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Accurate prediction of regional terrestrial water storage change (TWSA) is of great significance for water resources planning and management, and early warning of extreme climate disasters. Aiming at the problem that the conventional methods on prediction of TWSA time series are difficult to be accurate, the six typical regions are selected in China as examples, including the upper reaches of the Yangtze River (UYR), the southwest region (SWR), the Liaohe River Basin (LRB), the North China Plain (NCP), the Qinghai-Tibet Plateau (QTP), and the Pearl River Basin (PRB). The mascon product from GRACE/GRACE-FO provided by CSR is used to extract TWSA time series in six typical areas. The improved Back Propagation (BP) neural network, Long Short-Term Memory (LSTM) neural network and the latest Bidirectional LSTM (BiLSTM-attention) neural network model based on attention mechanism are proposed to predict and analyze the regional TWSA. In the experiment, the selection of the optimal model parameters such as the number of hidden layer nodes and the number of hidden units of the neural network model is tested and analyzed in detail. Meanwhile, the model prediction results are compared with the traditional least squares method and random forest (RF) prediction method. The root mean square error (RMSE), determination coefficient (R2), Nash–Sutcliffe efficiency coefficient (NSE) and mean absolute percentage error (MAPE) were used to evaluate the accuracy of the predicted results. The results show that the improved BP, LSTM and Bi-LSTM-attention neural network models all achieve higher prediction accuracy in UYR and SWR areas. RMSE is less than 2.641 cm, R2 is as high as 0.8 or more, NSE is above 0.6, and MAPE is within 0.1. Compared with the least square method, the RMSE of the predicted results from three neural network decreased by 0.998 cm, 0.700 cm and 0.7563 on average, and the R2 increased by 81.75%, 69.89% and 72% on average. Compared with RFML method, the RMSE from three neural network is reduced by 0.601 cm, 0.316 cm and 0.360, and R2 is increased by 38.20%, 24.60% and 27.06% on average. NSE and RMSE are improved to varying degrees in the above regions. It shows that the improved BP, LSTM and BiLSTM-attention model used can effectively predict TWSA. The research methods and results in this paper can provide important reference for the rational utilization of regional water resources and disaster risk assessment. [ABSTRACT FROM AUTHOR]

This paper introduces and summarises the main outcomes of the 19th workshop of the International Association for Phytoplankton Taxonomy and Ecology held in Tiszafüred, Hungary, Tisza Balneum Hotel, from 23 to 30 September 2022. The selected theme of the workshop was "Trait-Based Approaches in Micro-Algal Ecology". The discussions presented during the workshop sessions resulted in the 18 articles contained in this Special Issue. There are 6 main thematic aspects developed by the participants: 1. Shape and size: are these traits easy to measure? 2. Spatial scales: when and where to look for microalgae? 3. Climate and extremes of ecological gradients: hot topics of this century. 4. Metaphyton and metaphytic habitats: life beyond plankton and benthos. 5. Microalgae in water management: phycology in practice. 6. Traditional and new methods: perspectives and comments. Trait-based approaches in microalgae ecology, although requiring further investigation and methodological development, represent a valid tool for refining the analysis of environmental variability in aquatic ecosystems. The papers presented in this Special Issue demonstrate that these approaches are extremely useful not only in the study of planktic algae but constitute a thoughtful method for the analysis of benthic and metaphytic microalgae in a wide variety of aquatic ecosystems. [ABSTRACT FROM AUTHOR]

The processes of overland flow, infiltration through an unsaturated zone (UZ) and groundwater flow discharge to a surface-water network are simulated by a synthetic flow and transport watershed model under a 30-year warming signal. A promising strategy is to use both methods as complementary to each other: machine learning techniques can improve the calibration of numerical models whereas process-based numerical models are suitable to understand the physical system and, on turn, select proper input variables for machine learning models. In general, the study highlights that choosing the modelling approach based on the specific aquifer features is fundamental to obtaining a modelling tool efficient in supporting groundwater management actions aimed at mitigation of the effects of climate change. [Extracted from the article]

This article discusses the importance of integrating water management into urban planning to mitigate flooding risks and build resilient cities. It presents a case study of the city of Duran in Ecuador, where a successful partnership model has been implemented to address disaster risk reduction and climate change impact. The study emphasizes the need for interdisciplinary work, community involvement, and the use of early warning systems to effectively respond to potential threats. The article acknowledges the gap between global agendas and their implementation at the local level, particularly in low- and middle-income countries. The authors propose a co-production model that involves a transdisciplinary team of experts from various fields to study the urban basin and understand the city's vulnerability to flooding. They collected data from different sources and developed detailed flood risk maps using technology and available data. The implementation of an early warning system for floods was completed in 2023 and proved invaluable during the El Niño/Southern Oscillation event in 2023-2024. The collaborative approach between the community and local authorities has been effective in responding to potential threats and protecting against future disasters. The authors emphasize the importance of interdisciplinary work, evidence-based policy recommendations, and digital transformation to empower communities and local authorities in building resilience. The collaboration between the government of Duran and ESPOL (a public university) resulted in a research paper that examined the vulnerability of Duran to floods and proposed policy recommendations for climate event prevention, response, and adaptation. The COVID-19 pandemic led to adjustments in the project, including the establishment [Extracted from the article]

While timber harvesting has plateaued, repeat-logging and conversion into plantations (especially oil palm) are still active in the tropics. The associated hydrological impacts especially pertaining to enhanced runoff, flood, and erosion have been well-studied, but little attention has been given to water resource availability in the humid tropics. In the light of the increasing climate extremes, this paper compared baseflow values and baseflow recession constants (K) between headwater catchments of five differing land-uses in Sabah, Malaysian Borneo, namely primary forest (PF), old growth/virgin jungle reserve (VJR), twice-logged forest with 22 years regeneration (LF2), multiple-logged forest with 8 years regeneration (LF3), and oil palm plantation (OP). Hydrological and meteorological sensors and dataloggers were established in each catchment. Daily discharge was used for computing K via four estimation methods. Catchment ranks in terms of decreasing K were VJR (0.97841), LF3 (0.96692), LF2 (0.90347), PF (0.83886), and OP (0.86756). Catchment ranks in terms of decreasing annual baseflow were PF (1877 mm), LF3 (1265 mm), LF2 (812 mm), VJR (753 mm), and OP (367 mm), corresponding to 68%, 55%, 51%, 42%, and 38% of annual streamflow, respectively. Despite the low K, PF had the highest baseflow magnitude. OP had the fastest baseflow recession and lowest baseflow magnitude. Baseflow persistence decreased with increasing degree of disturbance. K showed strong association to catchment stem density instead of basal area. For dynamic catchments in this study, the Kb3 estimator is recommended based on its lowest combination of coefficient of variation (CoV) and root mean squared error (RMSE) of prediction. For wetter catchments with even shorter recession events, the Kb4 estimator may be considered. Regarding climate change, logging and oil palm agriculture should only be conducted after considering water resource availability. Forests (even degraded ones) should be conserved as much as possible in the headwaters for sustainable water resource. [ABSTRACT FROM AUTHOR]

Quantitative and qualitative knowledge about the potential impacts of climate change on extreme hydrological events is crucial for water resource management and extreme risk management under climate change. This has theoretical and realistic implications to study and couple the climate system with hydrologic processes, to understand the system and solve related problems in water resources and extreme hydrology, such as decision making, plan management, environmental protection, and ecological balance. This paper reviews recent studies investigating climate change impact on hydrological extremes using a perspective of the integrated modeling framework comprising climate change scenarios, climate models, bias correction methods, hydrological modeling (model structure and parameterization), and reducible uncertainty arising from these sources characterized by a paucity of knowledge. The available research outcomes show the extreme high flows are likely to increase under climate change in the most parts of Europe, Asia, and the USA, but greatly vary and decrease in Africa and Latin America, which is highly variable and uncertain in space and time. Each component in integrated modeling has an important role in shifting and producing uncertainty in projected extreme flow. Among them, the climate model's discrepancy and hydrological models' structure are the more dominant source of uncertainty in projection of extreme high and low (or mean) flow in most of the regions, respectively. However, the quality of input data and hydrological model structures are the most dominant source of uncertainty in Africa, Latin America, and some parts of Asia. This indicated that these regions have strong hydrological cycle and higher physiographic heterogeneity. We believe that our existing knowledge and skills need to be improved and transformed into an accurate mathematical and physical representation, to minimize the uncertainty due to the effect of choices in the methodology chain. So, disentangling the aggregated uncertainty in the cascade modeling chain can be done by using variances, which can help understand the interaction effect and identify their contribution to the projected extreme flow. This comprehensive review can help modelers to identify and reduce uncertainty in projecting hydrological extremes and policy makers for full awareness of the various uncertainties to make a robust decision for water resources management under climate change. Article Highlights: This study provides a comprehensive review on reducing uncertainty in projecting hydrological extremes from the perspective of an integrated modeling framework Existing knowledge and skills need to be improved and transformed into an accurate mathematical representation The impact of climate change on hydrological extremes is highly variable and uncertain in space and time Uncertainties of the integrated modeling framework can be reduced by decomposing the aggregated uncertainty using variance analysis and/or the modeling chain [ABSTRACT FROM AUTHOR]

In this paper, we used a Bayesian model averaging (BMA) approach to analyse the changes in rainfall extremes in the periods 2041–2070 and 2071–2099 over northeast Bangladesh as a consequence of climate change. Climate change over this region could potentially impact agricultural production, water resources management, and the overall economy of the country. We used six regional climate models (RCMs) over the Coordinated Regional Downscaling Experiment South Asia domain. We used one medium stabilization scenario (RCP4.5) and one high‐emission scenario (RCP8.5) for projecting the extreme rainfall indices. A multi‐model ensemble mean was generated using the BMA approach. The BMA mean is a weighted average related to each RCM's predictive skill during the training period. Most of the rainfall extremes are expected to increase in both pre‐monsoon (March–May) and monsoon (June–September) seasons in the future compared with baseline (1976–2005). The average pre‐monsoon rainfall of the study area is projected to increase by 12.93 and 18.42% under RCP4.5 and 18.18 and 23.85% under RCP8.5 for the periods 2041–2070 and 2071–2099, respectively. The average monsoon rainfall of the study area is projected to increase by 4.96 and 2.27% under RCP4.5 and 6.56 and 6.40% under RCP8.5 for the periods 2041–2070 and 2071–2099, respectively. All the extreme indices except consecutive wet day are expected to change significantly at the 95% confidence level during the pre‐monsoon season. The study area will potentially be subjected to more frequent floods in the future both in pre‐monsoon and monsoon seasons as a consequence of climate change. Notably, the intensity and the magnitude of flash flooding in the pre‐monsoon season are expected to increase more in the future because the increase in extreme indices is more significant during that season. [ABSTRACT FROM AUTHOR]

Semi-arid farming systems in India are facing an increasing frequency of climate change-induced extreme weather events. With the aim of improving their climate resilience, we retrospectively assess climate resilience in two case studies in Maharashtra, India. We considered a 15-year period and multiple interventions in both. The systems showed improved climate resilience when agricultural productivity-enhancing interventions were combined with those related to water management, soil health, livelihood diversification, and food and nutrition security. Further, we recommend embedding a monitoring, evaluation and learning component within the design of all interventions to help with adaptive decision-making. [ABSTRACT FROM AUTHOR]

Climate change led an increase in the frequency of severe droughts, the effects of which are exacerbated by a lack of water storage. Despite increasing research on global-scale total water storage (TWS) change and drought prediction, basin-scale long-term hydrological drought, TWS change, and El Nino–Southern Oscillation (ENSO) influence in East Africa (EA) remain unexplored. In this paper, we used multiple approaches, of ensemble machine learning (ML) and weighted averaging, to conduct a basin-scale exploratory analysis of future hydrological drought and TWS change for the period 2025–2099. Climate change will affect future hydrological conditions in the basins, with maximum severity values of −90.3, −726.6, and −2567.7 Gt in the Tana, Turkana, and Victoria basins, respectively, under RCP6.0. Similarly, we found maximum severities of −187.5 and −277.7 Gt in the Abaya-Chamo and Tanganyika basins, respectively, under RCP 2.6. The most severe El Nino drought and exceptional La Nina conditions in the basins were found under both RCP scenarios. To ensure future water security in EA, sustainable water resource management strategies that can mitigate the impacts of extreme climate events in the future are urgently needed. [ABSTRACT FROM AUTHOR]

• Drought followed by extreme rain/flooding exposed vulnerabilities in Ceará, Brazil. • Adaptative strategies in dry periods may become maladaptive during extreme rain. • Impacts of and responses to drought, extreme rain, and flooding are interrelated. • Hydrometereological extremes should be considered together in semi-arid regions. As climates continue to change, semi-arid rainfall regimes are projected to become increasingly more extreme, with longer dry periods and fewer, but more intense, heavy rainfall events. This process of hydroclimatic intensification increases the risk associated with successive extreme climate hazards, such as drought and then heavy rainfall, in the same area. However, the development of effective adaptation strategies to drought, heavy rainfall, and flood hazards is hampered by the lack of integrated analyses that consider the interactions among these hazards and responses to them. To increase understanding of these interactions, this paper examines impacts of and adaptive actions taken in response to prolonged drought (2012–2018) and subsequent extreme rainfall and flooding (March and April 2023) in the semi-arid region of Ceará, Northeast Brazil. We find that policies and adaptive measures focus primarily on drought hazard, while preparation for extreme rainfall events and flooding is scant. Management plans and long-term adaptive strategies are being developed for drought and not other extreme hydrometeorological events. Additionally, emergency measures for extreme rainfall and flooding are much less structured than those for drought. As such, the paradigm "Convivência com o semiárido" ("Living with the semi-arid region") remains limited to adapting to drought hazard, ultimately hindering adequate extreme rainfall and drought responses. To promote more effective adaptive strategies in the context of hydroclimatic intensification in semi-arid regions, drought, heavy rainfall, and flood responses must be considered in a more integrated manner to create management plans to prepare for the potential impacts of these hazards into the future. [ABSTRACT FROM AUTHOR]

This study examined the impacts of climate change and human activities on runoff within the Feiling Hydrological Station watershed in the Qinhe River basin, utilizing the SWAT (Soil and Water Assessment Tool) model. Several climate change and extreme land-use scenarios were evaluated for their effects on runoff. Results demonstrated the SWAT model's suitability for runoff simulation in the watershed, revealing a negative correlation between runoff and temperature changes, and a positive correlation with precipitation changes. Significantly, runoff responses to precipitation variations of ±10% and ±20% were more marked than those to temperature changes of ±1 °C and ±2 °C. In scenarios of extreme woodland and fallow land, runoff decreased, whereas in scenarios of extreme cropland and grassland, it increased, particularly in the extreme farmland scenario. The study's findings are important for the sensible management of soil and water resources and the enhancement of the natural environment in the studied area. [ABSTRACT FROM AUTHOR]

The synchronicity of rain and heat in the summer of China's monsoon region provides sufficient water and heat resources for maize growth. However, the intra-annual distribution of precipitation and the probability of extreme precipitation have been inevitably altered by the ongoing climate change, thus affecting the matching degree between precipitation and crop water requirements (MDPCWR). Evaluating the extent to which the MDPCWR will change in the future is of great importance for food security and the sustainable management of water resources. In this study, considering that different growth stages of crops have different sensitivities to water stress, the AquaCrop model was used to calculate the MDPCWR more accurately. In addition, a cumulative distribution function-transform (CDF-t) method was used to remove the bias of 11 global climate models (GCMs) under two typical emission scenarios (SSP2-4.5 and SSP5-8.5) from phase six of the Coupled Model Intercomparison Project (CMIP6). A comprehensive investigation was conducted on how maize growth, water consumption, and the MDPCWR will respond to future climate change with CO2 concentration enrichment in the Huang–Huai–Hai (3H) region in China by driving a well-tested AquaCrop model with the bias-corrected GCMs outputs. The results indicate the following: (1) The CDF-t method can effectively remove seasonal bias, and it also performs well in eliminating the bias of extreme climate events. (2) Under the SSP2-4.5 scenario, the average maximum temperature will increase by 1.31 °C and 2.44 °C in 2021–2050 and 2051–2080, respectively. The average annual precipitation will increase up to 96.8 mm/year, but it will mainly occur in the form of heavy rain. (3) The increased maize evapotranspiration rate does not compensate for the decreased crop water requirement (up to −32 mm/year), due to a shorter growth cycle. (4) The farmland cultivation layer is not able to hold a significant amount of precipitation, due to the increased frequency of heavy rains, resulting in increased irrigation water requirements for maize over the next two periods, with the maximum value of 12 mm/year. (5) Under different scenarios, the projected future MDPCWR will decrease by 9.3–11.6% due to changes in precipitation patterns and crop water requirements, indicating that it will be more difficult for precipitation to meet the water demand of maize growing in the 3H region. The results can provide comprehensive information to understand the impact of climate change on the agricultural water balance and improve the regional strategy for water resource utilization in the 3H region. [ABSTRACT FROM AUTHOR]

Water resources management during drought is a significant challenge worldwide, particularly for upland areas. Additionally, variations in water availability are becoming more extreme with climate change. Nature Based Solutions (NBS) e.g. Runoff Attenuation Features (RAFs) could provide an alternative to hard-engineering. Using more natural processes, flow pathways are intercepted and attenuated in features during wet periods, increasing infiltration opportunity and thus water availability for use later. NBS research has primarily focused on flood mitigation, but little is known about low flow impacts; knowledge is required on where and at what scale to implement NBS. To explore these questions, we used a physically-based catchment model (MIKE SHE) integrated with a hydraulic river model (MIKE 11) to evaluate scenarios with varying RAF volumes and locations. We applied this to an intensively monitored upland Scottish catchment (0.9 km2) where 40 RAFs (∼2m3 storage each) were installed for low flow enhancement. Model results showed installed RAFs increase recharge (∼0.1%), groundwater contribution to streamflow (∼4%) and low flows (∼1%) and reduce high (∼5%) and mean flows (∼2%), suggesting RAFs could be used to mitigate extreme flows. The scenarios revealed that RAF location (primarily soil type) and scale (total storage volume and spread of features) were both important. Doubling installed RAF volumes increased impact on low flows by ∼25% and high flows by ∼40%, although lower additional benefits were predicted with further storage increases. RAFs had greater impact in freely-draining soils than poorly-draining, however distributing the same storage volume across many smaller RAFs over greater areas (both soil types) provided the largest effect. Absolute changes observed were relatively small, and given model uncertainty, should be treated with caution. Nevertheless, the direction of change was clear and given ecological systems and water supply rely on small margins of change, even slight increases in low flows will likely be beneficial. [ABSTRACT FROM AUTHOR]

• Impact and uncertainty framework for the identification of compound hydro-hazards. • UK example application using EDgE RCP8.5 projections. • NE Scotland and SW UK identified as spatio-temporally compound hotspot regions. • Hydrological models identified as the largest source of variability. • Raises questions regarding spatial variability of hydroclimatological modelling uncertainty. There exists an increasing need to understand the impact of climate change on the hydrological extremes of flood and drought, collectively referred to as 'hydro-hazards'. At present, current methodology are limited in their scope, particularly with respect to inadequate representation of the uncertainty in the hydroclimatological modelling chain. This paper proposes spatially consistent comprehensive impact and uncertainty methodological framework for the identification of compound hydro-hazard hotspots – hotspots of change where concurrent increase in mean annual flood and drought events is projected. We apply a quasi-ergodic analysis of variance (QE-ANOVA) framework, to detail both the magnitude and the sources of uncertainty in the modelling chain for the mean projected mean change signal whilst accounting for non-stationarity. The framework is designed for application across a wide geographical range and is thus readily transferable. We illustrate the ability of the framework through application to 239 UK catchments based on hydroclimatological projections from the EDgE project (5 CMI5-GCMs and 3 HMs, forced under RCP8.5). The results indicate that half of the projected hotspots are temporally concurrent or temporally successive within the year, exacerbating potential impacts on society. The north-east of Scotland and south-west of the UK were identified as spatio-temporally compound hotspot regions and are of particular concern. This intensification of the hydrologic dynamic (timing and seasonality of hydro-hazards) over a limited time frame represents a major challenge for future water management. Hydrological models were identified as the largest source of variability, in some instances exceeding 80% of the total variance. Critically, clear spatial variability in the sources of modelling uncertainty was also observed; highlighting the need to apply a spatially consistent methodology, such as that presented. This application raises important questions regarding the spatial variability of hydroclimatological modelling uncertainty. In terms of water management planning, such findings allow for more focussed studies with a view to improving the projections which inform the adaptation process. [ABSTRACT FROM AUTHOR]

Abstract For many years, scientists have tried to understand, describe and quantify water and sediment fluxes, with associated substances like pollutants, at multiple scales. In the past two decades, a new concept called connectivity has been used by Earth Scientists as a means to describe and quantify the influences on the fluxes of water and sediment on different scales: aggregate, pedon, location on the slope, slope, watershed, and basin. A better understanding of connectivity can enhance our comprehension of landscape processes and provide a basis for the development of better measurement and modelling approaches, further leading to a better potential for implementing this concept as a management tool. This paper provides a short review of the State-of-the-Art of the connectivity concept, from which we conclude that scientists have been struggling to find a way to quantify connectivity so far. We adapt the knowledge of connectivity to better understand and quantify water and sediment transfers in catchment systems. First, we introduce a new approach to the concept of connectivity to study water and sediment transfers and the associated substances. In this approach water and sediment dynamics are divided in two parts: the system consists of phases and fluxes, each being separately measurable. This approach enables us to: i) better conceptualize our understanding of system dynamics at different timescales, including long timescales; ii) identify the main parameters driving system dynamics, and devise monitoring strategies which capture them; and, iii) build models with a holistic approach to simulate system dynamics without excessive complexity. Secondly, we discuss the role of system boundaries in designing measurement schemes and models. Natural systems have boundaries within which sediment connectivity varies between phases; in (semi-)arid regions these boundaries can be far apart in time due to extreme events. External disturbances (eg. climate change, changed land management) can change these boundaries. It is therefore important to consider the system state as a whole, including its boundaries and internal dynamics, when designing and implementing comprehensive monitoring and modelling approaches. Connectivity is a useful tool concept for scientists that must be expanded to stakeholder and policymakers. Graphical abstract Unlabelled Image Highlights • We introduce a conceptual framework for modelling and measuring water and sediment fluxes. • System phases and fluxes are differentiated to enable quantification of connectivity. • The mutual benefits of combining modelling and measuring to understand connectivity is shown. • Necessary data for measuring and/or modelling water and sediment transfer is identified. [ABSTRACT FROM AUTHOR]

Climate change is adversely affecting coffee production, impacting both yields and quality. Coffee production is dominated by the cultivation of Arabica and Robusta coffee, species that represent 99% of production, but both will be affected by climate change. Sustainable management practices that can enhance the resilience of production and livelihoods to climate change are urgently needed as production supports the livelihoods of over 25 million people globally, the majority of whom are smallholder farmers located in the coffee belt spanning the tropics. These communities are already experiencing the impacts of climate change. We conducted a systematic review, identifying 80 studies that describe the direct and indirect impacts of climate change on coffee agroecosystems, or that identify agroecological practices with the potential to enhance climate resilience. Adverse environmental impacts include a reduction in area suitable for production, lower yields, increased intensity and frequency of extreme climate events, and greater incidence of pests and diseases. Potential environmental solutions include altitudinal shifts, new, resilient cultivars, altering agrochemical inputs, and agroforestry. However, financial, environmental and technical constraints limit the availability of many of these approaches to farmers, particularly smallholder producers. There is therefore an urgent need to address these barriers through policy and market mechanisms, and stakeholder engagement to continue meeting the growing demand for coffee. [ABSTRACT FROM AUTHOR]

Germany's increasing temperatures and droughts are significantly impacting the hydrological realm. This study examines the implications of climate change on future droughts in a representative catchment within Germany's low mountain range. Findings of this research shed light on potential impacts on future seasonal water availability, aiding decision makers and stakeholders in managing regional climate change risks. Climate and drought indices, as well as the climatic water balance, are computed and analyzed until 2100, relative to a reference period. A high emission scenario (RCP8.5) and a climate protection scenario (RCP2.6) are considered to address uncertainties. Results reveal above-average warming in the study area compared to the national average. Under the RCP8.5 scenario, the far future exhibits an average of 44 annual heat days. Despite wetter winters, extended droughts persist. Water stress intensifies in summer and autumn, with a projected 68% increase in dry period duration. The findings emphasize the necessity of adaptation strategies, as even ambitious global warming mitigation efforts require regional adaptation. The study represents the first application of a Germany-wide, bias-adjusted, and regionalized dataset at catchment level. It contributes novel insights for regional water resources management and advances understanding of climate change impacts in German low mountain range regions. [ABSTRACT FROM AUTHOR]

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The objective of this study was to investigate rainfall trends in chosen climatic stations in Syria. Syria is prone to extreme climate events such as drought and flood. Annual as well as seasonal rainfall trends were detected by Mann-Kendall statistical test. The Sen's slope was applied to identify the magnitude of those trends. The results achieved for rainfall revealed more frequent significant decreasing trends. Achieved results can be the basis for the development of water resources management plans and within the framework of risk assessment they will address all aspects of risk management focusing on prevention, protection, preparedness (including forecasts and early warning systems) and taking into account the characteristics of specific area. The Intergovernmental Panel on Climate Change's (IPCC) Fifth Assessment Report concluded that precipitation has generally increased over latitudes north of 30 over the period of 1900-2005 and decrease in the Mediterranean and southern Asia. In the presented paper, we evaluate out coincidence with the IPCC report - decreasing rainfall in Syria. [ABSTRACT FROM AUTHOR]

The Mediterranean Basin has been identified as a climate change "hotspot", a region where increased warming and drying are expected to occur at rates faster than the global average. Increasing scientific attention has therefore been drawn to the repercussions of climate change for the Mediterranean's diverse and valued agricultural sector. The extent to which these repercussions vary throughout the region, owing both to a non-uniform distribution of climatic hazards and to uneven adaptive capacities of farmers, remains however unquantified. We hereby provide a comprehensive spatial assessment of the potential to implement different farm-based land and water management adaptations across the Mediterranean's croplands, and evaluate the extent to which different regions see a match or a mismatch between areas of adaptation need and areas of adaptation capacity. This approach made use of spatial multi-criteria analysis to evaluate the suitability of different farm adaptations, and relied on the Ecocrop climate suitability model and climate data on changing duration or frequency of extremes to identify areas of adaptation need under a high-end climate change scenario. The adaptations explored in this work span a range of sustainable approaches addressing different components of the farming system (soil-based, water-based, and crop-based adaptations). For each sub-system, we compared the potential to implement an adaptation representing an incremental change vs. one involving greater transformation. Results indicate a worsening of climatic conditions for all croplands in the region, and particularly within the Mediterranean extents of Egypt, Turkey, Greece, Spain, Morocco, Bosnia and Herzegovina, and Israel. In more than half of these countries, >60% of highly affected Mediterranean areas, on average, see no tangible potential to implement adaptations. Importantly, potentials for adaptation, and particularly of transformational adaptations having the greatest hypothesized capacity to buffer against the effects of climate change, are found to be lower within areas where the most adverse climate change hazards are forecast to occur. For regions found to be approaching so-called limits to adaptation, this research contributes to growing calls for consideration of more transformational options, alongside the opportunities and sacrifices these options entail. For regions where considerable (yet unrealized) adaptation capacity is found to match areas of adaptation need, this paper instead presents a basis for further investigation on how to bridge adaptation capacity and preparedness. [Display omitted] • Mediterranean croplands will witness increased drought and heat stress under RCP 8.5. • Croplands in the south-west and east will face the greatest increases in climatic extremes. • Most regions have a > 50% spatial mismatch between adaptation potential and needs. • Adaptation potential is lower where most needed, especially for transformational adaptations. • Greater reflection on transformation needed as limits to adaptation are approached. [ABSTRACT FROM AUTHOR]

The present study intends to assess the climatic controls on the streamflow and its impacts on the changing form of hydrological extremes in the Jhelum basin. The study entails robust statistical analysis of the observed hydroclimatic data (1980–2016) using the standard procedures of trend and abrupt change point detection, flood frequency analysis (FFA), and streamflow drought index (SDI). The coupled impact of rising temperatures (0.024 °C/year) and diminishing precipitation (− 5.71 mm/year) is yielding substantial decreases in the streamflow of the Jhelum basin. The other manifestations of changing climatic regimes are the increasing trends in the spring season (March-May) streamflow and the concurrence of abrupt change points in the streamflow data with climatic variables. The climate change signals are well evident over the hydrological extremes, reflected in an enhanced occurrence of droughts through the latter half of the examined period. Moreover, the flood frequency estimates show that the magnitude of the peak discharges about different return periods has increased significantly during 1986–2016 compared to 1956–1985 estimates. The magnitude of 100-year recurrence interval flood has increased by 10.54–79.58% during 1986–2016. The current study calls for the inclusive restructuring of water management practices to offset the impacts of changing hydrological extremes in the basin. [ABSTRACT FROM AUTHOR]

Extreme precipitation events have caused serious impacts on natural ecosystem and human society and have attracted increasing attention in recent years. IPCC AR6 WG I report highlighted a lack of conclusive consensus on the change trend of extreme precipitation in some basins and variation (increase or decrease) between regions. Based on seven precipitation indexes defined by ETCCDI, using daily precipitation data observed by 18 national reference meteorological stations in China during 1959–2018, this study analysed spatiotemporal variation trend of extreme precipitation in the Beijiang River Basin, Southern Coastal China, in recent 60 years, using Mann–Kendall (M-K) trend test, coefficient of variation, and continuous wavelet transformation. M-K test results showed that there were mutations in all seven precipitation indexes, and mutation points were mainly concentrated in two periods (1986–1991 and 2005–2010). The change range of each index after mutation was generally greater than that before mutation. Continuous wavelet transformation showed that each indicator had a significant oscillation period of 2–4 year in most time domains. The southeastern part of the basin (Fogang and Qingyuan) was the center of extremely heavy precipitation, and most precipitation indexes decreased from this area to the surrounding area. As far as the basin as a whole was concerned, consecutive wet days (CWD) declined significantly (passing 0.05 of confidence test), and there was a significantly positive correlation between annual distribution of R95ds and monthly precipitation (p < 0.001). The research results expand our understanding of regional water cycle and extreme climate change, guide the allocation and management of water resources related to regional industrial and agricultural activities, and provide reference for disaster prevention and mitigation. [ABSTRACT FROM AUTHOR]

Since the beginning of this century, Europe has been experiencing severe drought events (2003, 2007, 2010, 2018 and 2019) which have had adverse impacts on various sectors, such as agriculture, forestry, water management, health and ecosystems. During the last few decades, projections of the impact of climate change on hydroclimatic extremes have often been used for quantification of changes in the characteristics of these extremes. Recently, the research interest has been extended to include reconstructions of hydroclimatic conditions to provide historical context for present and future extremes. While there are available reconstructions of temperature, precipitation, drought indicators, or the 20th century runoff for Europe, multi-century annual runoff reconstructions are still lacking. In this study, we have used reconstructed precipitation and temperature data, Palmer Drought Severity Index and available observed runoff across 14 European catchments in order to develop annual runoff reconstructions for the period 1500–2000 using two data-driven and one conceptual lumped hydrological model. The comparison to observed runoff data has shown a good match between the reconstructed and observed runoff and their characteristics, particularly deficit volumes. On the other hand, the validation of input precipitation fields revealed an underestimation of the variance across most of Europe, which is propagated into the reconstructed runoff series. The reconstructed runoff is available via Figshare, an open-source scientific data repository, under the DOI 10.6084/m9.figshare.15178107,. [ABSTRACT FROM AUTHOR]

A better understanding of climate change impacts on water security beyond climate variability is of critical importance to tackle water vulnerabilities exacerbated by increasing extreme weather events. Thus, studies on water security in a changing climate help decision-makers to overcome existing political and socioeconomic challenges worldwide. In this study, future water security of two basins was assessed under climate change and demand scenarios by contrasting water demand with probabilistic levels of water availability to identify possible drivers of insecurity. The Guariroba and Jaguari basins are the main sources for supplying water to Campo Grande city and the São Paulo Metropolitan Region, respectively. The physically-based SWAT+ model was calibrated to simulate the basins' hydrological response to three climate change scenarios from a CMIP6 multimodel ensemble: SSP2-4.5 (medium forcing), SSP3-7.0 (high forcing), and SSP5-8.5 (high forcing). The Guariroba basin already presented scarcity indices close to the security threshold in the baseline period. The imbalance between availability and demand was the main driver of water insecurity in this basin. Despite showing a low scarcity risk in the Jaguari basin in the baseline, this risk considerably increased in the future periods due to a decrease in precipitation. A reduction in water demand of 20% by 2070 was not sufficient to improve water security in both basins. These findings indicate that a lack of policies for adapting demand to a changing availability exacerbates hydrological droughts. More stringent measures to balance water availability and demand are critical for improving water security in an uncertain future. [ABSTRACT FROM AUTHOR]

The study reported high summer-autumn and winter runoff changes for the Amur River under RCP 6.0 in the future case, as well as a significant increase in anomalies of the spring and winter runoff of the Lena under RCP 6.0 by the end of the 21st century. Due to the influences of climate changes and human activities, extreme climate events have made obvious changes to the hydrological process and the temporal-spatial distribution of water resources over the past several decades. 10.3390/w14081306 6 Tang Y., Huo J., Zhu D., Yuan Z. Simulation of the Water Storage Capacity of Siling Co Lake on the Tibetan Plateau and Its Hydrological Response to Climate Change. [Extracted from the article]

The present study aims to assess the recent changes and trends in the extreme climate indices in the Kashmir basin using the observational records from 1980 to 2016. The extreme climate indices were computed using the ClimPACT2 software and a total of 39 indices were selected for the analysis having particular utility to various sectors like agriculture, water resources, energy consumption, and human health. Besides adopting the station scale analysis, regional averages were computed for each index. In terms of the mean climatology, an increase has been observed in the annual mean temperature with a magnitude of 0.024 °C/year. Further, differential warming patterns have been observed in the mean maximum and minimum temperatures with mean maximum temperature revealing higher increases than mean minimum temperature. On the other hand, the annual precipitation shows a decrease over most of the region, and the decreases are more pronouncing in the higher altitudes. The trend analysis of the extreme indices reveals that in consonance with the rising temperature there has been an increase in the warm temperatures and decrease in the cold temperatures across the Kashmir basin. Furthermore, our analysis suggests a decrease in the extreme precipitation events. The drought indices viz., Standardised Precipitation Index (SPI), and Standardised Precipitation Evapotranspiration Index (SPEI) manifest decreasing trends with the tendency towards drier regimes implying the need for better water resource management in the region under changing climate. [ABSTRACT FROM AUTHOR]

This study was undertaken in Laikipia County, Kenya, to identify factors influencing the choices of strategies by pastoralists to adapt to climate change. The study particularly evaluates the role of perceived climate extremes (frequency of dry spells and droughts), early warning information, and access to private ranch grazing, in determining response decisions to climate change. Besides, we test if households jointly adopt climate change adaptation strategies. The primary data collected from 440 sample households was analyzed using the multivariate probit (MVP) model. In the MVP model, we consider the following measures: increased mobility (distance & frequency), storage/purchase of fodder, change in water management, partial shift to other livelihoods, and herd management. The results reveal that these adaptation strategies are jointly adopted by pastoralists as complements and substitutes. From the empirical result, the perceived increase in the number of dry spells and drought, access to early warning information, access to private ranch grazing, main market distance from homesteads, and the highest level of education in the household are the key determinants of the choices of adaptation strategies to cope with drought and climate change. From a policy perspective, this research contributes to the ongoing debate on best practices by addressing climate change-related challenges in semi-arid land management. Therefore, there is a need for early warning institutions to increase their visibility in the semi-arid areas by exploring effective methods of delivering climate risk information in good time. Improving access to market and private ranch grazing should be promoted in the Kenyan semi-arid areas. Given that pastoralists' perceptions of climate change and climate risk is a decisive variable in adaptation decision-making, there is need to improve the understanding of pastoralists' changing climatic conditions. Furthermore, since the results indicate that mobility and storage of fodder are substitutes, the adoption of hay production could become a key production strategy for pastoralists which will increase the competitiveness of their livestock in the market and increase milk production. [ABSTRACT FROM AUTHOR]

• Future change in extreme droughts over 5797 North American watersheds was studied. • Two climate model large ensembles were used to assess the change of frequency. • Changes in meteorological droughts are mostly correlated to mean precipitation. • Large increases in the frequency of hydrological droughts are observed over NA. • Projected changes in future extreme droughts get worse for longer return periods. This paper describes projected frequency changes in extreme summer meteorological and hydrological droughts over North American catchments. It uses two large ensemble climate models (50-member CanESM2 and 40-member CESM1) under the RCP 8.5 scenario to robustly assess frequency changes up to the 100-year drought, relative to the 1980–2009 reference period. Meteorological droughts, linked solely to precipitation deficit, are represented by the 1-month Standardized Precipitation Index (SPI), whereas hydrological droughts are characterized by the 1-month Streamflow Drought Index (SDI), based on hydrological simulation using a lumped hydrological model. Results show widely different patterns for future changes in extreme meteorological versus hydrological droughts. Future meteorological droughts show patterns of increasing and decreasing frequency that roughly match future expected changes of mean summer precipitation, although some regions are nonetheless projected to see more frequent extreme meteorological droughts despite increases in mean summer precipitation. The frequency changes for the 100-year meteorological droughts can be quite severe, with up to a 20-fold increase observed over some watersheds. On the other hand, hydrological droughts, which combine the effect of precipitation and temperature changes, show a mostly uniform pattern of large to very large increases in drought frequency. This shows that the projected temperature increase is a main driver of future extreme hydrological droughts, enough to overcome the projected increase in mean summer precipitation for many North American catchments. Projected changes in both meteorological and hydrological droughts get consistently worse for the longer considered return periods. In other words, frequency changes for the 100-year droughts are more significant than those expected for the 2- and 20-year droughts. This gradual worsening toward larger extremes has potentially large societal and economic impacts. The large projected increases in the frequency of extreme hydrological drought frequency (up to 27 times) are likely to severely stress water management systems across North America. [ABSTRACT FROM AUTHOR]

The 17 Sustainable Development Goals (SDGs) underpinned by 169 targets presents national governments with huge challenges for implementation. We developed a proposal for a National Blueprint Framework (NBF) with 24 water-related indicators, centered on SDG 6 (clean water and sanitation for all), each with a specific target. We applied the NBF to 28 EU Member States (EU-28) and conclude that: The current SDG 6 indicators are useful for monitoring progress toward water-related targets but their usefulness can be improved by focusing more on their practical implementation. The extension of SDG 6 with complementary indicators (e.g. for the circular economy of water) and quantitative policy targets is urgently needed. This will benefit the communication process and progress at the science-policy interface. SDG indicators can be improved in a SMART (specific, measurable, achievable, relevant, and time-bound) manner and by setting clear policy targets for each indicator, allowing for measuring distance-to-targets. This allows country-to-country comparison and learning, and accelerates the SDG implementation process. We propose 24 water-related indicators centered on SDG 6, with complementary indicators including quantitative policy targets. The approach is doable, easily scalable, and flexibly deployable by collecting information for the EU-28. Main gaps in the EU-28 are observed for water quality, wastewater treatment, nutrient, and energy recovery, as well as climate adaptation to extreme weather events (heat, droughts, and floods). The framework was less successful for non-OECD countries due to lack of data and EU-centric targets for each indicator. This needs further research. [ABSTRACT FROM AUTHOR]

The Truckee/Carson Basin, like other semiarid basins in the western United States, faces challenges to water management and planning under a changing climate. We analyzed tree‐ring data, along with instrumental climatic and hydrologic records, to provide a perspective on extreme drought in the 21st century. Drought indices highlighted a recent increase in the average duration of hydroclimatic episodes: in the new millennium average duration was 74% longer for the 24‐month Standardized Precipitation Index (SPI‐24) and 62% longer for the Palmer Drought Severity Index (PDSI) than in the previous century. Average snow water equivalent (SWE) declined 7% per decade from 1965 to 2018. The 2012‐2015 drought, in particular, stood out for its intensity and expression in snowpack, streamflow, and drought indices. Likely because of recent warming, this 4‐year drought event had a very low likelihood based on observed Carson River flows from the first half of the 20th century. A 501‐year tree‐ring reconstruction (1500‐2000 CE) of average water‐year streamflow for the Carson River indicated that positive (wet) spells had slightly longer duration (mean of 2.7 years and range from 1 to 10 years) than negative (dry) intervals (mean of 2.4 years and range from 1 to 9 years). The early 1900s pluvial, that is, 1905‐1911 in this record, was the third strongest episode in the entire reconstruction. The driest years were 1580 and 1934, both well‐known widespread and severe droughts in the western United States. Noise‐added reconstructions suggest that 2012‐2015, while not unique in the 401 years prior to the start of the Carson River gaged flows in 1901, was a less than one‐in‐a‐century event. Key Points: Increasing drought duration on the Carson River has characterized the transition from the first to the second millenniumTree‐ring chronologies show that the 2012‐2015 drought on the Carson River is a less than one‐in‐a‐century eventRecent warming has exacerbated the hydrologic impact of 21st century precipitation droughts on the Carson River [ABSTRACT FROM AUTHOR]

Using household survey data and historical daily climate data for 29 communities across Upper East Ghana and Southwest Burkina Faso, we document climatic conditions deemed major threat to farming in the West African Sudan Savanna and assess risks posed by such conditions over the period 1997-2014. Based on farmers' perception, it is found that drought, low rainfall, intense precipitation, flooding, erratic rainfall pattern, extremely high temperatures, delayed rains, and early cessation of rains are the major threats farmers face. Using first-order Markov chain model and relevant indices for monitoring weather extremes, it is discovered that climatic risk is a general inherent attribute of the rainy season in the study area. Due to recent changes in onset of rains and length of the rainy season, some farmers have either resorted to early planting of drought-hardy crops, late planting of drought-sensitive crops, or spreading of planting across the first 3 months of the season to moderate harm. Each of these planting decisions however has some risk implications. The months of May, June, and October are found to be more susceptible to relatively longer duration of dry and hot spells, while July, August, and September are found to be more susceptible to intense precipitation and flooding. To moderate harm from anticipated weather extremes, farmers need to adjust their cropping calendar, adopt appropriate crop varieties, and implement soil and water management practices. For policy makers and other stakeholders, we recommend the supply of timely and accurate weather forecasts to guide farmers in their seasonal cropping decisions and investment in/installation of low cost irrigation facilities to enhance the practice of supplemental irrigation. [ABSTRACT FROM AUTHOR]

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Increases in climate extremes and their impacts have attracted global attention recently. In this study, the change-point years of precipitation extremes (PEs) and drought extremes (DEs) were investigated by Moving t-Test at 500 stations across the six regions in China. The detailed temporal change processes of them were demonstrated by the cumulative deviation method based on the data from nine typical stations. The results showed that: 1) DEs were more significantly and widely increased than PEs, the stations with increasing trends of PEs and DEs accounted for greater than 52.6% and 61.6% of the total, respectively; 2) increasing trends of DEs were mainly distributed in the east of Hu Huanyong Line. In this area, the increasing change-point years of DEs often occurred in the early 1980s in the south of the Yangzi River, while occurred in the 1990s in the north of the Yangzi River; 3) increasing trends of PEs were mainly distributed in Qing-Tibet Platen, Northwest China, and the southeastern area of Hu Huanyong Line. In these areas, the increasing change-point years of PEs often occurred around 1990 in the southeast of Hu Huanyong Line, while often occurred in the early 1980s in Qing-Tibet Platen. The results indicated that the area in the southeast of Hu Huanyong Line was under the threats of both PEs and DEs, this may produce severe impacts on agriculture, environment, water resources management, human society, etc. [ABSTRACT FROM AUTHOR]