalysis data. This study found that on a short timescale (1-3 months), SPEI diagnosed mild and moderate droughts more frequently than SPI, particularly in stations with relatively heavy rainfall. The indices in all timescales at all sites throughout the monsoon months displayed strong positive associations (r > 0.8). The correlation decreases but remains positive as the temporal scale is extended up to 8 months. On a 9-months or longer scales that encompassed active monsoon rainfall months at all stations, correlation coefficients were between 0.8 and 0.9 for all months of the year. During monsoon months, high fractional matches were observed on a short scale. The months after the monsoon show a generalized diagonal pattern of high fractional match with the timescale for all stations. The kappa statistic followed a broad pattern comparable to the match fractions. The instances with poor agreements (R, Match and kappa < 0.3) had proportional bias between the indices. SPEI recognized more drought events at all stations in the short time periods, while the agreements increased with longer time scales. However, SPI detects high intensities in the subhumid., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

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.)

Eastern Thailand and Rayong province face perennial drought and water scarcity due to natural characteristics of climate and geology. Therefore, increasing water surface by man-made reservoirs is one of the priorities in the regional development plan to provide water adequately for industrial purposes, domestic consumption, and agriculture. The large reservoir constructions may induce land use, land cover changes (LULCC), yet it also is expected to alleviate the drought harshness in the region. By delineating Landsat satellite images and spatial analysis, this study revealed the LULCC in Rayong from 1990 to 2020. The most prominent LULCC was surface water expansion, about 10.9% per year, yet the increase was the most substantial in the first decade rather than the last two decades. Vegetation expansion was observed, contributing to an increase in forests/plantations and intensified agriculture by 39.19% and 25.54%, respectively. The LULCC corresponded to a 3.64% increase in ecosystem service values (ESV), implying positive benefits from the LULCC. Vegetation drought conditions monitored by the vegetation health index (VHI) exhibited an improvement trend, especially in the eastern basins. The development of artificial reservoirs was proven to stimulate the expansion of intensive agriculture and vegetation drought mitigation with spatial heterogeneity, spreading mainly across areas of the basins rather than remote areas. The research findings inform the efficiency of the reservoirs and irrigation systems regarding the beneficial effects on drought mitigation and water scarcity for agricultural cultivation. They also provide spatial information on areas still hindered by water problems that should be addressed in future strategies., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Adaptive responses to climate change, based on heritable variation in stress tolerance, may be important for plant population persistence. It is unclear which populations will mount the strongest future adaptive responses. It may be fruitful to identify populations that have escaped trade-offs among performance traits, which can hinder adaptation. Barring strong genetic constraints, the extent of trade-offs may depend on spatial relationships among climate variables shaping different traits. Here, we test for climate-driven ecotypic variation and trade-offs among drought and freezing sensitivity, and growth, for Lemmon's willow (Salix lemmonii) in a common garden study of 90 genotypes from 38 sites in the Sierra Nevada, USA. Salix lemmonii exhibits ecotypic variation in leaf turgor loss point, a measure of drought sensitivity, from -0.95 to -0.74 MPa along a gradient of spring snowpack. We also find variation in spring freezing sensitivity with minimum May temperature. However, we find no trade-off, as the climatic gradients shaping these traits are spatially uncorrelated in our study region, despite being negatively correlated across the Sierra Nevada. Species may escape adaptive trade-offs in geographic regions where climate variables are spatially decoupled. These regions may represent valuable reservoirs of heritable adaptive phenotypic variation., (© 2024 The Author(s). New Phytologist © 2024 New Phytologist Foundation.)

Assessing drought is crucial for effective water resources management and the development of mitigation strategies. Drought indices serve as indispensable tools in this evaluation process, and choosing an appropriate index is vital for accurate drought assessment. The characteristics and classification of drought depend entirely on the chosen index. Based on the existing literature, the Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) are the most commonly and widely used indices, and there is a significant need for a comprehensive comparison between SPI and SPEI to understand their differences and implications for drought assessment. This research aims to compare SPI and SPEI based on drought indices, characteristics, and classifications using the innovative drought classification matrix (IDCM) for spatiotemporal drought evaluation, and the comparison process is done for events and monthly scales. Also, it aims to investigate the comparison between SPEI obtained from in situ meteorological stations and from the SPEI database. The application and the comparison are presented for Istanbul city between 1951 and 2020. The results show similar variations and high correlation (more than 0.65) between SPI and SPEI. For drought characteristics, there is no consistent relationship between SPI and SPEI at the drought event scale. The outcomes revealed that approximately 60% of the months exhibit consistent drought classifications between the two indices. Finally, it shows a significant difference between SPEI based on in situ meteorological stations and satellite data. The comparison between SPI and SPEI based on different aspects is necessary and essential for drought studies and water resources management., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

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.)

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.)

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).)

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.)

Numerous recent studies have argued that moisture limitation is leading to growth declines and mortality of black spruce (Picea mariana) and white spruce (Picea glauca) in the North American boreal forest. A parallel line of research suggests that increasingly common severe wildfires are altering successional pathways and leading to long‐term replacement of spruce forests with those dominated by paper birch (Betula papyrifera, Betula neoalaskana) and trembling aspen (Populus tremuloides). When both conifers and deciduous trees establish after fire, this biome shift hypothesis implicitly assumes that deciduous species will outcompete the conifers, owing to their more rapid vertical growth and because they might be less sensitive to warm and dry conditions.We established a research site in a white spruce‐paper birch forest on an east‐facing slope in interior Alaska and tested the hypothesis that Alaska paper birch are better adapted to warm and dry conditions than white spruce. Over 6 years (2013–2018), we made hourly measurements of microclimate and xylem sap flux of both species. We also collected increment cores and conducted climate‐growth analyses for both species.During our 6‐year study, growing seasons with low volumetric soil water content (SWC) were those that followed shallow winter snowpacks and had limited summer rainfall, not necessarily those with warm air temperature. Both species were sensitive to moisture limitation. The tree‐ring data revealed significant positive effects of cumulative water year precipitation on radial growth, with a steeper slope for paper birch than for white spruce. Radial growth of both species was also positively related to mean water year air temperature. Sap flux density declined progressively for white spruce over the range of observed SWC and abruptly for paper birch when SWC fell below ~15%.Synthesis. Our results show that, while paper birch might be less sensitive to mild drought than white spruce, it may be more sensitive to severe drought, raising questions about the ability of paper birch to outcompete co‐occurring white spruce in a drier climate. [ABSTRACT FROM AUTHOR]

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.)

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.)

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.)

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.)

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).)

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.)

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.)

Although anthropogenic climate change is expected to have caused large shifts in temperature and rainfall, the detection of human influence on global drought has been complicated by large internal variability and the brevity of observational records. Here we address these challenges using reconstructions of the Palmer drought severity index obtained with data from tree rings that span the past millennium. We show that three distinct periods are identifiable in climate models, observations and reconstructions during the twentieth century. In recent decades (1981 to present), the signal of greenhouse gas forcing is present but not yet detectable at high confidence. Observations and reconstructions differ significantly from an expected pattern of greenhouse gas forcing around mid-century (1950-1975), coinciding with a global increase in aerosol forcing. In the first half of the century (1900-1949), however, a signal of greenhouse-gas-forced change is robustly detectable. Multiple observational datasets and reconstructions using data from tree rings confirm that human activities were probably affecting the worldwide risk of droughts as early as the beginning of the twentieth century.

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 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.)

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).)

The leaf of a deciduous species completes its life cycle in a few months. During leaf maturation, osmolyte accumulation leads to a significant reduction of the turgor loss point (Ψ TLP ), a known marker for stomatal closure. Here we exposed two grapevine cultivars to drought at three different times during the growing season to explore if the seasonal decrease in leaf Ψ TLP influences the stomatal response to drought. The results showed a significant seasonal shift in the response of stomatal conductance to stem water potential (g s ~Ψ stem ), demonstrating that grapevines become increasingly tolerant to low Ψ stem as the season progresses in coordination with the decrease in Ψ TLP . We also used the SurEau hydraulic model to demonstrate a direct link between osmotic adjustment and the plasticity of g s ~Ψ stem . To understand the possible advantages of g s ~Ψ stem plasticity, we incorporated a seasonally dynamic leaf osmotic potential into the model that simulated stomatal conductance under several water availabilities and climatic scenarios. The model demonstrated that a seasonally dynamic stomatal closure threshold results in trade-offs: it reduces the time to turgor loss under sustained long-term drought, but increases overall gas exchange particularly under seasonal shifts in temperature and stochastic water availability. A projected hotter future is expected to lower the increase in gas exchange that plants gain from the seasonal shift in g s ~Ψ stem . These findings show that accounting for dynamic stomatal regulation is critical for understanding drought tolerance., (© 2021 The Authors. The Plant Journal published by Society for Experimental Biology and John Wiley & Sons Ltd.)

Extreme drought and increasing temperatures can decrease the resilience of plant communities to fires. Not only may extremely dry conditions during or after fires lead to higher plant mortality and poorer recruitment, but severe pre-fire droughts may reduce the seed production and belowground vigor that are essential to post-fire plant recovery, and may indirectly facilitate invasion. We studied survival, recruitment, and growth of shrubs and herbs in chaparral (shrubland) communities in Northern California after a 2015 fire that immediately followed California's extreme 3-yr drought. We followed the same protocols used to study similar, adjacent communities after a 1999 fire that did not follow a drought, and we compared the two recovery trajectories. Overall, the 2015 fire was not more severe than the 1999 fire, yet it caused higher mortality and lower growth of resprouting shrubs on fertile (sandstone) soils. In contrast, the 2015 fire did not affect the mortality or growth of resprouting shrubs on infertile (serpentine) soils, the density of shrub seedlings, or the richness or cover of native herbs differently than the 1999 fire. However, the 2015 fire facilitated a massive increase in exotic herbaceous cover, especially on fertile soils, possibly portending the early stages of a type conversion to exotic-dominated grassland. Our findings indicate that the consequences of climate change on fire-dependent communities will include effects of pre-fire as well as post-fire climate, and that resprouting shrubs are particularly likely to be sensitive to pre-fire drought., (© 2021 by the Ecological Society of America.)

Agricultural drought risk analysis is useful for reducing probable drought risk in the background of global warming. This study aims to identify spatiotemporal characteristics of drought and drought disaster risk in the summer maize growth period under climate change condition. In this research, we use daily datasets from 79 meteorological stations and the maize yield data in the Huang-Huai-Hai (HHH) plain, eastern China during the period 1960-2015. The drought disaster risk index (DDRI) model was applied to assess the drought disaster risk. The maize drought disaster risk maps were drawn under current and future climate change conditions. The results showed that the high DDRI was distributed in northern region and low DDRI was distributed in most of southern region in the HHH plain. During the summer maize growth period, the DDRI decreased gradually from the northern to southern region. The results also exhibited that under the RCP4.5 (Representative Concentration Pathway 4.5) scenario, about one half of the HHH plain belonged to the slight and sub-slight DDRI region in the future 80 years. Overall, our results demonstrated that the DDRI model provided an accurate assessment in both spatial and temporal scales and had a theoretical guidance for improving the adaptation of crop production. Elevating maize drought risk management helps to lessen the anticipated risk to crop production in the HHH plain under the context of climate change.

The world including South Africa is faced with unprecedented environmental changes, which can be linked to climate-related disasters such as drought and extreme heat. Several studies have indicated that these changes are likely to accelerate in the future and cause an adverse impact on the environment. The Eastern Cape Province of South Africa, especially Amathole District Municipality (ADM), has recorded a high number of climate change-related disasters including prolonged drought conditions witnessed during the winter season of 2008, 2009, 2014 and 2015 among others. Consequently, this study aimed at exploring remote sensing information to assess and document drought occurrences in the ADM from 2007 to 2017. To accomplish the aim, the Normalized Difference Vegetation Index, Land Surface Temperature and Precipitation were utilised to access drought spatiotemporal variations. For the analysis, a total of 396 satellite imageries (MODIS and TRMM) were used. The results revealed that different correlations exist between the three variables. The significance of correlations differed from one season to another. Furthermore, it was revealed that the drought conditions in the district differed in the spatial distribution. The study accurately identified the drought episodes that occurred in the ADM in the years 2008, 2009, 2014, 2015 and 2016. The chosen methodology and variables proved to be suitable for analysing drought conditions offering space and temporal variation dimension, which is vital in monitoring drought events.

In the open literature, there are numerous studies on the normal and extreme (flood and drought) behavior of wet and dry periods based on the understanding of the standard precipitation index (SPI), which provides a series of categorizations by considering the standard normal (Gaussian) probability distribution function (PDF). The numerical meaning of each categorization assessment is quite lacking in terms of future predictions of wet and dry period duration based on historical records. This paper presents a new approach for calculating possible formations of future wet and dry period durations based on historical records through an effective fractal geometric forecasting approach. The essence of the proposed methodology is based on the number of dry periods (steps) of non-overlapping monthly duration along consecutive broken line paths in the SPI classification for wet and dry period durations. It has been observed that the plot of periods on double logarithmic paper falls along a straight line against the number of such periods, implying a power function, which is the essence of fractal geometry. Extending the empirically derived straight line provides the number of periods that may occur in the future over a range of SPI levels. This methodology is referred to as SPI fractal (SPIF), and the classic SPI classification is converted into SPIF wet and dry polygons, which provide additional information about the drought period number within a valid polygonal area, compared to the classic SPI results. The wet and dry period features of any hydro-meteorology time series are constrained in SPIF polygons. The application of the methodology was carried out on monthly rainfall records on the European side of the Istanbul Florya meteorological station in Turkey. [ABSTRACT FROM AUTHOR]

Knowledge of how water stress impacts the carbon and water cycles is a key uncertainty in terrestrial biosphere models. We tested a new profit maximization model, where photosynthetic uptake of CO 2 is optimally traded against plant hydraulic function, as an alternative to the empirical functions commonly used in models to regulate gas exchange during periods of water stress. We conducted a multi-site evaluation of this model at the ecosystem scale, before and during major droughts in Europe. Additionally, we asked whether the maximum hydraulic conductance in the soil-plant continuum k max (a key model parameter which is not commonly measured) could be predicted from long-term site climate. Compared with a control model with an empirical soil moisture function, the profit maximization model improved the simulation of evapotranspiration during the growing season, reducing the normalized mean square error by c. 63%, across mesic and xeric sites. We also showed that k max could be estimated from long-term climate, with improvements in the simulation of evapotranspiration at eight out of the 10 forest sites during drought. Although the generalization of this approach is contingent upon determining k max , it presents a mechanistic trait-based alternative to regulate canopy gas exchange in global models., (© 2020 The Authors. New Phytologist © 2020 New Phytologist Trust.)

Background: The function of 4-coumarate-CoA ligases (4CL) under abiotic stresses has been studied in plants, however, limited is known about the 4CL genes in cotton (G. hirsutum L.) and their roles in response to drought stress., Results: We performed genome-wide identification of the 4CL genes in G. hirsutum and investigated the expression profiles of the identified genes in various cotton tissues and in response to stress conditions with an aim to identify 4CL gene(s) associated with drought tolerance. We identified 34 putative 4CL genes in G. hirsutum that were clustered into three classes. Genes of the same class usually share a similar gene structure and motif composition. Many cis-elements related to stress and phytohormone responses were found in the promoters of the Gh4CL genes. Of the 34 Gh4CL genes, 26 were induced by at least one abiotic stress and 10 (including Gh4CL7) were up-regulated under the polyethylene glycol (PEG) simulated drought stress conditions. Virus-induced gene silencing (VIGS) in cotton and overexpression (OE) in Arabidopsis thaliana were applied to investigate the biological function of Gh4CL7 in drought tolerance. The Gh4CL7-silencing cotton plants showed more sensitive to drought stress, probably due to decreased relative water content (RWC), chlorophyll content and antioxidative enzyme activity, increased stomatal aperture, and the contents of malondialdehyde (MDA) and hydrogen peroxide (H 2 O 2 ). Arabidopsis lines overexpressing Gh4CL7, however, were more tolerant to drought treatment, which was associated with improved antioxidative enzyme activity, reduced accumulation of MDA and H 2 O 2 and up-regulated stress-related genes under the drought stress conditions. In addition, compared to their respective controls, the Gh4CL7-silencing cotton plants and the Gh4CL7-overexpressing Arabidopsis lines had a ~ 20% reduction and a ~ 10% increase in lignin content, respectively. The expression levels of genes related to lignin biosynthesis, including PAL, CCoAOMT, COMT, CCR and CAD, were lower in Gh4CL7-silencing plants than in controls. Taken together, these results demonstrated that Gh4CL7 could positively respond to drought stress and therefore might be a candidate gene for improvement of drought tolerance in cotton., Conclusion: We characterized the 4CL gene family in upland cotton and revealed a role of Gh4CL7 in lignin biosynthesis and drought tolerance.

Cysteine proteinases are involved in various physiological and developmental processes in plants. Two cDNAs from senescent and non-senescent tobacco leaves were isolated with degenerate primers designed from conserved regions of plant senescence-associated cysteine proteinases using rapid amplification of cDNA ends (RACE). Both sequences encode papain-like cysteine proteinases: the 833 bp fragment (NtCP1) encoding a C-terminus partial sequence of a putative tobacco cysteine proteinase gene whereas the 1300 bp fragment (NtCP2) is a full-length cysteine proteinase. On the amino acid sequence level, NtCP1 has a high similarity with other senescence-associated cysteine proteinases. It is expressed only in senescent leaves. It is not induced in mature green leaves upon exposure to drought or heat. These results suggest that it might be a good developmental senescence marker in tobacco. By contrast, NtCP2 has a high similarity to KDEL-tailed cysteine proteinases and is expressed in mature green leaves. Both drought and heat decreased NtCP2 transcript abundance in mature green leaves. It is concluded that NtCP1 is a senescence-specific cysteine proteinase whereas NtCP2 fulfils roles in green leaves that might be similar to those of KDEL-tailed cysteine proteinases involved, for example, in programmed cell death. [ABSTRACT FROM PUBLISHER]

Extensive dieback of salt marsh dominated by the perennial grass Spartina alterniflora occurred throughout the Mississippi River deltaic plain during 2000. More than 100,000 ha were affected, with 43,000 ha severely damaged. The aim of this work was to determine if sudden dieback could have been caused by a coincident drought and to assess the significance of this event with respect to long-term changes in coastal vegetation. Multiple dieback sites and reference sites were established along 150 km of shoreline in coastal Louisiana, USA. Aerial and ground surveys were conducted from June 2000 to September 2001 to assess soil conditions and plant mortality and recovery. Dieback areas ranged in size from ∼300 m2−5 km2 in area with 50–100% mortality of plant shoots and rhizomes in affected zones. Co-occurring species such as Avicennia germinans (black mangrove) and Juncus roemerianus (needlegrass rush) were unaffected. Historical records indicate that precipitation, river discharge, and mean sea level were unusually low during the previous year. Although the cause of dieback is currently unknown, plant and soil characteristics were consistent with temporary soil desiccation that may have reduced water availability, increased soil salinity, and/or caused soil acidification (via pyrite oxidation) and increased uptake of toxic metals such as Fe or Al. Plant recovery 15 months after dieback was variable (0–58% live cover), but recovering plants were vigorous and indicated no long-lasting effects of the dieback agent. These findings have relevance for global change models of coastal ecosystems that predict vegetation responses based primarily on long-term increases in sea level and submergence of marshes. Our results suggest that large-scale changes in coastal vegetation may occur over a relatively short time span through climatic extremes acting in concert with sea-level fluctuations and pre-existing soil conditions. [ABSTRACT FROM AUTHOR]

Unclassified roads comprise 60% of the road network in the United Kingdom (UK). The resilience of this locally important network is declining. It is considered by the Institution of Civil Engineers to be "at risk" and is ranked 26th in the world. Many factors contribute to the degradation and ultimate failure of particular road sections. However, several UK local authorities have identified that in drought conditions, road sections founded upon shrink/swell susceptible clay soils undergo significant deterioration compared with sections on non-susceptible soils. This arises from the local road network having little, if any structural foundations. Consequently, droughts in East Anglia have resulted in millions of pounds of damage, leading authorities to seek emergency governmental funding. This paper assesses the use of soil-related geohazard assessments in providing soilinformed maintenance strategies for the asset management of the locally important road network of the UK. A case study draws upon the UK administrative county of Lincolnshire, where road assessment data have been analysed against mapped clay-subsidence risk. This reveals a statistically significant relationship between road condition and susceptible clay soils. Furthermore, incorporation of UKCP09 future climate projections within the geohazard models has highlighted roads likely to be at future risk of clay-related subsidence. [ABSTRACT FROM AUTHOR]

Drought stress has serious effects on the growth and yield of wheat in both productivity and quality and is an abiotic factor. Traditional methods of crop drought stress monitoring have some deficits. This work has been conducted in order to enhance these conventional methods by proposing a new deep learning approach. This paper has presented a deep learning-based model customized for monitoring drought stress in winter wheat during the critical growth stages. Drought-afflicted winter wheat images were captured at three crucial phases: rising–jointing, heading–flowering, and flowering–maturity. These images are correlated against soil moisture data to construct a comprehensive dataset. DenseNet121 was chosen as the network model since it extracts features from images relating to phenotypes. Several factors, like training methods, learning rate adjustment, and addition of the attention mechanism, are optimized in eight sets of experiments. This provided the final DenseNet-121 model with an average recognition accuracy of 94.67% on the test set, which means that monitoring drought stress during wheat growth's key periods is feasible and effective. [ABSTRACT FROM AUTHOR]

Summary: Drought is intensifying globally with climate change, creating an urgency to understand ecosystem response to drought both during and after these events end to limit loss of ecosystem functioning. The literature is replete with studies of how ecosystems respond during drought, yet there are far fewer studies focused on ecosystem dynamics after drought ends. Furthermore, while the terms used to describe drought can be variable and inconsistent, so can those that describe ecosystem responses following drought. With this review, we sought to evaluate and create clear definitions of the terms that ecologists use to describe post‐drought responses. We found that legacy effects, resilience and recovery were used most commonly with respect to post‐drought ecosystem responses, but the definitions used to describe these terms were variable. Based on our review of the literature, we propose a framework for generalizing ecosystem responses after drought ends, which we refer to as 'the post‐drought period'. We suggest that future papers need to clearly describe characteristics of the imposed drought, and we encourage authors to use the term post‐drought period as a general term that encompasses responses after drought ends and use other terms as more specific descriptors of responses during the post‐drought period. [ABSTRACT FROM AUTHOR]

Administrative strategies to cope with drought are steadily changing, from emergency procedures to day-to-day monitoring. More consideration must be paid to long-term and preventive drought control measures in the future. This paper discusses the risk of hydrological drought in the Yellow River Basin. The standardized runoff index (SRI) was used to characterize hydrological drought, and the run theory was used to identify drought states and quantify drought characteristic variables. Based on the drought severity and duration, a drought development plan was proposed and a three-dimensional copula function was constructed to obtain the joint distribution function of three-dimensional drought characteristic variables. A drought risk assessment system based on the loss × probability risk theory was constructed to explore the spatial and temporal characteristics of hydrological drought risk in the Yellow River Basin. Finally, according to the risk assessment results, the risk level was divided into low, medium and high risk, and a Bayesian network was used to explore the probability of hydrological drought. The main results are as follows: (1) From 1960 to 2018, the severity of hydrological drought in the Yellow River Basin increased, the duration lengthened, and the development speed accelerated. (2) The hydrological drought risk in the Yellow River Basin showed an overall upward trend, with the fastest increase in the HJ region of 0.041/10a. The highest annual average drought risk in the TDG region is 0.598. (3) The spatial transmission of hydrological drought risk is divided into three types: constant, enhanced and mitigation types, of which the constant type is the most common. The transmission probabilities of low, medium and high risk of hydrological drought from the HYK region to the low, medium and high risk of hydrological drought in the LJ region are 0.68, 0.66 and 0.78, respectively. [ABSTRACT FROM AUTHOR]

Alfalfa (Medicago sativa L.) is one of the most important forage crops in the world. Drought is recognized as a major challenge limiting alfalfa production and threatening food security. Although some literature reviews have been conducted in this area, bibliometric reviews based on large amounts of published data are still lacking. In this paper, a bibliometric analysis of alfalfa drought stress from 1998-2023 was conducted using the Web of Science Core Collection database in order to assess global trends in alfalfa drought stress research and to provide new directions for future research. The results showed that the annual publication output maintained an increase in most years, with China and the United States contributing significantly to the field. Most of the journals published are specialized journals in botany, environmental science, soil science and crop science, as well as related agribusiness journals. "plant growth" and "yield" were the most frequently used keywords, reflecting the important purpose of research in this field. And two main research directions were identified: research on drought response mechanism of alfalfa and exploration of drought-resistant technology. In addition, physiological, biochemical, and molecular responses of drought tolerance and high yield in alfalfa, transgenics, and microbial fertilizer research have been hot research topics in recent years and may continue in the future. The ultimate goal of this paper is to provide a foundational reference for future research on alfalfa's drought resistance and yield optimization mechanisms, thereby enhancing the crop's application in agricultural production. [ABSTRACT FROM AUTHOR]

This document discusses the challenges faced by plants in arid and semi-arid regions due to harsh environmental conditions such as limited rainfall, high temperatures, and poor soil nutrition. The document highlights the importance of understanding plant adaptation strategies to extreme environments in order to protect and manage local vegetation and ecosystems. The document presents research papers that cover various aspects of plant adaptation in arid regions, including water uptake mechanisms, physiological and biochemical adaptations, plant-soil microbial interactions, and ecosystem services. The research findings provide insights into how plants in arid regions adapt to environmental changes and maintain ecological balance. However, further research is needed to fully understand the processes and mechanisms of plant adaptation in extreme environments. [Extracted from the article]

Disaster Risk Management (DRM) is complex due to interacting climate risks from interacting hazards and sectors. We develop a synthetic multi‐risk test case to explore the effects of these interactions on decision‐making under deep uncertainty. The test case accounts for changes in hazard impacts and occurrence frequency due to interactions between floods and droughts. Interactions between the shipping, housing and agricultural sectors are considered as well. We use this test case to explore the utility of the Dynamic Adaptive Policy Pathways for Multi‐Risk (DAPP‐MR) framework. DAPP‐MR has been introduced to assess DRM policies' effectiveness under deep uncertainties and to develop integrated adaptive strategies considering interactions across hazards, sectors and time. With the test case, we show that the stage‐wise approach of DAPP‐MR, which gradually increases the complexity of the analysis, can facilitate the evaluation process. Earlier stages of the analysis can be used to establish the direct cause‐effect relations, later stages allow us to identify whether additional interacting factors have a significant effect on the direct cause‐effect relations. As a result, decision‐makers can gain insights into dependencies and their relevance for developing short‐to long‐term strategies under deep uncertainty. We show that multi‐risk interactions can lead to non‐linear effects that influence the outcome of the policy analysis, for example, the indirect influence of a decision in one sector on another. Future work could investigate further improving the operationalization of this staged approach as well as extending the set of uncertainties, dynamics and decision‐rules accounted for in the multi‐risk test case. Plain Language Summary: This paper addresses the complex challenge that many regions face when dealing with multiple interconnected disasters, like floods, droughts and earthquakes. Traditional Disaster Risk Management methods often fall short, particularly in long‐term planning that considers factors such as climate change. We apply a step‐by‐step approach known as "Dynamic Adaptive Policy Pathways for Multi‐Risk (DAPP‐MR)" to assist decision‐makers in better understanding and planning for these intertwined risks over time. This paper employs a hypothetical test case where different sectors (e.g., agricultural sector) seek effective ways to prepare for and respond to flood and drought risks. The DAPP‐MR method facilitates this by breaking down the process into smaller, more manageable steps. This approach allows for an easier understanding of the direct effects of disasters and gradually incorporates more complex interactions between different risks. Our findings suggest that this step‐by‐step method can aid decision‐makers in grasping the connections between various factors and their significance in formulating both short‐ and long‐term strategies. The study also reveals that interactions between different risks can produce unexpected, nonlinear effects, adding complexity to the interpretation of policy outcomes. Key Points: A multi‐risk modeling case with interacting hazards and sectors is created to explore effects for decision‐making under deep uncertaintyDynamic Adaptive Policy Pathways for Multi‐Risk has proven effective for pathway analysis to grasp interactions and their relevance through a structured, stage‐by‐stage approachMulti‐risk interactions can alter the decision‐making outcome because of changes in performance or timings of potential pathways [ABSTRACT FROM AUTHOR]

Changes in precipitation patterns with climate change could have important impacts on human and natural systems. Zhang et al. (2021, https://doi.org/10.1029/2020gl092293) report trends in daily precipitation patterns over the last five decades in the western United States, focusing on meteorological drought. They report that dry intervals (calculated at the annual or seasonal level) have increased across much of the southwestern U.S., with statistical assessment suggesting the results are statistically robust. However, Zhang et al. (2021, https://doi.org/10.1029/2020gl092293) preprocess their annual (or seasonal) averages to compute 5‐year moving window averages before using established statistical techniques for trend analysis that assume independence about some fixed trend. Here we show that the moving window preprocessing violates that independence assumption and inflates the statistical significance of their trend estimates. This raises questions about the robustness of their results. We conclude by discussing the difficulty of adjusting for spatial structure when assessing time trends in a regional context. Plain Language Summary: A recent paper reports trends in drought in the western United States, in particular increases in drought in the southwestern United States, based on changes in the lengths of time intervals without precipitation. In this "comment" we note that the preprocessing approach used in the paper artificially increases the apparent statistical signal in the data and caution that the evidence for the trends reported is not as strong as presented in the paper. We conclude by discussing the difficulty of estimating trends in a statistically rigorous fashion across multiple weather stations. Key Points: Statistical uncertainty about trends in droughts in the southwestern US is larger than reported in a recent GRL letter [ABSTRACT FROM AUTHOR]

Paciorek and Wehner raise important questions around our use of the Mann‐Kendall nonparametric trend test on smoothed data for analyzing long‐term hydrometeorological trends in Zhang et al. (2021, https://doi.org/10.1029/2020gl092293). We thank them for initiating this important conversation and their gracious cooperation in exploring the issues addressed in their comment. In this reply we confirm the inflation of significant p‐values by our choice to smooth, illustrate the relatively minor impacts on the main conclusions of our paper, and add our voices to those of Paciorek and Wehner in highlighting the lack of methodology for hypothesis testing across multiple stations that have spatial structure (i.e., testing for regionally consistent trends). Plain Language Summary: Our colleagues Drs. Paciorek and Wehner have raised concerns about our paper (Zhang et al., 2021, https://doi.org/10.1029/2020gl092293), which showed widespread increases in the duration of drought events over the last five decades in the western United States. They point out that our decision to smooth the data using a moving average inflated the number of weather stations at which the trends toward longer droughts were deemed significant by a statistical test. We agree with them on this point, and we have recomputed all our results using unsmoothed data to determine the impacts. We find that for most stations and regions, trend magnitudes remained largely unchanged, with many stations nearby one another often suggesting similar trends. Finally, we agree with Paciorek and Wehner that there is a lack of statistical methods to test such coherent regional patterns, and we caution that over‐reliance on p‐values limits the power of regional data to identify important climate trends. Key Points: We agree that smoothing to 5‐year moving windows introduced serial correlation into time series of annual statistics of daily rainfall data, inflating the number of weather stations individually showing significant trends (p < 0.05) with the Mann‐Kendall testRecomputation with unsmoothed values produced substantially the same dry intervals trend magnitude and direction at most stations individually and had only minimal impacts on dry interval trends computed for National Ecological Observatory Network domains using the Regional Kendall testNo perfect statistical approach leverages the capacity of coherent regional patterns among spatially correlated weather stations, and an over‐reliance on p‐values as a binary (significant vs. insignificant) determinant of trends limits the power of regional data [ABSTRACT FROM AUTHOR]