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The Water-Energy-Food (WEF) Nexus is high-dimensional and sensitive to control inputs, such as policy changes. Constructing Nexus models to predict policy impacts is time consuming, and the temporal resolution of the available data is often coarse, limiting the use of many data-driven methods. We investigated the applicability Dynamic Mode Decomposition with control (DMDc) as a method of performing policy impact predictions. A high-resolution System Dynamics Model (SDM) of the Nexus in Latvia was used to simulate the impacts of different policies on the Nexus at annual resolution between 2000 and 2050 (m = 50 snapshots). This simulated data was used to assess how well DMDc could reconstruct policy impacts based on data alone. To obtain numerically stable DMDc models with just 50 snapshots, linear interpolation was used to artificially inflate the data to monthly resolution (m = 600). Three policies based on the SDM were tested for two different data sizes,small (n = 15 variables) and large (n = 100). With 5–15 control-policy variables specified, DMDc was able to reconstruct the impacts in both the small and large data sets for two out of the three policies with moderate accuracy (with a Nash-Sutcliffe Efficiency, NSE > 0.4). DMDc was able to capture the general trends in the data but not interannual variability. These findings suggests that DMDc shows promise for impact assessments, but policy variables have to be carefully selected. Improvements to the DMDc pipeline that could improve performance and interpretability are discussed, including data pre-processing steps, architectural changes, and modelconstraints informed by expert- or stakeholder opinion.

Droughts, traditionally less associated with high-latitude regions, are emerging as significant challenges due to changing climatic conditions. Recent severe droughts in Europe have exposed the vulnerability of northern catchments, where shifts in temperature and precipitation patterns may intensify drought impacts. This study investigates the dynamics of drought propagation in high-latitude regions, focusing on four key aspects: (1) the typical lag time for drought conditions to propagate from initial precipitation deficits to impacts on soil moisture, streamflow, and groundwater systems; (2) the probability of precipitation deficits leading to these droughts; (3) the key catchment characteristics influencing drought propagation; and (4) the way in which drought propagation has evolved under changing climate conditions. By analyzing long-term observational records from 50 Swedish catchments, the study reveals that drought propagation is highly variable and influenced by a complex interplay of catchment characteristics, hydroclimatic conditions, and soil properties. Soil moisture exhibits the shortest propagation times, often responding within a month to precipitation deficits, while groundwater shows the longest and most variable response times, sometimes exceeding several months. The probability of precipitation deficits propagating into soil moisture droughts is highest, followed by streamflow and groundwater, with these probabilities increasing over time. Across all drought types, annual precipitation and streamflow emerge as the most influential factors governing both propagation time and probability. Although most catchments have become wetter year-round due to climate change, southern catchments are increasingly vulnerable to spring droughts (particularly soil moisture drought), driven by increasing evaporative demand. Despite these hydroclimatic shifts, no significant long-term trends in propagation times or probabilities have been observed over the past 60 years. These findings highlight the need for tailored region-specific water management strategies to address seasonal and regional variations in drought risks, particularly as climate change continues to reshape hydrological regimes.

There is a global call for proactive drought risk management, stressing the need to further our understanding of the systemic nature of drought risk. Proactive drought risk management requires an understanding of not only the drought hazard itself, but also the underlying vulnerabilities in sociohydrological systems. As a result, drought vulnerability assessments are increasingly being conducted across the globe. However, drought vulnerability is complex and shaped by the social, ecological, and hydroclimatic context. Thus, understanding how vulnerability is manifested depending on regional, sectoral, or societal differences is crucial. Therefore, here we present an assessment of the practical relevance and relative impact of various drought vulnerability factors for water-dependent sectors and societies in forested cold climates. The analysis was based on the results of an online survey conducted in Sweden, targeting stakeholders from seven water-dependent sectors, working in authorities, private and public enterprises, NGOs, and trade associations. Respondents were asked to rate a comprehensive list of vulnerability factors, connected to sectoral and societal vulnerability as well as governance, based on their perceived impact on drought risk in their sector as well as for society as a whole. Results showed that the relevance and impact of individual vulnerability factors differed across sectors, with the forestry sector especially standing out compared to other sectors. Furthermore, the results indicate regional differences in societal vulnerability factors. The substantial list of vulnerability factors found to be relevant by the respondents demonstrates the complex nature of drought risk, as well as the importance of using caution when selecting generic vulnerability factors for applied vulnerability assessments. Furthermore, the results provide a comprehensive guide to both sectoral and societal drought vulnerability in sociohydrological systems located in forested cold climates.

To better understand the increasing human impact on the water cycle and the feedbacks between hydrology and society, the International Association of Hydrological Sciences (IAHS) organized the scientific decade “Panta Rhei – Everything Flows: Change in hydrology and society” (2013–2022). A key finding is the need to use integrated approaches to assess the co-evolution of human–water systems in order to avoid unintended consequences of human interventions over long periods of time. Additionally, substantial progress has been made in leveraging new data sources on human behaviour, e.g. through text mining of social media posts. Much has been learned about detecting hydrological changes and attributing them to their drivers, e.g. quantifying climate effects on floods. To achieve further progress, we recommend broadening the understanding, the discipline and training activities, while at the same time pursuing synthesis by focusing on key themes, developing innovative approaches and finding sustainable solutions to the world’s water problems.

The European continent has experienced several large-scale drought events in recent years, and climate projections suggest an increasing drought risk in many parts of the world. As droughts can have large impacts on socio-hydrological systems, analyzing drought risk is an important part of proactive drought risk management and disaster risk reduction. Drought risk can be expressed as a product of hazard, exposure, and vulnerability, where vulnerability is highly contextual and complex. As droughts can affect all parts of the hydrological system, from precipitation and soil moisture to groundwater and surface water reservoirs, drought vulnerability differs depending on what part of the system is studied. Building on previous results from a survey analyzing drought vulnerability across seven water-dependent sectors, this paper explores how vulnerability factors vary based on sectors' dependency on blue water (surface and subsurface freshwater) or green water (soil moisture) in mid- and high-latitude regions. The findings reveal that drought vulnerability differs based on water type dependency, especially concerning water supply and species characteristics. Perceptions of vulnerability factors vary in number, category, and overall ranking, highlighting the importance of considering water dependency when choosing vulnerability factors for drought risk assessments and to clearly define the drought hazard types involved.

Attaining resource security in the water, energy, food, and ecosystem (WEFE) sectors, the WEFE nexus, is paramount. This necessitates the use of quantitative modelling, which presents many challenges, as this is a complex system acting at the intersection of the physical- and social sciences. However, as WEFE data is becoming more widely available, data-driven methods of modelling this system are becoming increasingly viable. Here, we discuss two main problems in WEFE nexus modelling: system identification and control. System identification uses Machine Learning algorithms to obtain dynamical models from data and have shown promise in many disciplines with similar characteristics as the nexus. Meanwhile, control algorithms manipulate a system to achieve objectives and are becoming instrumental in shaping nexus policy. Despite the promise of these algorithms, data-driven modelling is a vast and daunting field, and so here we provide an introductory overview of this field, with emphasis on nexus applications.

In a changing climate, drought risk and vulnerability assessments are becoming increasingly important. Following the global call for proactive drought risk management, drought vulnerability assessments are progressively taking their stage in the drought research community. As the manifestation of drought vulnerability is dependent on the social, ecological, and hydroclimatic context in which it occurs, identifying vulnerability factors relevant for specific climatological and ecological regions may improve the quality of vulnerability assessments. Meanwhile, a holistic overview of factors affecting vulnerability in polar and cold climates is currently lacking. These regions are home to large socio-hydrological systems including urban areas, energy systems, agricultural practices, and the boreal forest. By conducting an interdisciplinary systematic literature review, the manifestation and conceptualization of drought vulnerability were identified for forested ecoregions in the Köppen–Geiger D and E climates. Vulnerability factors, as described by several scientific disciplines, were identified and combined into a conceptual framework for drought vulnerability in the study region. The results demonstrate the wide range of conceptualizations that exist for assessing drought vulnerability, and the thematic differences between sectors such as forestry, water supply, and agriculture. The conceptual framework presented herein adopts a novel approach, categorizing vulnerability factors by their location in a socio-hydrological system, and their relation to blue or green water sources. This allowed for identification of systemic vulnerability patterns, providing new insights into regional differences in drought vulnerability and a base for stakeholders performing proactive drought risk assessments in the study region.

Linkages between landscapes and streams are increasingly described in terms of hydrological connectivity. The ability to effectively distinguish different patterns of water movement through catchments makes connectivity particularly interesting to both scientists and practical water managers. Hydrometric data (groundwater levels, soil moisture and streamflow) are often employed to infer the connection between the landscape and its drainage network. Such observational data, however, are insufficient to infer subsurface connectivity in humid settings with perennial stream flow, due to the risk of equifinality. To quantify how much subsurface flow patterns can differ and still be consistent (equifinal) with comprehensive observations of hillslope groundwater levels and stream runoff (the hydrometric data), this study used a modelling experiment based on a well-characterised field site. Particle-tracking simulations at different flow rates defined the water flow paths and transit times of two virtual hillslopes that differed profoundly in the vertical distribution of the saturated hydraulic conductivity. Even though the simulated weekly stream flows and groundwater levels were similar (i.e., the hillslopes were hydrometrically equifinal) particle velocities and water ages at specific locations along these hillslopes differed by orders of magnitude. Flow path lengths and catchment transit times varied up to several 100%. The hillslope- and stream-based metrics used to describe connectivity also varied with stream flow rates. These results underline the need to recognise the risks for equifinality when inferring subsurface connectivity from hydrometric observations alone, even when those observations are comprehensive. The results also highlight the value of model simulations for quantifying the uncertainty in the inferred connectivity, targeting the best sampling locations/times to reduce this uncertainty with tracer data and better understanding the way connectivity influences stream chemistry.

Multi-model combination (averaging) methods (MMCMs) are used to improve the accuracy of hydrological (precipitation-runoff) outputs in simulation or forecasting/prediction modes. In this paper, we examined if the application of MMCMs can improve model performance in reproducing distributions of hydrological signatures, such as annual maxima or minima of varying durations. To this end, ten MMCMs were applied to 29 bucket-type models to simulate runoff in 50 high-latitude catchments. The MMCMs were evaluated by comparing the resulting simulated flows to the reference (i.e., best-performing) individual model, considering various commonly used performance indicators, as well as model performance in reproducing the distributions of signatures. Additionally, we analysed whether (1) the selection of the candidate models, or (2) targeting specific signatures, such as annual maxima or minima, can improve performance of the model combinations. The results suggest that the application of MMCMs can improve accuracy of runoff simulations in terms of traditional performance indicators, but fails to improve performance in reproducing the distributions of signatures. Neither excluding poor-performing models nor applying the MMCMs with the targeted signatures, improves this aspect of model performance. These findings clearly reveal the need for further research aiming at enhancing model performance in reproducing the distributions of hydrological signatures, which is essential for climate-change impact studies.

Peatlands are major terrestrial soil carbon stores, and open mires in boreal landscapes hold a considerable fraction of the global peat carbon. Despite decades of study, large-scale spatiotemporal analyses of mire arrangement have been scarce, which has limited our ability to scale-up mire properties, such as carbon accumulation to the landscape level. Here, we use a land-uplift mire chronosequence in northern Sweden spanning 9,000 years to quantify controls on mire distribution patterns. Our objectives include assessing changes in the spatial arrangement of mires with land surface age, and understanding modifications by upland hydrotopography. Characterizing over 3,000 mires along a 30 km transect, we found that the time since land emergence from the sea was the dominant control over mire coverage, especially for the establishment of large mire complexes. Mires at the youngest end of the chronosequence were small with heterogenous morphometry (shape, slope, and catchment-to-mire areal ratios), while mires on the oldest surfaces were variable in size, but included larger mires with more complex shapes and smaller catchment-to-mire ratios. In general, complex topography fragmented mires by constraining the lateral expansion, resulting in a greater number of mires, but reduced total mire area regardless of landscape age. Mires in this study area occurred on slopes up to 4%, indicating a hydrological boundary to peatland expansion under local climatic conditions. The consistency in mire responses to spatiotemporal controls illustrates how temporal limitation in peat initiation and accumulation, and topographic constraints to mire expansion together have shaped present day mire distribution patterns. Peatlands store nearly one third of the global soil carbon, despite covering only around three percent of the land surface. Open mires, which are characteristic peatland types at high latitudes, represent an important peat carbon store. Few studies have explored how mire patterns in the landscape change over time and space. This knowledge gap has limited our ability to estimate and scale-up mire properties, such as the peat carbon store, from the individual mire to the entire mire landscape. Here, we study the mire patch distribution in a landscape that covers nine thousand years of landscape development. Using this aging landscape, we can separate temporal controls on mire patterns from spatial controls related to local topography. We found that mire cover was mainly controlled by age, while the abundance of mires and their fragmentation was defined by local topography, for example, through the catchment-to-mire ratio and the slope of the surrounding upland areas, which define the limits for mire expansion upland. Our results provide an important step in understanding the spatial and temporal controls that give rise to present mire distribution patterns. Such information can further support landscape-level estimations of mire properties and functions, such as the long-term peat carbon store. Mire cover and shape are linked to the formation of large mire complexes, while abundance and fragmentation are driven by topography Areas of recent isostatic uplift hold small mires, while diverse initiation and expansion lead to heterogeneous mire patches in older areas Scaling up mire properties to the landscape level requires an understanding of spatiotemporal controls behind mire distribution patterns