Drought Research Articles

Capturing drought stress signals: The potential of dendrometers for monitoring tree water status.

The severity of droughts is expected to increase with climate change, leading to more frequent tree mortality and a decline in forest ecosystem services. Consequently, there is an urgent need for monitoring networks to provide early warnings of drought impacts on forests. Dendrometers capturing stem diameter variations may offer a simple and relatively low-cost opportunity. However, the links between stem shrinkage, a direct expression of tree water deficit (TWD), and hydraulic stress are not well understood thus far. In this study, we exposed two widespread conifers Pinus sylvestris and Larix decidua to lethal dehydration by withholding water and closely monitored TWD, midday water potential ($\psi $), and midday stomatal conductance ($g_{s}$) under controlled greenhouse conditions. We found strong relationships between the three variables throughout the dehydration process, particularly suggesting the potential for continuous $\psi $ predictions and stomatal closure assessments. However, the relationships decoupled during recovery from severe drought. We also identified TWD thresholds that signal the onset of drought stress and tissue damage, providing insights into stress impacts and recovery potential. While these findings are promising, challenges remain in practically transferring them to field set-ups by suitable TWD normalization. Importantly, we observed that midday $g_{s}$ was drastically reduced when TWD persisted overnight, providing a directly applicable drought stress signal that does not require normalization. In conclusion, while challenges remain, our results highlight the potential of dendrometers for monitoring tree water dynamics. Implementing dendrometer networks could support the development of early-warning metrics for drought impacts, enabling large-scale monitoring in diverse settings, such as urban areas and forest ecosystems.

Detection and correlation analysis of seasonal vertical ground movement measured from SAR and drought conditions

Detection and correlation analysis of seasonal vertical ground movement measured from SAR and drought conditions

Investigating drought tolerance in four Argania spinosa provenances through morpho-physio-biochemical traits

ABSTRACT Drought stress significantly threatens plant ecosystems, particularly amid climate change. Understanding the mechanisms of plant resilience is essential for developing strategies to mitigate water scarcity effects on agroforestry. This study evaluated morphological, physiological and biochemical traits in Argania spinosa seedlings from four provenances (Berkane (BRK), Essaouira (ESS), Agadir (AGD) and Bouizakarne (BZK)) subjected to severe drought for three weeks. The results showed significant inter-provenance variation in the traits examined. Root dry biomass increased markedly across all provenances, with the highest increase observed in BZK (117.9%). Leaf water potential significantly decreased under drought stress, but relative water content (RWC) remained stable. Proline accumulation was significant in stressed seedlings, especially in ESS (163.4%), while total soluble sugars significantly increased only in BRK (26.6%). All provenances showed a significant reduction in chlorophyll a and b, except for BRK. Correlations among all studied traits varied significantly in both number and significance between drought stress and non-stress conditions. Canonical discriminant analysis revealed distinct separation among the provenances, indicating intra-species variability in drought responses. Key traits like dry biomass, collar diameter, basic leaf water potential, RWC and proline were identified as important indicators of drought tolerance, suggesting their utility in selecting the most resilient A. spinosa provenance.

Mapping of drought-induced changes in tissue characteristics across the leaf profile of Populus balsamifera.

Leaf architecture impacts the ease of gases diffusion, biochemical process, and photosynthetic performance. For balsam poplar, a widespread North American species, the influence of water availability on leaf anatomy and subsequent photosynthetic performance remains unknown. To address this shortcoming, we characterized the anatomical changes across the leaf profile in three-dimensional space for saplings subjected to soil drying and rewatering using X-ray microcomputed tomography. Our hypothesis was that higher abundance of bundle sheet extensions (BSE) minimizes drought-induced changes in intercellular airspace volume relative to mesophyll volume (i.e. mesophyll porosity, θIAS) and aids recovery by supporting leaf structural integrity. Leaves of 'Carnduff-9' with less abundant BSEs exhibited greater θIAS, higher spongy mesophyll surface area, reduced palisade mesophyll surface area, and less veins compared with 'Gillam-5'. Under drought conditions, Carnduff-9 showed significant changes in θIAS across leaf profile while that was little for 'Gillam-5'. Under rewatered conditions, drought-induced changes in θIAS were fully reversible in 'Gillam-5' but not in 'Carnduff-9'. Our data suggest that a 'robust' leaf structure with higher abundance of BSEs, reduced θIAS, and relatively large mesophyll surface area provides for improved photosynthetic capacity under drought and supports recovery in leaf architecture after rewatering in balsam poplar.

Are Climate Change Strategies Effective in Managing Urban Water Resources? The Case of Portugal

This study examines the relationship between climate mitigation, adaptation strategies, and water management practices in Portugal from 2015 to 2021. Utilizing climate and water resource data from 2015 to 2021, including meteorological data (emperature, rainfall), wastewater treatment volumes, and energy efficiency metrics, the data are sourced from national agencies such as IPMA, ERSAR, APA, and Eurostat. The methodology employs correlation analysis to assess the relationships between climate variables (e.g., temperature, rainfall) and water resource indicators (e.g., reclaimed wastewater, energy efficiency). Despite notable reductions in greenhouse gas emissions and improvements in wastewater treatment efficiency, water resource stability remains a complex issue, particularly with regional disparities such as severe droughts in the Algarve. Additionally, the study evaluates the effectiveness of rainwater harvesting systems, reclaimed wastewater, and infiltration facilities, revealing a decline in reclaimed wastewater efficiency despite increased wastewater treatment. Rainwater harvesting systems (RWHSs) offer resilience, but their broader adoption is hindered by high costs and public perception challenges. Key recommendations include the development of resilient infrastructure, enhanced support for reclaimed water use, and increased investment in research to address water management challenges amid climate variability.

Prominent Increase in Air Temperatures on Two Small Mediterranean Islands, Lastovo and Lošinj, Since 1998 and Its Effect on the Frequency of Extreme Droughts

The article analyzes the development of air temperatures and precipitation on two remote islands in the Adriatic Sea from 1961 to 2023, examining annual and monthly time scales. Lastovo Island is located in the southern Adriatic, and Lošinj Island is situated 277 km north, and both exhibit a sharp rise in air temperatures since 1998, though precipitation series show no significant trends of an increase or decrease. Using the New Drought Index (NDI) method, this study calculated drought intensities for the period 1961–2023. The analyses conducted in this study undoubtedly indicate a rising frequency and intensity of droughts, with severe droughts doubling and extreme droughts increasing fourfold in the recent period (1998–2023) compared to the previous one (1961–1997). The most pronounced increase in severe and extreme droughts occurs specifically from June to August. This trend is likely applicable to many small Mediterranean Islands, which number over 10,000 and have a permanent population of more than 1.6 million people, with numbers significantly rising during the tourist season. The increased water demand for agriculture and daily use, combined with increased drought risk, not only exacerbates the potential for forest fires but also threatens social structures and ecological conditions. This is particularly critical as the combination of drier conditions and increased fire risk poses a significant challenge, endangering natural landscapes and valuable historical sites that are integral to the islands’ identity and heritage. This study’s findings indicate a dangerous trend likely to persist and worsen with continued increases in air temperatures in the Mediterranean region.

Investigating the impacts of climate variations and armed conflict on drought and vegetation cover in Northeast Syria (2000–2023)

Over the last decades, The Northeast part of Syria (NES) has been significantly affected by multiple drought events, which are exacerbated by armed conflict and climate variations. In this study, the spatiotemporal effects of climate fluctuations on drought episodes and agricultural areas in NES from 2000 to 2023 were examined by utilizing diverse meteorological parameters combined with the normalized difference vegetation index. The relationships between the change in climatic variables and vegetation cover alterations were determined by performing different statistical methods, such as the Pearson correlation coefficient and Mann-Kendall trend analysis. The results indicated a significant decrease in the agricultural area, especially in recent years, accompanied by a notable increase in the precipitation levels. Moreover, there has been a substantial increase in temperatures, particularly in the minimum temperatures. The results also indicate that drought severity and frequency have increased since the armed conflict despite the area receiving higher precipitation amounts, highlighting the role and impacts of violence. Therefore, we recommend further research on how different vegetation species have been affected by climate change and armed conflict, defining specific growing seasons for each vegetation species, and creating land use land cover maps to understand the spatial alteration of these types better.

Disentangling the Complex Effects of Seasonal Drought, Floor Mass, and Roots on Soil Microbial Biomass in a Subtropical Moist Forest

Severe seasonal droughts driven by global climate change significantly alter the cycling of carbon and nutrients in forest ecosystems, while the investigation into the impacts of floor mass and plant roots on soil microbial biomass within the context of recurrent seasonal droughts is still rare. To investigate the environmental determinants governing soil microbial biomass with the escalating severity of seasonal droughts, we conducted a study in a montane subtropical moist evergreen broad-leaved forest in southwestern China from June 2019 to May 2023. The study results revealed that soil microbial biomass, as well as soil moisture, floor mass, and plant roots, showed an apparent single-hump modal within one year. In the comparative analysis of the soil microbial biomass fluctuation amplitudes across control and watered plots, a discernible disparity was observed, indicating significant differences in microbial biomass dynamics between the respective experimental conditions. The pooled data revealed a statistically significant influence of seasonal drought, floor mass, plant roots, and their reciprocal interactions on the soil microbial biomass, highlighting these factors as pivotal determinants of microbial community dynamics. This study elucidates the interactive regulatory mechanisms by which seasonal drought, floor mass, and plant roots collectively modulate soil microbial biomass within tropical and subtropical forests, offering insights into the complex ecological processes governing microbial community dynamics. This interactive regulation might influence the trajectory of plant species and soil microbial communities, facilitating their adaptive development and evolutionary responses.

Simulated sensitivity of the Amazon rainforest to extreme drought

Abstract The Amazon rainforest is highly biodiverse and the largest intact, tropical forest in the world. Undisturbed tropical forests act as a carbon sink by taking up about 15% of anthropogenic carbon emissions per year. In the past decades, a declining trend in the carbon sink capacity in the Amazon rainforest has been observed due to increased carbon losses and tree mortality. The causes are disputed, but increasing temperatures and more frequent severe droughts are potentially major drivers. We employ a novel modelling framework and hypothesize that previously rare, extreme droughts in the Amazon, such as the ones in 2005 and 2010, constitute the main cause behind the decline of the net carbon sink in aboveground biomass. Our dynamic vegetation model simulates process-based plant hydraulics and drought-induced mortality, and accounts for the diversity of strategies in plant responses to drought based on observed hydraulic vulnerability curves. The simulated impact of the 2005 drought event temporarily turned the annual Amazon net carbon sink to a carbon source of about 0.25 MgC ha-1. In contrast to other dynamic vegetation models our model simulated an increasing trend in carbon losses and a declining trend in the Amazon carbon sink over the past 25 years (net sink rate of -0.018 Mg C ha-1 year-1 or -0.22 Mg C ha-1 per decade) which corresponds well with long-term forest monitoring data (net sink rate of -0.016 Mg C ha-1 year-1). We show that this trend is entirely attributable to drought-induced forest mortality during extreme years. The simulations show a threshold-like behaviour between drought intensity and biomass loss, which is due to xylem vulnerability, indicating the potentially high sensitivity of Amazon forests to extreme drought. Further increases in the severity and frequency of droughts might thus lead to greater carbon release and tree mortality than previously assumed.

Subsidence and Uplift in Active and Closed Lignite Mines: Impacts of Energy Transition and Climate Change

This study examines the combined effects of decommissioning lignite mining operations and long-term climate trends on groundwater systems and land surface movements in the Konin region of Poland, which is characterised by extensive open-pit lignite extraction. The findings reveal subsidence rates ranging from −26 to 14 mm per year within mining zones, while land uplift of a few millimetres per year occurred in closed mining areas between 2015 and 2022. Groundwater levels in shallow Quaternary and deeper Paleogene–Neogene aquifers have declined significantly, with drops of up to 26 m observed near active mining, particularly between 2009 and 2019. A smaller groundwater decline of around a few metres was observed outside areas influenced by mining. Meteorological data show an average annual temperature of 8.9 °C from 1991 to 2023, with a clear warming trend of 0.0050 °C per year since 2009. Although precipitation patterns show a slight increase from 512 mm to 520 mm, a shift towards drier conditions has emerged since 2009, characterised by more frequent dry spells. These climatic trends, combined with mining activities, highlight the need for adaptive groundwater management strategies. Future research should focus on enhanced monitoring of groundwater recovery and sustainable practices in post-mining landscapes.

SAM-ResNet50: A Deep Learning Model for the Identification and Classification of Drought Stress in the Seedling Stage of Betula luminifera

Betula luminifera, an indigenous hardwood tree in South China, possesses significant economic and ecological value. In view of the current severe drought situation, it is urgent to enhance this tree’s drought tolerance. However, traditional artificial methods fall short of meeting the demands of breeding efforts due to their inefficiency. To monitor drought situations in a high-throughput and automatic approach, a deep learning model based on phenotype characteristics was proposed to identify and classify drought stress in B. luminifera seedlings. Firstly, visible-light images were obtained from a drought stress experiment conducted on B. luminifera shoots. Considering the images’ characteristics, we proposed an SAM-CNN architecture by incorporating spatial attention modules into classical CNN models. Among the four classical CNNs compared, ResNet50 exhibited superior performance and was, thus, selected for the construction of the SAM-CNN. Subsequently, we analyzed the classification performance of the SAM-ResNet50 model in terms of transfer learning, training from scratch, model robustness, and visualization. The results revealed that SAM-ResNet50 achieved an accuracy of 1.48% higher than that of ResNet50, at 99.6%. Furthermore, there was a remarkable improvement of 18.98% in accuracy, reaching 82.31% for the spatial transform images generated from the test set images by applying movement and rotation for robustness testing. In conclusion, the SAM-ResNet50 model achieved outstanding performance, with 99.6% accuracy and realized high-throughput automatic monitoring based on phenotype, providing a new perspective for drought stress classification and technical support for B. luminifera-related breeding work.

Examining wildfire dynamics using ECOSTRESS data with machine learning approaches: the case of South‐Eastern Australia's black summer

Wildfires are increasing in risk and prevalence. The most destructive wildfires in decades in Australia occurred in 2019–2020. However, there is still a challenge in developing effective models to understand the likelihood of wildfire spread (susceptibility) and pre‐fire vegetation conditions. The recent launch of NASA's ECOSTRESS presents an opportunity to monitor fire dynamics with a high resolution of 70 m by measuring ecosystem stress and drought conditions preceding wildfires. We incorporated ECOSTRESS data, vegetation indices, rainfall, and topographic data as independent variables and fire events as dependent variables into machine learning algorithms applied to the historic Australian wildfires of 2019–2020. With these data, we predicted over 90% of all wildfire occurrences 1 week ahead of these wildfire events. Our models identified vegetation conditions with a 3‐week time lag before wildfire events in the fourth week and predicted the probability of wildfire occurrences in the subsequent week (fifth week). ECOSTRESS water use efficiency (WUE) consistently emerged as the leading factor in all models predicting wildfires. Results suggest that the pre‐fire vegetation was affected by wildfires in areas with WUE above 2 g C kg−1 H₂O at 95% probability level. Additionally, the ECOSTRESS evaporative stress index and topographic slope were identified as significant contributors in predicting wildfire susceptibility. These results indicate a significant potential for ECOSTRESS data to predict and analyze wildfires and emphasize the crucial role of drought conditions in wildfire events, as evident from ECOSTRESS data. Our approaches developed in this study and outcome can help policymakers, fire managers, and city planners assess, manage, prepare, and mitigate wildfires in the future.

The Need to Maintain the Quality of Naturally Pure Water of Sarayu River

Rivers are a link between human life and nature. All the ancient developed cities are situated on the banks of some river or the other ancient civilizations of India have developed on the banks of rivers. The river is helpful in both, flood and drought conditions, works to balance nature by absorbing the flood water inside itself and giving water to animals and humans during drought. In the present scenario, due to the increasing population of cities and the pollution arising from it, the water of rivers is getting polluted rapidly. Many rivers of the country are slowly disappearing and some rivers have water only during monsoon. Our country is slowly moving towards water crisis. To get out of this crisis, we all need a corrective change in behaviour along with scientific remedial system. The per capita availability of water has decreased significantly in the last 75 years. According to one figure, in 1951 the per capita was 5177 cubic meters but in the year 2011 only 1545 cubic meters of water is available per person. According to a study by the National Institute of Hydrology, India will have only 814 cubic meters of usable water per capita in 2025. When we studied the water of Sarayu river, it was found that all the parameters and heavy metals present in the water raised after monsoon are within the processed limit. When the properties of the water of Sarayu river were studied, surprising results came out. All the elements present in the water like calcium, magnesium, chloride, fluoride, alkalinity, nitrate ion, sulphate ion, arsenic and manganese etc. were within the required limits. Desirable limits of calcium, magnesium, chloride, alkalinity, nitrate ion, sulphate ion are 75 mg/l, 30 mg/l, 25 mg/l, 200 mg/l, 200 mg/l, respectively. The maximum values in pre-monsoon were found to be 38.47 mg/l, 26.24 mg/l, 15.9 mg/l, 192 mg/l, 0.20 mg/l and 20.10 mg/l respectively and in post-monsoon its maximum value was found to be 28.86 mg/l, 12.49 mg/l, 17.99 mg/l, 128 mg/l, 1.5 mg/l and 41.30 mg/l, respectively. The desirable limit of arsenic is 0.01, found to be 0.01 at some places in pre-monsoon but found to be nil in post-monsoon.

Correlation Analysis of Vertical Ground Movement and Climate Using Sentinel-1 InSAR

Seasonal vertical ground movement (SVGM), which refers to the periodic vertical displacement of the Earth’s surface, has significant implications for infrastructure stability, agricultural productivity, and environmental sustainability. Understanding how SVGM correlates with climatic conditions—such as temperatures and drought—is essential in managing risks posed by land subsidence or uplift, particularly in regions prone to extreme weather events and climate variability. The correlation of periodic SVGM with climatic data from Earth observation was investigated in this work. The European Ground Motion Service (EGMS) vertical ground movement measurements, provided from 2018 to 2022, were compared with temperature and precipitation data from MODIS and CHIRP datasets, respectively. Measurement points (MP) from the EGMS over Italy provided a value for ground vertical movement approximately every 6 days. The precipitation and temperature datasets were processed to provide drought code (DC) maps calculated ad hoc for this study at a 1 km spatial resolution and daily temporal resolution. Seasonal patterns were analyzed to assess correlations with Spearman’s rank correlation coefficient (ρ) between this measure and the DCs from the Copernicus Emergency Management Service (DCCEMS), from MODIS + CHIRP (DC1km) and from the temperature. The results over the considered area (Italy) showed that 0.46% of all MPs (32,826 MPs out of 7,193,676 MPs) had a ρ greater than 0.7; 12,142 of these had a positive correlation, and 20,684 had a negative correlation. DC1km was the climatic factor that provided the highest number of correlated MPs, roughly giving +59% more correlated MPs than DCCEMS and +300% than the temperature data. If a ρ greater than 0.8 was considered, the number of MPs dropped by a factor of 10: from 12,142 to 1275 for positive correlations and from 20,684 to 2594 for negative correlations between the DC1km values and SVGM measurements. Correlations that lagged in time resulted in most of the correlated MPs being within a window of ±6 days (a single satellite overpass time). Because the DC and temperature are strongly co-linear, further analysis to assess which was superior in explaining the seasonality of the MPs was carried out, resulting in DC1km significantly explaining more variance in the SVGM than the temperature for the inversely correlated points rather than the directly correlated points. The spatial distribution of the correlated MPs showed that they were unevenly distributed in clusters across the Italian territory. This work will lead to further investigation both at a local scale and at a pan-European scale. An interactive WebGIS application that is open to the public is available for data consultation. This article is a revised and expanded version of a paper entitled “Detection and correlation analysis of seasonal vertical ground movement measured from SAR and drought condition” which was accepted and presented at the ISPRS Mid-Term Symposium, Belem, Brasil, 8–12 November 2024. Data are shared in a public repository for the replication of the method.

Polycaprolactone-zinc oxide biocomposite membranes for wastewater treatment by ultrafiltration process: Synthesis, characterization and removal of inorganic pollutants

The severe droughts impacting North Africa have intensified the pressure on potable water supplies and agricultural irrigation, highlighting the urgent need for sustainable water management solutions. This study explores the potential of poly(ε-caprolactone)/zinc oxide (PCL/ZnO) biocomposites as ultrafiltration membranes for treating urban wastewater, with the goal of enabling water reuse in agriculture. PCL/ZnO membranes, fabricated using the solvent-casting method, were thoroughly characterized using FTIR, XRD, EDAX, SEM, AFM, DSC, TGA, and water contact angle (WCA) measurements. Key findings revealed that increasing ZnO content (1–4 wt%) significantly enhanced membrane thickness, crystallinity, mechanical robustness, and surface roughness, while lowering WCA values to improve hydrophilicity. These enhanced properties are critical for ultrafiltration, as they contribute to higher contaminant rejection and improved water permeability. Performance tests demonstrated ion retention rates of 32–61 % post-filtration, including for toxic metals, effectively reducing pollutant levels. Notably, the treated water met the Food and Agriculture Organization (FAO) standards for irrigation quality, indicating its suitability for agricultural applications. This work highlights the efficacy of PCL/ZnO membranes in facilitating sustainable wastewater recycling under drought conditions, presenting a promising, adaptable solution for water reclamation in water-scarce regions. The results underscore the potential of these biocomposite membranes to advance sustainable water treatment practices, supporting both environmental resilience and agricultural productivity.

Zoysia spp. putting green tolerance to postemergence herbicides

AbstractSpecies of Zoysia Willd. are used on approximately 9550 ha of golf course surfaces throughout the United States, primarily fairways and tees in transitional climates. Recently, cultivars featuring dwarf canopy height and improved quality have been released for putting green use; however, tolerance of these cultivars to postemergence herbicides is unknown. Field research was conducted in 2021 and 2022 evaluating the tolerance of Prizm® [Zoysia matrella (L.) Merr.] and Lazer® [Z. matrella (L.) Merr. × Zoysia minima (Colenso) Zotov] zoysiagrass to pyrimisulfan + penoxsulam (Aethon™), pyrimisulfan (Arkon™), flazasulfuron (Katana®), 2,4‐D + quinclorac + dicamba + sulfentrazone (Q4® Plus), 2,4‐D + MCPP + dicamba + carfentrazone (SpeedZone® EW), 2,4‐D + MCPP + dicamba + sulfentrazone (Surge®), and pyrimisulfan (formulated as a granule; Vexis®). A nontreated check was included for comparison. All of these herbicides have commercial labeling for use on zoysiagrass (Zoysia Willd.); however, none of these herbicides have labeling for use on zoysiagrass putting greens. Application rates in this study exceeded label maximums (for use on zoysiagrass) to ascertain the upper limits of Prizm® and Lazer® tolerance to these herbicides in Knoxville, TN and College Station, TX, respectively. Plots were arranged in randomized complete block design with four replications at both sites. Turfgrass injury was visually evaluated with data subjected to analysis of variance. Prizm® in Tennessee exhibited commercially acceptable tolerance to the applied herbicides, resulting in ≤8% injury either year. Lazer® in Texas sustained injury ranging from 21% to 61% and 10% to 31% in 2021 and 2022, respectively. Conditions of extreme heat and drought in Texas may have exacerbated differences in Lazer® tolerance to applied herbicides between years. Additional research across varying geographies and environmental conditions is needed to better understand tolerance of new zoysiagrass putting green lines, particularly within Z. minima.

How Severe Was the 2022 Flash Drought in the Yangtze River Basin?

Flash droughts, characterized by their rapid onset and severe impacts, have critical implications for the ecological environment and water resource security. However, inconsistent definitions of flash droughts have hindered scientific assessments of drought severity, limiting efforts in disaster prevention and mitigation. In this study, we propose a new method for explicitly characterizing flash drought events, with particular emphasis on the process of soil moisture recovery. The temporal and spatial evolution of flash droughts over the Yangtze River Basin was analyzed, and the severity of the extreme flash drought in 2022 was assessed by comparing its characteristics and impacts with those of three typical dry years. Additionally, the driving factors of the 2022 flash drought were evaluated from multiple perspectives. Results indicate that the new identification method for flash droughts is reasonable and reliable. In recent years, the frequency and duration of flash droughts have significantly increased, with the Dongting Lake and Poyang Lake basins being particularly affected. Spring and summer were identified as peak seasons for flash droughts, with the middle reaches most affected in spring, while summer droughts tend to impact the entire basin. Compared to 2006, 2011, and 2013, the flash drought in 2022 affected the largest area, with the highest number of grids experiencing two flash drought events and a development rate exceeding 15%. Moreover, the summer heat in 2022 was more extreme than in the other three years, extending from spring to fall, especially during July–August. Its evolution was driven by the Western Pacific Subtropical High, which suppressed precipitation and elevated temperatures. The divergence of water vapor flux intensified water shortages, while anomalies in latent and sensible heat fluxes increased surface evaporation and heat transfer, further disturbing the regional water cycle. This study provides valuable insights for flash drought monitoring and early warning in the context of a changing climate.

Assessment of Soil Moisture in Vegetation Regions of Mu Us Sandy Land Using Several Aridity Indicators

Drought, a significant calamity in the natural domain, has extensive worldwide repercussions. Drought, primarily characterized by reduced soil moisture (SM), presents a significant risk to both the world environment and human existence. Various drought indicators have been suggested to accurately represent the changing pattern of SM. The study examines various indices related to the Drought Severity Index (DSI), Evaporation Stress Index(ESI), Vegetation Supply Water Index(VSWI), Temperature-Vegetation Dryness Index(TVDI), Temperature Vegetation Precipitation Dryness Index(TVPDI), Vegetation Health Index(VHI), and Temperature Condition Index (TCI). An evaluation was conducted to assess the effectiveness of seven drought indicators, such as DSI, ESI, TVPDI, VSWI, etc., in capturing the changes in SM in Mu Us Sandy Land. The research results indicated that DSI and ESI had the highest accuracy, while TVDI and VSWI showed relatively lower accuracy. However, their smaller fluctuations in the time series demonstrated stronger adaptability to different regions. Additionally, the delayed impact of aridity indices on soil moisture, variable attributes, temperature, and vegetation coverage in sandy land and grassland areas with low, medium, and high coverage all contributed to the effectiveness of the four aridity indices (DSI, ESI, VSWI, and TVPDI) in capturing the dynamics of soil moisture. The primary element that affects the effectiveness of TVDI is the divergence of the relationship curve between Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI), which is a kind of deterioration. This paper presents a very efficient approach for monitoring soil moisture dynamics in dry and semi-arid regions. It also analyzes the patterns of soil moisture changes, offering valuable scientific insights for environmental monitoring and ecological enhancement.

Diverging Projections of Future Droughts in High‐End Climate Scenarios for Different Potential Evapotranspiration Methods: A National‐Scale Assessment for Poland

ABSTRACTIt has been broadly reported that future climate change will most likely affect the spatio‐temporal distribution of water resources and consequently droughts. There is a prevailing notion that an increase in temperature and frequency of heat waves are expected to result in more intense droughts in the coming years. In this study, we aimed to evaluate the effect of the potential evapotranspiration (PET) method selection on future drought projections over Poland. In our study, simulations of the Soil and Water Assessment Tool (SWAT) model were conducted, utilising an ensemble of six EURO‐CORDEX projections, spanning the period from 2006 to 2100 under the RCP8.5 scenario. Two model setups with two different PET methods (Penman‐Monteith—PM and Hargreaves—HAR) were used. For drought conditions evaluation we selected the Standardized Precipitation Index (SPI) and Standardized Precipitation‐Evapotranspiration Index (SPEI) for meteorological drought, Standardized Streamflow Index (SSI) for hydrological drought, and Standardized Soil Moisture Index (SMI) for agricultural drought. The meteorological and hydrological droughts were calculated using a 12‐month time aggregation window, while agricultural drought was calculated using a 3‐month window. Climate projections revealed that by 2080s annual mean temperature and precipitation increase is expected by up to +3.4°C and +10.3% respectively. Under future climate conditions duration and severity of meteorological droughts are projected to decrease. PM method leads to a higher PET increases (1.35 mm year−1) than the HAR method (1.1 mm year−1) throughout the century which entail diverging signal of change for agricultural and hydrological droughts. PM‐ and HAR‐based simulations indicate increase in the total duration and cumulative severity of agricultural droughts, buthowever, for HAR‐based projections, the increase is much less. For hydrological droughts the signal of change is similar for both PET methods, but considerably distinct in magnitude. Considering the entire simulation period, by the end of the century cumulative severity of hydrological droughts is projected to decrease, with a much more pronounced decline for HAR (70% reduction) than for the PM method (35% reduction). Our study demonstrated that methodological choices are crucial to the assessment of future drought risk under climate change.

Influence of previous drought exposure on the 3D microstructure of the cambium and developing xylem in Eucalyptus clones: An X-ray CT investigation

Summary In plant biology research, X-ray computed tomography (CT) has been demonstrated to be useful for studying the complex tissues of trees qualitatively and quantitatively. The cambium plays a very important role in plant growth and development. However, this tissue is relatively poorly studied due to its complex nature and its localization between layers of xylem and phloem cells. Antecedent environmental conditions may have a substantial impact on plant responses to drought and recovery dynamics. Therefore, this study aimed to investigate the impact of previous drought exposure on the 3D microstructure of two commercial Eucalyptus clones by monitoring the development of the cambium, in the same plant and same area of cambial tissue, during a 4-week trial consisting of well-watered, mild drought, severe drought, and rewatering phases. To track microstructural changes, the plants were imaged weekly with non-destructive X-ray micro-computed tomography (μCT). On the last day of the experiment, X-ray nano-CT was also performed. Our results indicate that trees subjected to earlier well-watered conditions were more affected by the severe drought, compared to those previously exposed to mild drought conditions. Thus, previous exposure to water deficit may provide the benefit of increased drought tolerance during future water deficit. Previous mild drought exposure can facilitate morphological adjustments, which potentially enhances drought tolerance during subsequent drought events.