Persistent multi-scale fluctuations shift European hydroclimate to its millennial boundaries

Can we identify tipping points of resilience loss in Mediterranean rangelands under increased summer drought?

Mediterranean ecosystems are predicted to undergo longer and more intense summer droughts. The mechanisms underlying the response of herbaceous communities to such drier environments should be investigated to identify the resilience thresholds of Mediterranean rangelands. A 5-year experiment was conducted in deep and shallow soil rangelands of southern France. A rainout shelter for 75 days in summer imposed drier and warmer conditions. Total soil water content was measured monthly to model available daily soil water. Aboveground net primary production (ANPP), forage quality, and the proportion of graminoids in ANPP were measured in spring and autumn. Plant senescence and plant cover were assessed in summer and spring, respectively. The experimental years were among the driest ever recorded at the site. Therefore, manipulated summer droughts were drier than long-term ambient conditions. Interactions between treatment, community type, and experimental year were found for most variables. In shallow soil communities, spring plant cover decreased markedly with time. This legacy effect, driven by summer plant mortality and the loss of perennial graminoids, led to an abrupt loss of resilience when the extreme water stress index exceeded 37 mm 10 day-1, characterized by a reduction of spring plant cover below 50% and a decreased ANPP in rainy years. Conversely, the ANPP of deep soil communities remained unaffected by increased summer drought, although the presence of graminoids increased and forage nutritive value decreased. This study highlights the role of the soil water reserve of Mediterranean plant communities in modulating ecosystem responses to chronically intensified summer drought. Communities on deep soils were resilient, but communities on shallow soils showed a progressive, rapid, and intense degradation associated with a loss of resilience capacity. Notably, indexes of extreme stress were a better indicator of tipping points than indexes of integrated annual stress. Considering the role of soil water availability in other herbaceous ecosystems should improve the ability to predict the resilience of plant communities under climate change.

Climate oscillation impacts on water supply augmentation planning

Climate oscillations ranging from years to decades drive precipitation variability in many river basins globally. As a result, many regions will require new water infrastructure investments to maintain reliable water supply. However, current adaptation approaches focus on long-term trends, preparing for average climate conditions at mid- or end-of-century. The impact of climate oscillations, which bring prolonged and variable but temporary dry periods, on water supply augmentation needs is unknown. Current approaches for theory development in nature-society systems are limited in their ability to realistically capture the impacts of climate oscillations on water supply. Here, we develop an approach to build middle-range theory on how common climate oscillations affect low-cost, reliable water supply augmentation strategies. We extract contrasting climate oscillation patterns across sub-Saharan Africa and study their impacts on a generic water supply system. Our approach integrates climate model projections, nonstationary signal processing, stochastic weather generation, and reinforcement learning-based advances in stochastic dynamic control. We find that longer climate oscillations often require greater water supply augmentation capacity but benefit more from dynamic approaches. Therefore, in settings with the adaptive capacity to revisit planning decisions frequently, longer climate oscillations do not require greater capacity. By building theory on the relationship between climate oscillations and least-cost reliable water supply augmentation, our findings can help planners target scarce resources and guide water technology and policy innovation. This approach can be used to support climate adaptation planning across large spatial scales in sectors impacted by climate variability.

Historical information sheds new light on the intensification of flooding in the Central Mediterranean

Hydrological disasters, such as floods, can have dire consequences for human societies. Historical information plays a key role in detecting whether particular types of hydrological disasters have increased in frequency and/or magnitude and, if so, they are more likely attributable to natural or human-induced climatic and other environmental changes. The identification of regions with similar flood conditions is essential for the analysis of regional flooding regimes. To this end, we here present the longest existing flood reconstruction for the Eastern Liguria Area (ELA) in northwestern Italy, covering 1582 to 2022 CE, which offers a case study representative of the central Mediterranean region. An Annual Flood Intensification Index was developed to transform the historical data into a continuous annual hydrological time-series contained by a homogeneous data structure for the study-area. We found two change-points (trend breaks) in the reconstructed time-series, in 1787 and 1967, with only occasional heavy floods comparable to present-day disasters occurring before the first change-point, and an increasing intensification of floods after the second change-point up to the present day. The recent intensification of flooding in the ELA, associated with changes in land use and land cover, also appears to coincide with phases in which hydrological hazards have become more changeable and extreme in disaster-affected areas. This is evidenced by river basin responses to human-induced disturbances.

Shifts in flood generation processes exacerbate regional flood anomalies in Europe

Anomalies in the frequency of river floods, i.e., flood-rich or -poor periods, cause biases in flood risk estimates and thus make climate adaptation measures less efficient. While observations have recently confirmed the presence of flood anomalies in Europe, their exact causes are not clear. Here we analyse streamflow and climate observations during 1960-2010 to show that shifts in flood generation processes contribute more to the occurrence of regional flood anomalies than changes in extreme rainfall. A shift from rain on dry soil to rain on wet soil events by 5% increased the frequency of flood-rich periods in the Atlantic region, and an opposite shift in the Mediterranean region increased the frequency of flood-poor periods, but will likely make singular extreme floods occur more often. Flood anomalies driven by changing flood generation processes in Europe may further intensify in a warming climate and should be considered in flood estimation and management.

The Impact of Climate Change on the Reliability of Water Resources

Climate change impact assessment is crucial for strategic planning in many areas, including water management, agriculture and forestry. Water planning has a long tradition in the Czech Republic, who has implemented the requirements of the Water Framework Directive since 2000. Following the expected impacts of climate change on the hydrological regime, adaptation measures in the water sector are being prepared as part of strategic plans. This contribution studies the uncertainty propagation of climate scenarios in hydrological data, which are then used to assess the reliability of water resources and to design appropriate adaptation measures. The results are being discussed for a case study in the deficit area of Rakovnický stream and Blšanska river basins, which are among the driest areas in the Czech Republic. Research of the impact of climate change on the reliability of water resources has been prepared using ensembles of selected regional climate models. This approach has allowed a probabilistic assessment of the impact on the hydrology regime and the reliability of water supply from reservoirs for various time horizons of climate change. In view of the relatively large variance of potential impacts on water resources, options for further strategic planning in the water management area are being discussed.

Spatial and Temporal Analysis of Dry and Wet Spells in the Wadi Cheliff Basin, Algeria

The Mediterranean Basin, located in a transition zone between the temperate and rainy climate of central Europe and the arid climate of North Africa, is considered a major hotspot of climate change, subject to water scarcity and drought. In this work, dry and wet spells have been analyzed in the Wadi Cheliff basin (Algeria) by means of annual precipitation observed at 150 rain gauges in the period 1970–2018. In particular, the characteristics of dry and wet spells (frequency, duration, severity, and intensity) have been evaluated by means of the run theory applied to the 12-month standardized precipitation index (SPI) values. Moreover, in order to detect possible tendencies in the SPI values, a trend analysis has been performed by means of two non-parametric tests, the Theil–Sen and Mann–Kendall test. The results indicated similar values of frequency, severity, duration, and intensity between the dry and the wet spells, although wet events showed higher values in the extreme. Moreover, the results of the trend analysis evidenced a different behavior between the northern side of the basin, characterized by a negative trend in the 12-month SPI values, and the southern side, in which positive trends were detected.

Global-scale massive feature extraction from monthly hydroclimatic time series: Statistical characterizations, spatial patterns and hydrological similarity

Hydroclimatic time series analysis focuses on a few feature types (e.g., autocorrelations, trends, extremes), which describe a small portion of the entire information content of the observations. Aiming to exploit a larger part of the available information and, thus, to deliver more reliable results (e.g., in hydroclimatic time series clustering contexts), here we approach hydroclimatic time series analysis differently, i.e., by performing massive feature extraction. In this respect, we develop a big data framework for hydroclimatic variable behaviour characterization. This framework relies on approximately 60 diverse features and is completely automatic (in the sense that it does not depend on the hydroclimatic process at hand). We apply the new framework to characterize mean monthly temperature, total monthly precipitation and mean monthly river flow. The applications are conducted at the global scale by exploiting 40-year-long time series originating from over 13 000 stations. We extract interpretable knowledge on seasonality, trends, autocorrelation, long-range dependence and entropy, and on feature types that are met less frequently. We further compare the examined hydroclimatic variable types in terms of this knowledge and, identify patterns related to the spatial variability of the features. For this latter purpose, we also propose and exploit a hydroclimatic time series clustering methodology. This new methodology is based on Breiman's random forests. The descriptive and exploratory insights gained by the global-scale applications prove the usefulness of the adopted feature compilation in hydroclimatic contexts. Moreover, the spatially coherent patterns characterizing the clusters delivered by the new methodology build confidence in its future exploitation. Given this spatial coherence and the scale-independent nature of the delivered feature values (which makes them particularly useful in forecasting and simulation contexts), we believe that this methodology could also be beneficial within regionalization frameworks, in which knowledge on hydrological similarity is exploited in technical and operative terms.

The rise of compound warm-season droughts in Europe

Drought is one of the main threats to food security and ecosystem productivity. During the past decades, Europe has experienced a series of droughts that caused substantial socioeconomic losses and environmental impacts. A key question is whether there are some similar characteristics in these droughts, especially when compared to the droughts that occurred further in the past. Answering this question is impossible with traditional single-index approaches and also short-term and often spatially inconsistent records. Here, using a multidimensional machine learning-based clustering algorithm and the hydrologic reconstruction of European drought, we determine the dominant drought types and investigate the changes in drought typology. We report a substantial increase in shorter warm-season droughts that are concurrent with an increase in potential evapotranspiration. If shifts reported here persist, then we will need new adaptive water management policies and, in the long run, we may observe considerable alterations in vegetation regimes and ecosystem functioning.

Current European flood-rich period exceptional compared with past 500 years

There are concerns that recent climate change is altering the frequency and magnitude of river floods in an unprecedented way¹. Historical studies have identified flood-rich periods in the past half millennium in various regions of Europe². However, because of the low temporal resolution of existing datasets and the relatively low number of series, it has remained unclear whether Europe is currently in a flood-rich period from a long-term perspective. Here we analyse how recent decades compare with the flood history of Europe, using a new database composed of more than 100 high-resolution (sub-annual) historical flood series based on documentary evidence covering all major regions of Europe. We show that the past three decades were among the most flood-rich periods in Europe in the past 500 years, and that this period differs from other flood-rich periods in terms of its extent, air temperatures and flood seasonality. We identified nine flood-rich periods and associated regions. Among the periods richest in floods are 1560-1580 (western and central Europe), 1760-1800 (most of Europe), 1840-1870 (western and southern Europe) and 1990-2016 (western and central Europe). In most parts of Europe, previous flood-rich periods occurred during cooler-than-usual phases, but the current flood-rich period has been much warmer. Flood seasonality is also more pronounced in the recent period. For example, during previous flood and interflood periods, 41 per cent and 42 per cent of central European floods occurred in summer, respectively, compared with 55 per cent of floods in the recent period. The exceptional nature of the present-day flood-rich period calls for process-based tools for flood-risk assessment that capture the physical mechanisms involved, and management strategies that can incorporate the recent changes in risk.

An Index-Flood Statistical Model for Hydrological Drought Assessment

Modelling of hydrological extremes and drought modelling in particular has received much attention over recent decades. The main aim of this study is to apply a statistical model for drought estimation (in this case deficit volume) using extreme value theory and the index-flood method and to reduce the uncertainties in estimation of drought event return levels. Deficit volumes for 133 catchments in the Czech Republic (1901–2015) were simulated by hydrological model BILAN. The validation of severity, intensity and length of simulated drought events revealed good match with the available observed data. To estimate return levels of the deficit volumes, it is assumed (in accord with the index-flood method), that the deficit volumes within a homogeneous region are identically distributed after scaling with a site-specific factor. The parameters of the scaled regional distribution are estimated using L-moments. The goodness-of-fit of the statistical model is assessed by Anderson–Darling test. For the estimation of critical values, sampling methods allowing for handling of years without drought were used. It is shown, that the index-flood model with a Generalized Pareto distribution performs well and substantially reduces the uncertainty related to the estimation of the shape parameter and of the large deficit volume quantiles.

The climatic drivers of primary Picea forest growth along the Carpathian arc are changing under rising temperatures

Climatic constraints on tree growth mediate an important link between terrestrial and atmospheric carbon pools. Tree rings provide valuable information on climate-driven growth patterns, but existing data tend to be biased toward older trees on climatically extreme sites. Understanding climate change responses of biogeographic regions requires data that integrate spatial variability in growing conditions and forest structure. We analyzed both temporal (c. 1901-2010) and spatial variation in radial growth patterns in 9,876 trees from fragments of primary Picea abies forests spanning the latitudinal and altitudinal extent of the Carpathian arc. Growth was positively correlated with summer temperatures and spring moisture availability throughout the entire region. However, important seasonal variation in climate responses occurred along geospatial gradients. At northern sites, winter precipitation and October temperatures of the year preceding ring formation were positively correlated with ring width. In contrast, trees at the southern extent of the Carpathians responded negatively to warm and dry conditions in autumn of the year preceding ring formation. An assessment of regional synchronization in radial growth variability showed temporal fluctuations throughout the 20th century linked to the onset of moisture limitation in southern landscapes. Since the beginning of the study period, differences between high and low elevations in the temperature sensitivity of tree growth generally declined, while moisture sensitivity increased at lower elevations. Growth trend analyses demonstrated changes in absolute tree growth rates linked to climatic change, with basal area increments in northern landscapes and lower altitudes responding positively to recent warming. Tree growth has predominantly increased with rising temperatures in the Carpathians, accompanied by early indicators that portions of the mountain range are transitioning from temperature to moisture limitation. Continued warming will alleviate large-scale temperature constraints on tree growth, giving increasing weight to local drivers that are more challenging to predict.

A millennium-long reconstruction of damaging hydrological events across Italy

Damaging hydrological events are extreme phenomena with potentially severe impacts on human societies. Here, we present the hitherto longest reconstruction of damaging hydrological events for Italy, and for the whole Mediterranean region, revealing 674 such events over the period 800–2017. For any given year, we established a severity index based on information in historical documentary records, facilitating the transformation of the data into a continuous time-series. Episodes of hydrological extremes disrupted ecosystems during the more severe events by changing landforms. The frequency and severity of damaging hydrological events across Italy were likely influenced by the mode of the Atlantic Multidecadal Variability (AMV), with relatively few events during the warm Medieval Climate Anomaly dominated by a positive phase of the AMV. More frequent and heavier storms prevailed during the cold Little Ice Age, dominated by a more negative phase of the AMV. Since the mid-19^th century, a decreasing occurrence of exceptional hydrological events is evident, especially during the most recent decades, but this decrease is not yet unprecedented in the context of the past twelve centuries.