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Effective management of groundwater resources during drought is essential. How is groundwater currently managed during droughts, and in the face of environmental change, what should be the future priorities? Four themes are explored, from the perspective of groundwater management in England (UK): (1) integration of drought definitions; (2) enhanced fundamental monitoring; (3) integrated modelling of groundwater in the water cycle; and (4) better information sharing. Whilst these themes are considered in the context of England, globally, they are relevant wherever groundwater is affected by drought.

An understanding of multi-annual behaviour in streamflow allows for better estimation of the risks associated with hydrological extremes. This can enable improved preparedness for streamflow-dependant services, such as freshwater ecology, drinking water supply and agriculture. Recently, efforts have focused on detecting relationships between long-term hydrological behaviour and oscillatory climate systems (such as the North Atlantic Oscillation – NAO). For instance, the approximate 7 year periodicity of the NAO has been detected in groundwater-level records in the North Atlantic region, providing potential improvements to the preparedness for future water resource extremes due to their repetitive, periodic nature. However, the extent to which these 7-year, NAO-like signals are propagated to streamflow, and the catchment processes that modulate this propagation, are currently unknown. Here, we show statistically significant evidence that these 7-year periodicities are present in streamflow (and associated catchment rainfall), by applying multi-resolution analysis to a large data set of streamflow and associated catchment rainfall across the UK. Our results provide new evidence for spatial patterns of NAO periodicities in UK rainfall, with areas of greatest NAO signal found in southwest England, south Wales, Northern Ireland and central Scotland, and show that NAO-like periodicities account for a greater proportion of streamflow variability in these areas. Furthermore, we find that catchments with greater subsurface pathway contribution, as characterised by the baseflow index (BFI), generally show increased NAO-like signal strength and that subsurface response times (as characterised by groundwater response time – GRT), of between 4 and 8 years, show a greater signal presence. Our results provide a foundation of understanding for the screening and use of streamflow teleconnections for improving the practice and policy of long-term streamflow resource management.

Currently, land use and land cover change (LULCC) is of utmost concern for global environmental change and sustainability. Among the portfolio of techniques, modelling is considered as the best approach to explore LULC dynamics. We have performed a model inter-comparison exercise (including hybrid and non-hybrid models) using multiple performance metrics to identify the best modelling approach for the subsequent projection of future LULC. The methodology is demonstrated on the Subarnarekha basin of Eastern India by utilizing the LANDSAT imagery of 1989, 1994, 2006, and 2011. Before LULC modelling, the cross-tabulation and trend-surface analyses were performed to identify dominant land transitions in post-classification maps. Temporal mapping results over 1989–2011 exhibited a drastic decrease in the area under dense forest (25.7% to 19.0%), a substantial increase in the area under scrubland (21.0% to 26.1%) and a nominal reduction in the coverage of the agricultural land (51.2% to 49.0%). Four integrated models namely Multilayer perceptron-Markov Model (MLP-MC), Logistic Regression-Markov Model (LR-MC), and two hybrid models, i.e. Multilayer perceptron-Cellular automata-Markov model (MLP-CA-MC) and Logistic Regression-Cellular automata-Markov model (LR-CA-MC) were tested for their suitability for predicting future LULC for the basin. Based on the multiple model validation techniques, the MLP-MC model performed the best. MLP-MC model subsequently used a non-stationary relationship between selected explanatory variables and LULC to predict the future LULC for 2020 and 2030. The MLP-MC model projected that relative to the level of 2011, agricultural land, dense forest, and barren land may decrease by 8.3, 28.2 and 23.5%, respectively, and scrubland, built-up area, and water bodies may increase by 22.5, 87.3 and 13.3%, respectively, by 2030. Our findings contradict the prevalent view regarding the nationwide intensification of agriculture over the Indian subcontinent but are consistent with the national decreasing trend in the dense forest. The study provides a transferable methodology for the systematic comparison of LULC models (including hybrid and non-hybrid) against multiple performance metrics. The outcomes of the study may help land-use planners, environmentalist, and policymakers in framing better policies and management .recommendations.

Erosion and the impacts of the redistribution of sediment are a serious threat to the quality of water resources. They cause losses and/or additional expenses in many areas, such as water treatment, biodiversity or fisheries. The implementation of catchment management measures, aimed at preventing the transfer of sediment to rivers, can be a cost-beneficial way to address the problem. In order to select the measures and appropriate locations for erosion control, the spatially distributed soil erosion and sediment delivery model WaTEM-SEDEM was used. The model was calibrated against total suspended solids data at the outlet of the Wey catchment, South-east England, yielding satisfactory results. Different scenarios of catchment management were modelled to reduce the amount of sediment transported to the river. Scenarios introducing 24 retention ponds, 50-m-wide buffer strips and cover crops in areas with the largest erosion and sediment delivery were tested. The largest decrease in both sediment production and sediment export was obtained using cover crops, with reductions of 13.4% and 14.1%, respectively. A cost-benefit analysis considering multiple ecosystem services (e.g. control of erosion rates, attenuation of mass flow, pest control, wildlife and its outputs) identified the cover crops as the most cost-beneficial measure and a possible funding scheme based on payments for ecosystem services was developed as a way to enable its implementation.

Due to it having the lowest priority for water allocation during drought events and the consequent agronomic and economic impacts of abstraction restrictions, UK irrigated agriculture has been identified as a key business sector ‘at risk’. An enhanced version of the D-Risk webtool has been developed to help agricultural stakeholders and catchment water managers to evaluate the joint multi-scale risks of abstraction restrictions (voluntary and mandatory) and having insufficient irrigation volumes during drought events. The webtool uses annual maximum potential soil moisture deficit as the agroclimate index to calculate monthly and annual volumetric irrigation demand for the selected crop mix, soil available water capacity and location. Simulated river flows are used to identify days not under abstraction restrictions. Annual probability distributions of irrigation deficit and licence utilisation (headroom) are derived from a monthly time-step water balance model that calculates whether the farm irrigation demand in each month can be met, taking account of river flow-based abstraction restrictions, daily and annual volumetric licensed abstraction limits, the licenced abstraction period(s) and any on-farm reservoir storage. The enhanced D-Risk tool provides a more holistic understanding of drought risk on irrigated agriculture from individual farm to catchment scales and supports improved collaborative decision-making regarding future water sharing, water trading and on-farm reservoir investment to reduce business vulnerability to drought and regulatory change.

Drought forecasting and early warning systems for water resource extremes are increasingly important tools in water resource management, particularly in Europe where increased population density and climate change are expected to place greater pressures on water supply. In this context, the North Atlantic Oscillation (NAO) ais often used to indicate future water resource behaviours (including droughts) over Europe, given its dominant control on winter rainfall totals in the North Atlantic region. Recent hydroclimate research has focused on the role of multiannual periodicities in the NAO in driving low frequency behaviours in some water resources, suggesting that notable improvements to lead-times in forecasting may be possible by incorporating these multiannual relationships. However, the importance of multiannual NAO periodicities for driving water resource behaviour, and the feasibility of this relationship for indicating future droughts, has yet to be assessed in the context of known non-stationarities that are internal to the NAO and its influence on European meteorological processes. Here we quantify the time-frequency relationship between the NAO and a large dataset of water resources records to identify key non-stationarities that have dominated multiannual behaviour of water resource extremes over recent decades. The most dominant of these is a 7.5-year periodicity in water resource extremes since approximately 1970 but which has been diminishing since 2005. Furthermore, we show that the non-stationary relationship between the NAO and European rainfall is clearly expressed at multiannual periodicities in the water resource records assessed. These multiannual behaviours are found to have modulated historical water resource anomalies to an extent that is comparable to the projected effects of a worst-case climate change scenario. Furthermore, there is limited systematic understanding in existing atmospheric research for non-stationaries in these periodic behaviours which poses considerable implications to existing water resource forecasting and projection systems, as well as the use of these periodic behaviours as an indicator of future water resource drought.

This work was supported by the Global Challenges Research Fund through quality-related funding (QR GCRF) and the UK Natural Environment Research Council (Grant number NE/N015541/1). J. Krishnaswamy acknowledges support from the Climate Change and Disaster Risk Mitigation component of the National Mission on Biodiversity and Human Well-being supported by the Office of the Principal Scientific Adviser to the Government of India and Google Research (Google Grant for AI on Social Good). In India’s Indo-Gangetic plains, river flows are strongly altered by dams, barrages and water diversions for irrigation, urban supply, hydropower production and flood control. Human demands for freshwater are likely to intensify with climatic and socio-economic changes, exacerbating trade-offs between different sustainable development goals (SDGs) dependent on freshwater (e.g. SDG2, SDG6, SDG7, SDG11 and SDG15). Freshwater ecosystems and endangered aquatic species are not explicitly addressed in the SDGs, but only nested as targets within SDG6 and SDG15. Thus, there is high risk that decisions to advance other SDGs may overlook impacts on them. In this study, we link a water resource systems model and a forecast extinction risk model to analyze how alternative conservation strategies in the regulated Beas River (India) affect the likelihood of survival of the only remaining population of endangered Indus River Dolphins (IRD) in India in the face of climate change-induced impacts on river hydrology and human water demands, explicitly accounting for potential trade-offs between related SDGs. We find that the frequency of low flow released from the main reservoir may increase under some climate change scenarios, significantly affecting the IRD population. The strongest trade-offs exist between the persistence of IRD, urban water supply and hydropower generation. The establishment of ecologically informed reservoir releases combined with IRD population supplementation enhances the probability of survival of the IRD and is compatible with improving the status of relevant SDGs. This will require water managers, conservation scientists, and other stakeholders to continue collaborating to develop holistic water management strategies. Publisher PDF

Assessing the combined impacts of future climate and socio-economic change at the country level is vital for supporting national adaptation policies. Here, we use a novel modelling approach to study the systemic impacts of climate and socio-economic changes on the Czech Republic, taking account of cross-sectoral interactions between agriculture, water, forestry, land-use and biodiversity, and, for the first time, trans-national interactions. We evaluate the national-level baseline results, scenario-neutral model sensitivities, and climate and socio-economic scenario impacts using a European-scale integrated modelling tool. Consistently across most climate and socio-economic scenarios, the Czech Republic is projected to have increasing importance as a crop-growing region in Europe, due to an increased competitive advantage within the continent. Arable land in the Czech Republic expands, at the expense of livestock farming and forestry, with associated impacts of increased water scarcity and reduced biodiversity for the country. Accounting for trans-national interactions in national-scale assessments provides more realistic assessments of impacts and helps to identify the changing role of the country within its regional and continental domain. Such improved understanding can support policy-makers in developing national adaptation actions that reduce adverse impacts and realise opportunities.

Holistic water management approaches are essential under future climate and socio-economic changes, especially while trying to achieve inter-disciplinary societal goals such as the Sustainable Development Goals (SDGs) of clean water, hunger eradication, clean energy and life on land. Assessing water resources within a water-food-energy-environment nexus approach enables the relationships between water-related sectors to be untangled while incorporating impacts of societal changes. We use a systems modelling approach to explore global change impacts on the nexus in the mid-21st century in a complexwestern Himalayanwater resource system in India, considering a range of climate change and alternative socio-economic development scenarios. Results show that future socio-economic changes will have a much stronger impact on the nexus compared to climate change. Hydropower generation and environmental protection represent the major opportunities and limitations for adaptation in the studied system and should, thereby, be the focus for actions and systemic transformations in pursue of the SDGs. The emergence of scenario-specific synergies and trade-offs between nexus component indicators demonstrates the benefits that water resource systems models canmake to designing better responses to the complex nexus challenges associated with future global change. (c) 2018 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license

Achieving the Paris Agreement’s aim of limiting average global temperature increases to 1.5 °C requires substantial changes in the land system. However, individual countries’ plans to accomplish these changes remain vague, almost certainly insufficient and unlikely to be implemented in full. These shortcomings are partially the result of avoidable ‘blind spots’ relating to time lags inherent in the implementation of land-based mitigation strategies. Key blind spots include inconsistencies between different land-system policies, spatial and temporal lags in land-system change, and detrimental consequences of some mitigation options. We suggest that improved recognition of these processes is necessary to identify achievable mitigation actions, avoiding excessively optimistic assumptions and consequent policy failures. The Paris Agreement requires substantial changes in the land system. However, national implementation plans are vague, largely insufficient and unlikely to be fully achieved. Realistic policies require proper consideration of land-system lags.

Satellite Remote Sensing, with both optical and SAR instruments, can provide distributed observations of snow cover over extended and inaccessible areas. Both instruments are complementary, but there have been limited attempts at combining their measurements. We describe a novel approach to produce monthly maps of dry and wet snow areas through application of data fusion techniques to MODIS fractional snow cover and Sentinel-1 wet snow mask, facilitated by Google Earth Engine. The method is demonstrated in a 55,000 km2 river basin in the Indian Himalayan region over a period of ∼2.5 years, although it can be applied to any areas of the world where Sentinel-1 data are routinely available. The typical underestimation of wet snow area by SAR is corrected using a digital elevation model to estimate the average melting altitude. We also present an empirical model to derive the fractional cover of wet snow from Sentinel-1. Finally, we demonstrate that Sentinel-1 effectively complements MODIS as it highlights a snowmelt phase which occurs with a decrease in snow depth but no/little decrease in snowpack area. Further developments are now needed to incorporate these high resolution observations of snow areas as inputs to hydrological models for better runoff analysis and improved management of water resources and flood risk.

Scenarios have been recognised as a useful tool for planning, which have resulted in a strong increase in the number of (multi-scale) scenarios in climate change research. This paper addresses the need for methodological progress and testing of conceptual considerations, by extending the global shared socio-economic pathways (SSPs). We present a set of four European SSPs until 2100 and a novel method to develop qualitative stories for Europe equivalent to the global SSPs starting from an existing set of European scenarios. Similar to the global SSPs, the set includes a sustainable future with global cooperation and less intensive lifestyles (We are the World; Eur-SSP1); a future in which countries struggle to maintain living standards in a high-carbon intensive Europe (Icarus; Eur-SSP3); a world in which power becomes concentrated in a small elite and where Europe becomes an important player (Riders on the Storm; Eur-SSP4); and one where a lack of environmental concern leads to the over-exploitation of fossil fuel resources addressed by technological solutions (Fossil-fuelled Development; Eur-SSP5). We conclude that the global SSPs are a good starting point for developing equivalent continental scale scenarios that, in turn, can serve multiple purposes. There are, however, methodological challenges related to the choice for equivalence and the exact methods by which scenarios are constructed that need to be tested further.

The Himalayan region has a large hydropower potential due to the natural topographic gradient and abundance of water resource from rainfall, snow and glacier melt. However, future water availability in the Himalayan streams is likely to be altered due to climatic conditions, which necessitates an assessment of hydropower investments, especially for small run-of-the-river projects. Here, we study the future glacio-hydrological changes in a small catchment located in the Upper Beas basin, in Western Himalaya in India, and their impacts on the operation of two small hydropower projects with contrasting hydrological requirements. The Water Evaluation and Planning (WEAP) model is used to integrate and analyse changes in cryosphere, hydrology and hydropower production in the middle and end of the 21st century using multiple climate models representing different types of future scenarios under RCP 4.5 and 8.5. In response to projected climate, the snow and glacier melt contribution to annual discharge declines from 34% in the baseline to 16.5% (RCP4.5) and 13.8% (RCP8.5) by the end of the century. The total streamflow shows broad uncertainty in magnitude and direction of change but shows a noticeable seasonal shift in the hydrological cycle. Of the two hydropower projects, the plant that utilizes high flows with low hydraulic head shows a behaviour similar to streamflow projections resulting in 13% (RCP45) and 19.7% (RCP85) increase in annual power generation by the end of the century arising from the increased hydropower potential of low flows and the rise in precipitation. The second power project that relies on lesser flows with high head maintains its designed power production consistently throughout the century in all the climate change scenarios. The differing sensitivity of the power projects to climate change is influenced by future changes in the runoff as well as by their design. Thus, this study provides insights into the climate-adaptive development and planning of small hydropower projects in the Himalayan region.

Study Region Allain catchment, a sub-basin of Beas basin, Western Himalaya. Study Focus This study aims to assess future glacio-hydrological changes in a small basin and their impacts on the operation of two Small Hydropower Projects (SHP) with contrasting hydrological requirements. The Water Evaluation and Planning (WEAP) model is used to integrate cryosphere, hydrology and hydropower production modelling in the 21st century using climate changes projected by the ensembles of five global climate models under RCP 4.5 and 8.5. New Hydrological Insights for the Region The total streamflow in the future is projected to have widespread uncertainty in the magnitude but shows noticeable changes in the seasonality. Of the two SHPs, the one utilizing high flows with low hydraulic head shows a power generation behaviour similar to streamflow projections. Its annual hydropower production is projected to change by 2 to 21% (RCP4.5) and -5 to 40% (RCP8.5) by the end of the century. The other plant that uses lesser flows but high head maintains its designed power production consistently throughout the century. The study indicates that the design of hydropower plants strongly influences their sensitivity to future climate and thus provides important insights into the climate-adaptive designs and planning of future hydropower projects in Himalaya.

Water resource forecasting generally centres on understanding hydrological variability over coming months or years, so that water managers can prepare for extremes such as droughts or floods (Chang & Guo, 2020; Hao et al., 2018). Some forecasting systems seek to project further into the future to allow long‐term planning of infrastructure and resilience to extremes and climate change (Svensson et al., 2015). These systems can rely directly or indirectly on outputs from Global Climate Models (GCMs; such as gridded reanalysis datasets) to forecast hydrological conditions (Bhatt & Mall, 2015; Ionita & Nagavciuc, 2020). In the North Atlantic region, in particular Western Europe, the North Atlantic Oscillation (NAO) is used as an indicator for hydrometeorological conditions given its leading control on winter rainfall totals (Hurrell & Deser, 2010; Scaife et al., 2008, 2014). A dipole of pressure anomalies over the North Atlantic, the NAO's positive phase (greater than average pressure gradient; NAO+) results in wetter conditions in northwest Europe with dryer conditions in southwest Europe (Rust et al., 2018; Trigo et al., 2004). Its negative phase (weaker than average pressure gradient; NAO−) results in the inverse effect on rainfall (Folland et al., 2015; and as shown by the correlation coefficients in Figure 1). Given this relationship, and, considering the role of winter rainfall variability in groundwater drought development (e.g., reduced winter recharge) and generation of late winter/early spring floods, the NAO offers a potential explanatory variable when understanding the behaviour of some hydrological extremes. image

Droughts can exert significant pressure on regional water resources resulting in abstraction constraints for irrigated agriculture with consequences for productivity and revenue. While water trading can support more efficient water allocation, high transactional costs and delays in approvals often restrict its wider uptake among users. Collaborative water sharing is an alternative approach to formal water trading that has received much less regulatory and industry attention. This study assessed how the potential benefits of water sharing to reduce water resources risks in agriculture are affected by both drought severity and the spatial scale of water-sharing agreements. The research focused on an intensively farmed lowland catchment in Eastern England, a known hot-spot for irrigation intensity and recurrent abstraction pressures. The benefits of water sharing were modelled at four spatial scales: (i) individual licence (with no water sharing), (ii) tributary water sharing among small farmer groups (iii) sub-catchment and (iv) catchment scale. The benefits of water sharing were evaluated based on the modelled reductions in the probability of an irrigation deficit occurring (reducing drought risks) and reduced licensed ‘headroom’ (spare capacity redeployed for more equitable allocation). The potential benefits of water sharing were found to increase with scale, but its impact was limited at high levels of drought severity due to regulatory drought management controls. The broader implications for water sharing to mitigate drought impacts, the barriers to wider uptake and the environmental consequences are discussed.

Droughts affect a range of economically important sectors but their impacts are usually most evident within agriculture. Agricultural impacts are not confined to arid and semi-arid regions, but are increasingly experienced in more temperate and humid regions. A transferable drought management framework is needed to transition from coping to adapting to drought through supporting improved planning and policy decision-making through the supply chain from primary producers to consumers. A combination methodology using a Driver-Pressure-State-Impact-Response (DPSIR) approach, an analysis of weekly agricultural trade publications and semi-structured interviews were used to explore drought impacts and responses, using the 2018 United Kingdom drought as a case study. While most reported responses were on-farm, a diverse range of measures were implemented across institutional scales and through the supply chain, reflecting complex interactions within the food system. However, drought responses were dominated by reactive and crisis-driven actions to cope with, or enhance the recovery from, drought; but which contributed little to increased resilience to future droughts. Our transferable drought management framework shows how improved collaboration and multi-sector engagement across spatial, governance and supply-chain scales to develop human and social capital can enable the transition from coping (short-term and reactive) to adapting (long-term and anticipatory) strategies to increase agricultural resilience to future droughts.

There are many sources of uncertainty in scenarios and models of socio-ecological systems, and understanding these uncertainties is critical in supporting informed decision-making about the management of natural resources. Here, we review uncertainty across the steps needed to create socio-ecological scenarios, from narrative storylines to the representation of human and biological processes in models and the estimation of scenario and model parameters. We find that socio-ecological scenarios and models would benefit from moving away from “stylized” approaches that do not consider a wide range of direct drivers and their dependency on indirect drivers. Indeed, a greater focus on the social phenomena is fundamental in understanding the functioning of nature on a human-dominated planet. There is no panacea for dealing with uncertainty, but several approaches to evaluating uncertainty are still not routinely applied in scenario modeling, and this is becoming increasingly unacceptable. However, it is important to avoid uncertainties becoming an excuse for inaction in decision-making when facing environmental challenges.

As the pressure to take action against global warming is growing in urgency, scenarios that incorporate multiple social, economic and environmental drivers become increasingly critical to support governments and other stakeholders in planning climate change mitigation or adaptation actions. This has led to the recent explosion of future scenario analyses at multiple scales, further accelerated since the development of the Intergovernmental Panel on Climate Change (IPCC) research community Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs). While RCPs have been widely applied to climate models to produce climate scenarios at multiple scales for investigating climate change impacts, adaptation and vulnerabilities (CCIAV), SSPs are only recently being scaled for different geographical and sectoral applications. This is seen in the UK where significant investment has produced the RCP-based UK Climate Projections (UKCP18), but no equivalent UK version of the SSPs exists. We address this need by developing a set of multi-driver qualitative and quantitative UK-SSPs, following a state-of-the-art scenario methodology that integrates national stakeholder knowledge on locally-relevant drivers and indicators with higher level information from European and global SSPs. This was achieved through an intensive participatory process that facilitated the combination of bottom-up and top-down approaches to develop a set of UK-specific SSPs that are locally comprehensive, yet consistent with the global and European SSPs. The resulting scenarios balance the importance of consistency and legitimacy, demonstrating that divergence is not necessarily the result of inconsistency, nor comes as a choice to contextualise narratives at the appropriate scale.

In many countries, including the UK, water resources are under intense stress with recent droughts highlighting the risks to the security of supplies for different sectors including domestic water supply, industry, agriculture (including horticulture), power generation and the environment. A changing climate with greater rainfall uncertainty, coupled with new regulations, increasing competition for water and demands for sustainable development will only exacerbate the current situation, with major supply-demand imbalances expected over the next few decades. In the UK, irrigated agriculture constitutes a volumetrically small but economically high value use of water, to maximise crop yields and quality. However, the importance of irrigation is also changing; driven by the intensification and transformation of the agricultural sector, the need to recognise water as an ‘essential’ use, policy incentives to increase domestic food production and an industry imperative to increase water use efficiency 1 and ensure agricultural expansion can continue to underpin the rural economy. This review considers the key climate and water-related risks facing the agricultural and horticultural crop sectors, the various environmental, regulatory and business externalities or ‘drivers for change’, and the strategic priorities for action, both from industry and research perspectives.

Future climate change will likely impact the multiple freshwater ecosystem services (fES) provided by catchments through their landscapes and river systems. However, there is high spatio-temporal uncertainty on those impacts linked to climate change uncertainty and the natural and anthropogenic interdependencies of water management systems. This study identifies current and future spatial patterns of fES production in a highly managed water resource system in northern India to inform the design and assessment of plausible adaptation measures to enhance fES production in the catchment under uncertain climate change. A water resource systems modelling approach is used to evaluate fES across the full range of plausible future scenarios, to identify the (worst-case) climate change scenarios triggering the greatest impacts and assess the capacity of adaptation to enhance fES. Results indicate that the current and future states of the fES depend on the spatial patterns of climate change and the impacts of infrastructure management on river flows. Natural zones deliver more regulating and cultural services than anthropized areas, although they are more climate-sensitive. The implementation of a plausible adaptation strategy only manages to slightly enhance fES in the system with respect to no adaptation. These results demonstrate that water resource systems models are powerful tools to capture complex system dependencies and inform the design of robust catchment management measures. They also highlight that mitigation and more ambitious adaptation strategies are needed to offset climate change impacts in highly climate-sensitive catchments.

Land use models operating at regional to global scales are almost exclusively based on the single paradigm of economic optimisation. Models based on different paradigms are known to produce very different results, but these are not always equivalent or attributable to particular assumptions. In this study, we compare two pan-European land use models that are based on the same integrated modelling framework and utilise the same climatic and socio-economic scenarios, but which adopt fundamentally different model paradigms. One of these is a constrained optimising economic-equilibrium model and the other is a stochastic agent-based model. We run both models for a range of scenario combinations and compare their projections of spatial and aggregate land use change and ecosystem service supply. We find that the agent-based model projects more multifunctional and heterogeneous landscapes in most scenarios, providing a wider range of ecosystem services at landscape scales, as agents make individual, time-dependent decisions that reflect economic and non-economic motivations. This tendency also results in food shortages under certain scenario conditions. The optimisation model, in contrast, maintains food supply through intensification of agricultural production in the most profitable areas, sometimes at the expense of active management in large, contiguous parts of Europe. We relate the principal differences observed to underlying model assumptions, and hypothesise that optimisation may be appropriate in scenarios that allow for coherent political and economic control of land systems, but not in scenarios where economic and other scenario conditions prevent the normal functioning of price signals and responses. In these circumstances, agent-based modelling allows explicit consideration of behavioural processes, but in doing so provides a highly flexible account of land system development that is harder to link to underlying assumptions. We suggest that structured comparisons of parallel, transparent but paradigmatically distinct models are an important method for better understanding the potential scope and uncertainties of future land use change.

Water is a fundamental component in primary food production, whether it be rainfall, irrigation used to water crops, or for supplying drinking water for animals, while the amount of water in the soil determines it capacity to support machinery and animals. We identify that UK agriculture is exposed to five main water-related risks: agricultural drought, scarcity of water resources, restrictions on the right to abstract water, excess soil water, and inundation. Projected milder, wetter winters and hotter, drier summers by the end of the century will change the frequency, persistence, or severity of each of these risks. This paper critically reviews and synthesizes the scientific literature on the impact of these risks on primary food production and the technological and managerial strategies employed to build resilience to these changing risks. At the farm scale, the emphasis has been on strategies to build robustness to reduce the impact of a water-related risk. However, collaborative partnerships allow for a more optimal allocation of water during times of scarcity. Enhancing cross-scale interactions, learning opportunities, and catchment-scale autonomy will be key to ensuring the agricultural system can build adaptive and transformational capacity.

An understanding of multi-annual behaviour in streamflow allows for better estimation of the risks associated with hydrological extremes. This is can enable improved preparedness for streamflow-dependant services such as freshwater ecology, drinking water supply and agriculture. Recently, efforts have focused on detecting relationships between long-term hydrological behaviour and oscillatory climate systems (such as the NAO). For instance, the approximate 7-year periodicity of the NAO has been detected in groundwater level records in the North Atlantic region, providing a degree of forecasting for future water resource extremes due to their repeating, periodic nature. However, the extent to which these 7-year NAO-like signals are propagated to streamflow, and the catchment processes that modulate this propagation, are currently unknown. Here, we show statistically significant evidence that these 7-year periodicities are present in streamflow (and associated catchment rainfall), by applying multi-resolution analysis to a large dataset of streamflow and associated catchment rainfall across the UK. Our results provide new evidence for spatial patterns of NAO periodicities in UK rainfall with areas of greatest NAO signal found in south west England, South Wales, Northern Ireland and central Scotland, and that NAO-like periodicities account for a greater proportion of streamflow variability in these areas. Furthermore, we show that subsurface pathway contribution, as characterised by the Baseflow Index (BFI), and the response times of subsurface pathways, as characterised by Groundwater response Time (GRT), are influential factors for streamflow sensitivity to these NAO-like cycles. Our results provide critical process understanding for the screening and use of streamflow teleconnections for the improving the practice and policy of long-term streamflow resource management.

In this chapter, we present how climate action that fosters transformations to sustainability and resilience in European societies can be developed in the context of high-end climate change. The chapter builds from the IMPRESSIONS inter- and transdisciplinary research project work on high-end climate change. It brings a unique perspective on long-term horizons (until 2100) and extreme climate change and socio-economic scenarios and uncertainties, as well as how to co-develop transformative adaptation and mitigation pathways with stakeholders to build capacities for responding to such scenarios. The chapter responds to the very fundamental question: ‘what is high-end climate change and why it is relevant for science and policy?’

Transition management has been applied in different governance contexts over the past 15 years, showing its modularity and also its ability to facilitate participatory strategic planning and agenda setting. This book chapter presents the operational framework of transition management as developed to guide the design of a three-series workshop in four case studies in Europe. What is unique in this contribution is a well-developed operational framework to explain how every phase and every step of transition management can be applied and tailored to climate change discussions and agenda setting. Another unique point is the introduction of climate scenarios as the context for developing transition pathways and acknowledging deep uncertainty in future actions. For each step, we elaborate on the lessons learnt and provide suggestions for future development and applications from the realisation of the transition management workshops in all four case studies.

This chapter introduces the robust transition pathways developed in four case studies at different scales in Europe and analyses what capacities they create. Implementing transition pathways to respond to high-end scenarios and contribute to sustainability and resilience transformations requires new agency capacities that are able to deal with complexity, uncertainty, thresholds and lock-ins. We identified key conditions that may enable an overall shift towards an integrated, multi-scale, inclusive and learning-based governance approach. The capacities are enacted by a large diversity of actors—combining a mix of governance models and instruments, including decisive top-down regulation, market-based self-regulation and sustainability accounting, and bottom-up and community-based decision-making, markets and resource management. The agency capacities show ways forward for supporting systemic solutions and innovations with multiple benefits, and how to build social resilience and adaptive institutions.

Glaciers and snowpacks influence streamflow by altering the volume and timing of discharge. Without reliable data on baseline snow and ice volumes, properties and behaviour, initializing hydrological models for climate impact assessment is challenging. Two contrasting HySIM model builds were calibrated and validated against observed discharge data (2000–2008) assuming that snowmelt of the baseline permanent snowpack reserves in the high-elevation sub-catchment are either constrained (snowmelt is limited to the seasonal snow accumulation) or unconstrained (snowmelt is only energy-limited). We then applied both models within a scenario-neutral framework to develop impact response surface of hydrological response to future changes in annual temperature and precipitation. Both models had similar baseline model performance (NSE of 0.69–0.70 in calibration and 0.64–0.66 in validation), but the impact response surfaces differ in the magnitude and (for some combinations) direction of model response to climate change at low (Q10) and high (Q90) daily flows. The implications of historical data inadequacies in snowpack characterization for assessing the impacts of climate change and the associated timing of hydrological tipping points are discussed.

The need to provide accurate estimates of precipitation over catchments in the Hindu Kush, Karakoram, and Himalaya mountain ranges for hydrological and water resource systems assessments is widely recognized, as is identifying precipitation extremes for assessing hydro-meteorological hazards. Here, we investigate the ability of bias-corrected Weather Research and Forecasting model output at 5-km grid spacing to reproduce the spatiotemporal variability of precipitation for the Beas and Sutlej river basins in the Himalaya, measured by 44 stations spread over the period 1980 to 2012. For the Sutlej basin, we find that the raw (uncorrected) model output generally underestimated annual, monthly, and (particularly low-intensity) daily precipitation amounts. For the Beas basin, the model performance was better, although biases still existed. It is speculated that the cause of the dry bias over the Sutlej basin is a failure of the model to represent an early-morning maximum in precipitation during the monsoon period, which is related to excessive precipitation falling upwind. However, applying a nonlinear bias-correction method to the model output resulted in much better results, which were superior to precipitation estimates from reanalysis and two gridded datasets. These findings highlight the difficulty in using current gridded datasets as input for hydrological modeling in Himalayan catchments, suggesting that bias-corrected high-resolution regional climate model output is in fact necessary. Moreover, precipitation extremes over the Beas and Sutlej basins were considerably underrepresented in the gridded datasets, suggesting that bias-corrected regional climate model output is also necessary for hydro-meteorological risk assessments in Himalayan catchments. © 2019. The Authors.

In a post-Paris Agreement world, where global warming has been limited to 1.5 or 2 °C, adaptation is still needed to address the impacts of climate change. To reinforce the links between such climate actions and sustainable development, adaptation responses should be aligned with goals of environmental conservation, economic development and societal wellbeing. This paper uses a multi-sectoral integrated modelling platform to evaluate the impacts of a + 1.5 °C world to the end of the 21st century under alternative Shared Socioeconomic Pathways (SSPs) for Europe. It evaluates the ability of adaptation strategies to concurrently improve a range of indicators, relating to sustainable development, under the constraints imposed by the contrasting SSPs. The spatial synergies and trade-offs between sustainable development indicators (SDIs) are also evaluated across Europe. We find that considerable impacts are present even under low-end climate change, affecting especially biodiversity. Even when the SDIs improve with adaptation, residual impacts of climate change affect all the SDIs, apart from sustainable production. All but one of the adaptation strategies have unintended consequences on one or multiple SDIs, although these differ substantially between strategies, regions and socio-economic scenarios. The exception was the strategy to increase social and human capital. Other strategies that lead to successful adaptation with limited unintended consequences are those aiming at adoption of sustainable behaviours and implementation of sustainable water management. This work stresses the continuing importance of adaptation even under 1.5 °C or 2 °C of global warming. Further, it demonstrates the need for policy-makers to develop holistic adaptation strategies that take account of the synergies and trade-offs between sectoral adaptation strategies, sectors and regions, and are also constrained by scenario context to avoid over-optimistic assessments.

In many temperate parts of the world, supplemental irrigation is crucial to assure both crop yield and quality. Climate change could increase the risks of irrigation being restricted by increasing crop water requirements and/or decreasing water availability. In England, water abstraction for irrigation is limited by maximum annual volumetric limits, as specified in the abstraction licences, and surface water abstraction restrictions imposed by the regulator during drought. This paper assesses how climate change might impact future irrigation abstraction reliability from surface water in England. Firstly, the probability of annual abstraction being close to the maximum licence limit was estimated for the baseline (1961–1990) and future (2071–2098) periods in each catchment based on observed relationships between annual weather and irrigation abstraction in three licence usage groups. Secondly, the current river discharge triggers for mandatory drought restrictions were used to assess the annual probability of surface water abstraction restrictions being imposed by the regulator in each period. Results indicate significant future increases in irrigated abstraction licence use due to an increase in aridity, particularly in the most productive agricultural areas located in eastern and southern England, assuming no adaptation. The annual probability of having less than 20% licence headroom in the highest usage group is projected to exceed 0.7 in 45% of the management units, mostly in the south and east. In contrast, irrigators in central and western England face an increased risk of drought restrictions due to the lower buffering capacity of groundwater on river flows, with the annual probability of mandatory drought restrictions reaching up to 0.3 in the future. Our results highlight the increasing abstraction reliability risks for irrigators due to climate change, and the need for the farming community and the regulator to adapt and collaborate to mitigate the associated impacts.

The Paris Agreement established the 1.5 and 2 °C targets based on the recognition “that this would significantly reduce the risks and impacts of climate change”. We tested this assertion by comparing impacts at the regional scale between low-end (< 2 °C; RCP2.6) and high-end (> 4 °C; RCP8.5) climate change scenarios accounting for interactions across six sectors (agriculture, forestry, biodiversity, water, coasts and urban) using an integrated assessment model. Results show that there are only minor differences in most impact indicators for the 2020s time slice, but impacts are considerably greater under high-end than low-end climate change in the 2050s and 2080s. For example, for the 2080s, mitigation consistent with the Paris Agreement would reduce aggregate Europe-wide impacts on the area of intensive agriculture by 21% (on average across climate models), on the area of managed forests by 34%, on water stress by 14%, on people flooded by 10% and on biodiversity vulnerability by 16%. Including socio-economic scenarios (SSPs 1, 3, 4, 5) results in considerably greater variation in the magnitude, range and direction of change of the majority of impact indicators than climate change alone. In particular, socio-economic factors much more strongly drive changes in land use and food production than changes in climate, sometimes overriding the differences due to low-end and high-end climate change. Such impacts pose significant challenges for adaptation and highlight the importance of searching for synergies between adaptation and mitigation and linking them to sustainable development goals.

The ability to predict future variability of groundwater resources in time and space is of critical importance to drought management. Periodic control on groundwater levels from oscillatory climatic systems (such as the North Atlantic Oscillation) offers a potentially valuable source of longer term forecasting capability. While some studies have found evidence of the influence of such climatic oscillations within groundwater records, there is little information on how periodic signals propagate between a climatic system and a groundwater resource. This paper develops a conceptual model of this relationship for groundwater resources in the UK and Europe, based on a review of current research. The studies reviewed here reveal key spatial and temporal signal modulations between climatic oscillations, precipitation, groundwater recharge and groundwater discharge. Generally positive correlations are found between the NAO (as a dominant influence) and precipitation in northern Europe indicating a strong control on water available for groundwater recharge. These periodic signals in precipitation are transformed by the unsaturated and saturated zones, such that signals are damped and lagged. This modulation has been identified to varying degrees, and is dependent on the shape, storage and transmissivity of an aquifer system. This goes part way towards explaining the differences in periodic signal strength found across many groundwater systems in current research. So that an understanding of these relationships can be used by water managers in building resilience to drought, several research gaps have been identified. Among these are improved quantification of spatial groundwater sensitivity to periodic control, and better identification of the hydrogeological controls on signal lagging and damping. Principally, research needs to move towards developing improved predictive capability for the use of periodic climate oscillations as indicators of longer term groundwater variability.

Predicting the next major drought is of paramount interest to water managers globally. Estimating the onset of groundwater drought is of particular importance, as groundwater resources are often assumed to be more resilient when surface water resources begin to fail. A potential source of long-term forecasting is offered by possible periodic controls on groundwater level via teleconnections with oscillatory ocean–atmosphere systems. However, relationships between large-scale climate systems and regional to local-scale rainfall, evapotranspiration (ET) and groundwater are often complex and non-linear so that the influence of long-term climate cycles on groundwater drought remains poorly understood. Furthermore, it is currently unknown whether the absolute contribution of multi-annual climate variability to total groundwater storage is significant. This study assesses the extent to which multi-annual variability in groundwater can be used to indicate the timing of groundwater droughts in the UK. Continuous wavelet transforms show how repeating teleconnection-driven 7-year and 16–32-year cycles in the majority of groundwater sites from all the UK's major aquifers can systematically control the recurrence of groundwater drought; and we provide evidence that these periodic modes are driven by teleconnections. Wavelet reconstructions demonstrate that multi-annual periodicities of the North Atlantic Oscillation, known to drive North Atlantic meteorology, comprise up to 40 % of the total groundwater storage variability. Furthermore, the majority of UK recorded droughts in recent history coincide with a minimum phase in the 7-year NAO-driven cycles in groundwater level, providing insight into drought occurrences on a multi-annual timescale. Long-range groundwater drought forecasts via climate teleconnections present transformational opportunities to drought prediction and its management across the North Atlantic region.

Scenarios are a useful tool to explore possible futures of social-ecological systems. The number of scenarios has increased dramatically over recent decades, with a large diversity in temporal and spatial scales, purposes, themes, development methods, and content. Scenario archetypes generically describe future developments and can be useful in meaningfully classifying scenarios, structuring and summarizing the overwhelming amount of information, and enabling scientific outputs to more effectively interface with decision-making frameworks. The Intergovernmental Platform for Biodiversity and Ecosystem Services (IPBES) faced this challenge and used scenario archetypes in its assessment of future interactions between nature and society. We describe the use of scenario archetypes in the IPBES Regional Assessment of Europe and Central Asia. Six scenario archetypes for the region are described in terms of their driver assumptions and impacts on nature (including biodiversity) and its contributions to people (including ecosystem services): Business-as-usual, economic optimism, regional competition, regional sustainability, global sustainable development, and inequality. The analysis shows that trade-offs between nature’s contributions to people are projected under different scenario archetypes. However, the means of resolving these trade-offs depend on differing political and societal value judgements within each scenario archetype. Scenarios that include proactive decision making on environmental issues, environmental management approaches that support multifunctionality, and mainstreaming environmental issues across sectors, are generally more successful in mitigating tradeoffs than isolated environmental policies. Furthermore, those scenario archetypes that focus on achieving a balanced supply of nature’s contributions to people and that incorporate a diversity of values are estimated to achieve more policy goals and targets, such as the UN Sustainable Development Goals and the Convention on Biological Diversity Aichi targets. The scenario archetypes approach is shown to be helpful in supporting science-policy dialogue for proactive decision making that anticipates change, mitigates undesirable trade-offs, and fosters societal transformation in pursuit of sustainable development, The authors are grateful to the IPBES Europe and Central Asia Expert Group and Technical Support Unit for all their input support, and collaboration over the past three years. Paula Harrison and Ian Holman acknowledge financial support from the UK Department of Environment, Food and Rural Affairs and the EUfunded IMPRESSIONS project (Grant Agreement 603416). Martin Schlaepfer received support from ENVIROSPACE, University of Geneva. Antoine Guisan acknowledges additional funding from the University of Lausanne to support Anthony Sonrel's contribution to the assessment

Global change is expected to have a strong impact in the Himalayan region. The climatic and orographic conditions result in unique modelling challenges and requirements. This paper critically appraises recent hydrological modelling applications in Himalayan river basins, focusing on their utility to analyse the impacts of future climate and socio-economic changes on water resource availability in the region. Results show that the latter are only represented by land use change. Distributed, process-based hydrological models coupled with temperature-index melt models are predominant. The choice of spatial discretisation is critical for model performance due to the strong influence of elevation on meteorological variables and snow/ice accumulation and melt. However, the sparsity and limited reliability of point weather data, and the biases and low resolution of gridded datasets, hinder the representation of the meteorological complexity. These data limitations often limit the selection of models and the quality of the outputs by forcing the exclusion of processes that are significant to the local hydrology. The absence of observations for water stores and fluxes other than river flows prevents multi-variable calibration and increases the risk of equifinality. The uncertainties arising from these limitations are amplified in climate change analyses and, thus, systematic assessment of uncertainty propagation is required. Based on these insights, transferable recommendations are made on directions for future data collection and model applications that may enhance realism within models and advance the ability of global change impact assessments to inform adaptation planning in this globally important region.

With a range of potential pathways to a sustainable future compatible with the Paris Agreement 1.5 °C target, scenario analysis has emerged as a key tool in studies of climate change mitigation and adaptation. A wide range of alternative scenarios have been created, and core amongst these are five socio-economic scenarios (Shared Socio-economic Pathways or SSPs) and four emission scenarios (Representative Concentration Pathways or RCPs). Whilst mitigation scenarios (the Shared Policy Assumptions, or SPAs) have been developed for each SSP-RCP combination, describing the actions necessary to match the climate pathway of the RCP, there has not yet been a systematic approach to address whether and how these actions can be enabled in practice. We present a novel and transferable framework to understand society’s capacity to achieve the 1.5 °C target, based on four participatory case studies using the SSP-RCP scenarios. The methodology builds on a framework for categorising different types of societal capitals and capacities and assessing their impact on the potential to implement different types of mitigation actions. All four case studies show that SSP1 has the highest potential to reach the target. Although environmental awareness is high in both SSP1 and SSP4, continued social inequalities in SSP4 restrict society’s capacity to transform, despite economic growth. In the two least environmentally-aware SSPs, SSP3 and SSP5, the transformation potential is low, but the view on capitals and capacities nonetheless helps identify opportunities for actors to develop and implement mitigation actions. The study highlights that techno-economic assessments of climate strategies need to be complemented by consideration of the critical role played by social and human capital, and by societal capacity to mobilise and create these capitals despite different socio-economic trends. These capitals and capacities are essential to enable the rapid innovation, behavioural change and international co-ordination needed to achieve the 1.5 °C target.

Climate change adaptation is a complex human process, framed by uncertainties and constraints, which is difficult to capture in existing assessment models. Attempts to improve model representations are hampered by a shortage of systematic descriptions of adaptation processes and their relevance to models. This paper reviews the scientific literature to investigate conceptualisations and models of climate change adaptation, and the ways in which representation of adaptation in models can be improved. The review shows that real-world adaptive responses can be differentiated along a number of dimensions including intent or purpose, timescale, spatial scale, beneficiaries and providers, type of action, and sector. However, models of climate change consequences for land use and water management currently provide poor coverage of these dimensions, instead modelling adaptation in an artificial and subjective manner. While different modelling approaches do capture distinct aspects of the adaptive process, they have done so in relative isolation, without producing improved unified representations. Furthermore, adaptation is often assumed to be objective, effective and consistent through time, with only a minority of models taking account of the human decisions underpinning the choice of adaptation measures (14%), the triggers that motivate actions (38%) or the time-lags and constraints that may limit their uptake and effectiveness (14%). No models included adaptation to take advantage of beneficial opportunities of climate change. Based on these insights, transferable recommendations are made on directions for future model development that may enhance realism within models, while also advancing our understanding of the processes and effectiveness of adaptation to a changing climate. Electronic supplementary material The online version of this article (10.1007/s10113-018-1328-4) contains supplementary material, which is available to authorized users.

Drought has wide ranging impacts on all sectors. Despite much effort to identify the best drought indicator to represents the occurrence of drought impacts in a particular sector, there is still no consensus among the scientific community on this. Using a more detailed and extensive impact dataset than in previous studies, this paper assesses the regional relationship between drought impacts occurrence in British agriculture and two of the most commonly used drought indices (SPI and SPEI). The largest qualitative dataset on reported drought impacts on British agriculture for the period 1975–2012 spanning all major recent droughts was collated. Logistic regression using generalised additive models was applied to investigate the association between drought indices and reported impacts at the regional level. Results show that SPEI calculated for the preceding six months is the best indicator to predict the probability of drought impacts on agriculture in the UK, although the variation in the response to SPEI6 differed between regions. However, this variation appears to result both from the method by which SPEI is derived, which means that similar values of the index equate to different soil moisture conditions in wet and dry regions, and from the variation in agriculture between regions. The study shows that SPEI alone has limited value as an indicator of agricultural droughts in heterogeneous areas and that such results cannot be usefully extrapolated between regions. However, given the drought sensitivity of agriculture, the integration of regional predictions within drought monitoring and forecasting would help to reduce the large on-farm economic damage of drought and increase the sector's resilience to future drought.

Drought frequency and intensity is expected to increase in many regions worldwide, and water shortages could become more extreme, even in humid temperate climates. To protect the environment and secure water supplies, water abstraction for irrigation can be mandatorily reduced by environmental regulators. Such abstraction restrictions can result in economic impacts on irrigated agriculture. This study provides a novel approach for the probabilistic risk assessment of potential future economic losses in irrigated agriculture arising from the interaction of climate change and regulatory drought management, with an application to England and Wales. Hydro-meteorological variability is considered within a synthetic dataset of daily rainfall and river flows for a baseline period (1977-2004), and for projections for near (2022-2049) and far (2072-2099) futures. The probability, magnitude and timing of abstraction restrictions are derived by applying rainfall and river flow triggers in 129 catchments. The risk of economic losses at the catchment level is then obtained from the occurrences of abstraction restrictions combined with spatially distributed crop-specific economic losses. Results show that restrictions will become more severe, frequent and longer in the future. The highest economic risks are projected where drought-sensitive crops with a high financial value are concentrated in catchments with increasingly uncertain water supply. This research highlights the significant economic losses associated with mandatory drought restrictions experienced by the agricultural sector and supports the need for environmental regulators and irrigators to collaboratively manage scarce water resources to balance environmental and economic considerations.

16 Pags.- 1 Tabl.- 1 Fig. The definitive version is available at: https://www.sciencedirect.com/science/journal/01681699. Supporting annual PSMDmax data referred to in this article can be accessed at https://doi.org/10.17862/cranfield.rd.6792260. The MaRIUS event set data are available on the Centre for Environmental Data Analysis (CEDA) platform (see https://doi.org/10.5285/0cea8d7aca57427fae92241348ae9b03)., Drought constitutes a significant production and business risk in agriculture, particularly for those enterprises dependent on irrigation to deliver high quality continuous supplies of fresh produce to the retail sector. Whilst most farmers are well attuned to managing short term weather-related crop risks, they lack access to tools that can support medium-term decision-making and risk management strategies under conditions of increasing water scarcity and climate uncertainty. This paper describes D-Risk, an intuitive online webtool designed to help farming enterprises easily understand their existing and emergent drought and irrigation abstraction risks and thereby support more robust decision-making regarding future changes in crop planning and water resources infrastructure investment., The authors acknowledge funding support from UK Research and Innovation (UKRI) Natural Environment Research Council (NERC) innovation grant (NE/N017471/1) and access to the MaRIUS event sets (developed in NERC grants NE/L010364/1, NE/L010208/1, NE/L010399/1, NE/L010186/1).

One of the consequences of the generally agreed rise of global temperatures, furtherly exacerbated by the growth of water demand caused by the needs of a growing population, is an increase of areas with water stress. This will imply and in part is already implying, an always greater imbalance between water (and in particular drinking water) demand and supply. These issues are among those investigated by the “Adapting Drinking Water resources to the Impacts of Climate change in Europe” (ADWICE) project that had, among its main goals, the identification of priority adaptation measures aimed at reducing drinking water vulnerability to the pressures of a changing climate. In this paper these adaptation measures are described, with special attention given to their associated European water policy context. The complexity of designing and implementing such adaptation measures will benefit from integrating drinking water concerns with wider water management, within a framework able to facilitate the necessary complex collaborations between various actors involved in the different scales of the decision-making arena and to develop an effective science policy interfacing mechanism. Last, but not least, because drinking water is commonly considered by stakeholders and citizens to be a public service, drinking water managers should enable their involvement in the adaptation decision-making process, to ensure their acceptance and cooperation and to prevent conflicts.

The complex challenges arising from climate change that exceeds the +2 °C target (termed ‘high-end climate change’) in Europe require new integrative responses to support transformations to a more sustainable future. We present a novel methodology that combines transition management and high-end climate and socioeconomic change scenarios to identify pathways and move Europe closer to sustainability. Eighteen pathways have been co-created with stakeholders through a participatory process. The pathways support Europe in moving towards a desirable future vision, through top-down and bottom-up actions that lower greenhouse gas emissions, reduce impacts of and vulnerabilities to climate and socioeconomic changes and enhance well-being. Analysis shows that the pathways that are robust to future scenario uncertainty are those that shift Europe towards sustainable lifestyles, support and strengthen good governance for sustainability and promote adaptive resource management for water, agriculture and energy. The methodology can support the design of the urgent actions needed to meet the requirements of the Paris Agreement and to transform Europe, in preparation for an uncertain future.

Uncertainties in our understanding of current and future climate change projections, impacts and vulnerabilities are structured by scientists using scenarios, which are generally in qualitative (narrative) and quantitative (numerical) forms. Although conceptually strong, qualitative and quantitative scenarios have limited complementarity due to the lack of a fundamental bridge between two different concepts of uncertainty: linguistic and epistemic. Epistemic uncertainty is represented by the range of scenarios and linguistic variables within them, while linguistic uncertainty is represented by the translation of those linguistic variables via the fuzzy set approach. Both are therefore incorporated in the models that utilise the final quantifications. The application of this method is demonstrated in a stakeholder-led development of socioeconomic scenarios. The socio-economic scenarios include several vague elements due to heterogeneous linguistic interpretations of future change on the part of stakeholders. We apply the so-called ‘Centre of Gravity’ (CoG) operator to defuzzify the quantifications of linguistic values provided by stakeholders. The results suggest that, in these cases, uniform distributions provide a close fit to the membership functions derived from ranges of values provided by stakeholders. As a result, the 90% or 95% intervals of the probability density functions are similar to the 0.1 or 0.05 degrees of membership of the linguistic values of linguistic variables. By bridging different uncertainty concepts (linguistic and epistemic uncertainties), this study offers a substantial step towards linking qualitative and quantitative scenarios.

Responses to future changes in climatic and socio-economic conditions can be expected to vary between sectors and regions, reflecting differential sensitivity to these highly uncertain factors. A sensitivity analysis was conducted using a suite of impact models (for health, agriculture, biodiversity, land use, floods and forestry) across Europe with respect to changes in key climate and socio-economic variables. Depending on the indicators, aggregated grid or indicative site results are reported for eight rectangular sub-regions that together span Europe from northern Finland to southern Spain and from western Ireland to the Baltic States and eastern Mediterranean, each plotted as scenario-neutral impact response surfaces (IRSs). These depict the modelled behaviour of an impact variable in response to changes in two key explanatory variables. To our knowledge, this is the first time the IRS approach has been applied to changes in socio-economic drivers and over such large regions. The British Isles region showed the smallest sensitivity to both temperature and precipitation, whereas Central Europe showed the strongest responses to temperature and Eastern Europe to precipitation. Across the regions, sensitivity to temperature was lowest for the two indicators of river discharge and highest for Norway spruce productivity. Sensitivity to precipitation was lowest for intensive agricultural land use, maize and potato yields and Scots pine productivity, and highest for Norway spruce productivity. Under future climate projections, North-eastern Europe showed increases in yields of all crops and productivity of all tree species, whereas Central and East Europe showed declines. River discharge indicators and forest productivity (except Holm oak) were projected to decline over southern European regions. Responses were more sensitive to socio-economic than to climate drivers for some impact indicators, as demonstrated for heat-related mortality, coastal flooding and land use. ISSN:1436-3798 ISSN:1436-378X