Precipitation patterns play a crucial role in sustaining rainfed agriculture, particularly in regions like Ethiopia, where millions depend on it for their livelihoods. Understanding the ability of climate models to simulate precipitation accurately is essential for predicting the potential impacts of climate change, especially in regions with complex topography like Ethiopia. This study assesses the performance of 16 CMIP6 climate models in simulating precipitation patterns across different rainfall regimes in the Amhara region. By comparing model outputs with observed data, the research aims to identify which models best capture the seasonal and annual variability in precipitation, thereby informing climate adaptation strategies.To conduct the analysis, observational data from the Enhanced National Climate Services and Climate Hazard Infrared Precipitation with Stations datasets were utilized. The study focused on evaluating the models' performance over the period 1985–2014 using statistical metrics such as the coefficient of determination (R2), root mean square error (RMSE), mean bias (MB), and Student's t-test. In the Western Amhara region, the models were further assessed with Taylor Skill Score (TSS), Inter-annual Variability Score (IVS), and Comprehensive Rating Method (CRM). The top-performing models for simulating the annual rainfall cycle in this region were GFDL-ESM4 (CRM: 0.88), EC-Earth3-Veg (CRM: 0.85), and CESM2 (CRM: 0.82). Other notable models included MRI-ESM2.0, MPI-ESM1-2-HR, and IPSL-CM6A-LR. In the Eastern Amhara region, which follows a bi-modal rainfall pattern, EC-Earth3-Veg (CRM: 0.85, R: 0.83, RMSE: 52.4 ​mm/month) showed the best performance, followed by MRI-ESM2.0 (CRM: 0.76, R: 0.76, RMSE: 55.6 ​mm/month) and CESM2 (CRM: 0.82, R: 0.88, RMSE: 65.46 ​mm/month). GFDL-ESM4 also demonstrated strong performance (CRM: 0.88, R: 0.77, RMSE: 55.6 ​mm/month). CMCC-ESM2, although lower-ranked in Western Amhara (CRM: ∼0.41), performed better in the Eastern region. However, most models exhibited a dry bias and substantial inter-model variability, particularly in simulating rainfall patterns in highland areas. Only 31 ​% and 44 ​% of models successfully captured the seasonality of rainfall in the Western and Eastern Amhara regions, respectively. Even the top models showed significant discrepancies compared to observed rainfall, indicating ongoing challenges in model accuracy. These findings provide valuable insights for developing targeted climate adaptation strategies in the Amhara region and highlight the need for improving climate models to better assess future climate change impacts in Ethiopia.

Green-blue-grey infrastructure (GBGI) offers environmental benefits in urban areas, yet its impact on air pollution is under-researched, and the literature fragmented. This review evaluates quantitative studies on GBGI's capability to mitigate air pollution, compares their specific pollutant removal processes, and identifies areas for further investigation. Of the 51 GBGI types reviewed, only 22 provided quantitative pollution reduction data. Street trees and mixed-GBGI are the most studied GBGIs, with efficacy influenced by wind, GBGI type vegetation characteristics, and urban morphology. Negative percentages denote worsening air quality, while positive reflect improvement. The 22 different GBGI grouped into eight main categories provide an average (± s.d.) reduction in air pollution of 16 ± 21%, with substantial reduction shown by linear features (23 ± 21%), parks (22 ± 34%), constructed GI (14 ± 25%), and other non-sealed urban areas (14 ± 20%). Other individual GBGI reducing air pollutants include woodlands (21 ± 38%), hedges (14 ± 25%), green walls (14 ± 27%), shrubland (12 ± 20%), green roofs (13 ± 23%), parks (9±36%), and mixed-GBGI (7 ± 23 %). On average, GBGI reduced PM1, PM2.5, PM10, UFP and BC by 13 ± 21%, 1 ± 25%, 7 ± 42%, 27 ± 27%, and 16 ± 41%, respectively. GBGI also lowered gaseous pollutants CO, O3 and NOx by 10 ± 21%, 7 ± 21%, and 12 ± 36%, on average, respectively. Linear (e.g., street trees and hedges) and constructed (e.g., green walls) features can impact local air quality, positively or negatively, based on the configuration and density of the built environment. Street trees generally showed adverse effects in street canyons and beneficial outcomes in open-road conditions. Climate change could worsen air pollution problems and impact GBGI effectiveness by shifting climate zones. In Europe and China, climate shifts are anticipated to affect 8 of the 22 GBGIs, with the rest expected to remain resilient. Despite GBGI's potential to enhance air quality, the meta-analysis highlights the need for a standardised reporting structure or to enable meaningful comparisons and effectively integrate findings into urban pollution and climate strategies.

The combination of urbanization and global warming leads to urban overheating and compounds the frequency and intensity of extreme heat events due to climate change. Yet, the risk of urban overheating can be mitigated by urban green-blue-grey infrastructure (GBGI), such as parks, wetlands, and engineered greening, which have the potential to effectively reduce summer air temperatures. Despite many reviews, the evidence bases on quantified GBGI cooling benefits remains partial and the practical recommendations for implementation are unclear. This systematic literature review synthesizes the evidence base for heat mitigation and related co-benefits, identifies knowledge gaps, and proposes recommendations for their implementation to maximize their benefits. After screening 27,486 papers, 202 were reviewed, based on 51 GBGI types categorized under 10 main divisions. Certain GBGI (green walls, parks, street trees) have been well researched for their urban cooling capabilities. However, several other GBGI have received negligible (zoological garden, golf course, estuary) or minimal (private garden, allotment) attention. The most efficient air cooling was observed in botanical gardens (5.0 ± 3.5°C), wetlands (4.9 ± 3.2°C), green walls (4.1 ± 4.2°C), street trees (3.8 ± 3.1°C), and vegetated balconies (3.8 ± 2.7°C). Under changing climate conditions (2070–2100) with consideration of RCP8.5, there is a shift in climate subtypes, either within the same climate zone (e.g., Dfa to Dfb and Cfb to Cfa) or across other climate zones (e.g., Dfb [continental warm-summer humid] to BSk [dry, cold semi-arid] and Cwa [temperate] to Am [tropical]). These shifts may result in lower efficiency for the current GBGI in the future. Given the importance of multiple services, it is crucial to balance their functionality, cooling performance, and other related co-benefits when planning for the future GBGI. This global GBGI heat mitigation inventory can assist policymakers and urban planners in prioritizing effective interventions to reduce the risk of urban overheating, filling research gaps, and promoting community resilience.

As climate change intensifies, the frequency and intensity of heatwaves are rising to pose significant health risks. Population vulnerability, influenced by socioeconomic and demographic factors, is a widespread concern. We analysed heat vulnerability by demonstrating usefulness of principal component analysis on recent, localised census data at lower super output scale for vulnerability factors such as poverty, access to cooling facilities, age, and gender for a non-city yet highly heat risk vulnerable case study of Surrey, UK. Four major factors (poverty, elderly population, unemployed students, daily commute) were identified, creating a cumulative Heat Vulnerability Index, aiding in prioritising interventions and mapping vulnerable areas. Mapping revealed most areas had a moderate vulnerability level of 3 out of 6 for individual major factors, with cumulative scores ranging from 11 to 12 out of 20. The study emphasises the interconnectedness of vulnerability factors and highlights the applicability of the approach beyond Surrey. The demonstrated methodology provides a valuable template for vulnerability assessments in regions facing similar challenges and have its up-to-date effective heat action plan underlining the importance of tailored strategies for comprehensive heat risk management (e.g. cooling centres, transport aid, multilingual risk communication and home visits). Policymakers can utilise the insights gained to develop targeted measures for vulnerable populations and manage heat-related issues effectively on a global scale.

The projection and identification of historical and future changes in climatic systems is crucial. This study aims to assess the performance of CMIP6 climate models and projections of precipitation and temperature variables over the Upper Blue Nile Basin (UBNB), Northwestern Ethiopia. The bias in the CMIP6 model data was adjusted using data from meteorological stations. Additionally, this study uses daily CMIP6 precipitation and temperature data under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios for the near (2015–2044), mid (2045–2074), and far (2075–2100) periods. Power transformation and distribution mapping bias correction techniques were used to adjust biases in precipitation and temperature data from seven CMIP6 models. To validate the model data against observed data, statistical evaluation techniques were employed. Mann–Kendall (MK) and Sen’s slope estimator were also performed to identify trends and magnitudes of variations in rainfall and temperature, respectively. The performance evaluation revealed that the INM-CM5-0 and INM-CM4-8 models performed best for precipitation and temperature, respectively. The precipitation projections in all agro-climatic zones under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios show a significant (p < 0.01) positive trend. The mean annual maximum temperature over UBNB is estimated to increase by 1.8 °C, 2.1 °C, and 2.8 °C under SSP1-2.6, SSP2-4.5, and SSP5-8.5 between 2015 and 2100, respectively. Similarly, the mean annually minimum temperature is estimated to increase by 1.5 °C, 2.1 °C, and 3.1 °C under SSP1-2.6, SSP2-4.5, and SSP5-8.5, respectively. These significant changes in climate variables are anticipated to alter the incidence and severity of extremes. Hence, communities should adopt various adaptation practices to mitigate the effects of rising temperatures.

The use of nature-based solutions (NbS) to address the risks posed by hydro-meteorological hazards have not yet become part of the mainstream policy response, and one of the main reasons cited for this, is the lack of evidence that they can effectively reduce disaster risk. This paper addresses this issue, by providing model-based evidence from five European case studies which demonstrate the effectiveness of five different NbS in reducing the magnitude of the hazard and thus risk, in present-day and possible future climates. In OAL-Austria, the hazard is a deep-seated landslide, and the NbS analysed is afforestation. Modelling results show that in today's climate and a landcover scenario of mature forest, a reduction in landslide velocity of 27.6% could be achieved. In OAL-Germany, the hazard is river flooding and the NbS analysed is managed grazing with removal of woody vegetation. Modelling results show that the NbS could potentially reduce maximum flood water depth in the near-future (2031-2060) and far-future (2070-2099), by 0.036m and 0.155m, respectively. In OAL-Greece, the hazard is river flooding, and the NbS is upscaled natural storage reservoirs. Modelling results show that in a possible future climate the upscaled NbS show most potential in reducing the total flooded area by up to 1.26 km2. In OAL-Ireland, the hazard is surface and river flooding, and the NbS is green roofs. Results from a modelled upscaling analysis under two different climate scenarios show that both maximum flood water depth, and total flooded area were able to be reduced. In OAL-UK, the hazard is shallow landslides, and the NbS is high-density planting of two different tree species. Modelling results under two different climate scenarios show that both tree species were able to improve slope stability, and that this increased over time as the NbS matured. The significance of these results is discussed within the context of the performance of the NbS over time, to different magnitude type events, impact with stakeholders in engendering wider support for the adoption of the NbS in the OALs, and the uncertainty in the modelling analyses.

Providing children with a clear understanding of climate change drivers and their mitigation is crucial for their roles as future earth stewards. To achieve this, it will be necessary to reverse the declining interest in STEM (Science, Technology, Engineering and Mathematics) education in schools in the UK and other countries, as STEM skills will be critical when designing effective mitigation solutions for climate change. The ‘Heat-Cool Initiative’ was co-designed and successfully implemented in five primary/secondary UK schools, as a playful learning tool to unleash student interest in STEM subjects. 103 students from two cohorts (years 5–6 and 7–9) participated in five Heat-Cool activity sessions where they used infrared cameras to explore the issue of urban heat. Their learning was evaluated using a multi-functional quantitative assessment, including pre- and post-session quizzes. Climate change literacy increased by 9.4% in primary school children and by 4.5% in secondary school children. Analyses of >2000 infrared images taken by students, categorised into 13 common themes, revealed age-related differences in children's cognitive development. At primary school age, images of the ‘self’ dominated; secondary school children engaged more with their physical environment. This novel approach demonstrated the importance of developing tailored technology-enhanced STEM education programmes for different age cohorts, leading to a high capacity for improving learning outcomes regarding climate change. Such programmes, embedded in school curricula nationally and internationally, could become a much-needed positive contribution to reaching the United Nation's Sustainable Development Goals, especially Goals 4 (Quality Education) and 13 (Climate Action).

Nature-based solutions (NbS) can be beneficial to help human communities build resilience to climate change by managing and mitigating related hydro-meteorological hazards (HMHs). Substantial research has been carried out in the past on the detection and assessment of HMHs and their derived risks. Yet, knowledge on the performance and functioning of NbS to address these hazards is severely lacking. The latter is exacerbated by the lack of practical and viable approaches that would help identify and select NbS for specific problems. The EU-funded OPERANDUM project established seven Open-Air Laboratories (OALs) across Europe to co-develop, test, and generate an evidence base from innovative NbS deployed to address HMHs such as flooding, droughts, landslides, erosion, and eutrophication. Herein, we detail the original approaches that each OAL followed in the process of identifying and selecting NbS for specific hazards with the aim of proposing a novel, generic framework for selecting NbS. We found that the process of selecting NBS was overall complex and context-specific in all the OALs, and it comprised 26 steps distributed across three stages: (i) Problem recognition, (ii) NbS identification, and (iii) NbS selection. We also identified over 20 selection criteria which, in most cases, were shared across OALs and were chiefly related to sustainability aspects. All the identified NbS were related to the regulation of the water cycle, and they were mostly chosen according to three main factors: (i) hazard type, (ii) hazard scale, and (iii) OAL size. We noticed that OALs exposed to landslides and erosion selected NbS capable to manage water budgets within the soil compartment at the local or landscape scale, while OALs exposed to floods, droughts, and eutrophication selected approaches to managing water transport and storage at the catchment scale. We successfully portrayed a synthesis of the stages and steps followed in the OALs' NbS selection process in a framework. The framework, which reflects the experiences of the stakeholders involved, is inclusive and integrated, and it can serve as a basis to inform NbS selection processes whilst facilitating the organisation of diverse stakeholders working towards finding solutions to natural hazards. We animate the future development of the proposed framework by integrating financial viability steps. We also encourage studies looking into the implementation of the proposed framework through quantitative approaches integrating multi-criteria analyses.

The use of Nature-based Solutions (NBS), designed and implemented with participatory approaches, is rapidly increasing. Much use is being made of the Living Lab (LL) concept to co-create innovative NBS with stakeholders in a certain societal and environmental, real-life context. Most of the current research revolves around urban LLs, thus overlooking specificities of rural areas. Furthermore, the influence of the context itself on co-creation processes is insufficiently recognised, leaving challenges associated with co-creation such as stakeholder engagement unresolved. By exploring the co-creation processes in the LLs of the OPERANDUM project, this study identifies eighteen contextual factors shaping the co-creation processes of NBS within rural territories and provides associated recommendations. In addition, based on lessons learnt in the OPERANDUM project, we discuss the value of a relational place-based approach in LLs, suggesting that the co-creation process should be approached as a dynamic confluence of many interconnected contextual factors. We conclude that acknowledging the interconnections in co-creation in the real-life context of rural territories may increase the success and impact of the LL approach, and ultimately, the benefits of NBS.

The international community, particularly across the European Union (EU), is increasingly recognizing and promoting Nature-based Solutions (NBS) as long-term and sustainable measures against hydro-meteorological hazards such as flooding, coastal erosion, heat waves and landslides. Yet, scaled implementation of NBS at EU and global level presently remains a challenge due to often complex and lengthy permitting procedures. While efforts have been made to highlight the explicit and implicit role of NBS in major global and European policy frameworks, uncertainty remains when it comes to the level of coherence across government levels, from international to national and local scale. This paper attempts to address this gap by introducing an open-access online policy catalogue pertaining to the implementation of 740 NBS projects globally to mitigate the impact of hydro-meteorological phenomena. Based on a policy screening of 88 NBS projects in Europe and an in-depth analysis of the NBS permitting paths across seven Open-Air Laboratories in European countries, we examine the linkages between European and national legislation and policies. Understanding these linkages will help promote NBS mainstreaming as the NBS agenda is set at EU and global level while implementation is heavily dependent on national-scale governance. We identify a common permitting path for NBS paved by the EU in several directives, as well as some divergence in the implementation of these directives at national level which can pose significant challenges to the uptake of NBS. The NBS policy catalogue provides a valuable resource for further analysis of the NBS policy context from local to global levels towards increasing uptake and acceptance of NBS in Europe and beyond.

Nature-based solutions (NBS) such as green (vegetation) and blue (waterbodies) infrastructure are being promoted as cost-effective and sustainable strategies for managing the heatwaves risks, but long-term monitoring evidence is needed to support their implementation. This work aims to conduct a comparative assessment of the cooling efficiency of green (woodland and grassland) and blue (waterbody) NBS in contrast to a built-up area. Over a year of continuous fixed monitoring showed that the average daily maximum temperatures at NBS locations were 2-3(degrees)C (up-to 15%) lower than the built-up area. Woodland showed the maximum temperature reduction in almost all seasons, followed by waterbody and grassland. NBS performed the best during the summers, peak sunshine, and heatwave hours (up to similar to 6(degrees)C cooler than built-up area). Using an e-bike for mobile monitoring, the areas where green-blue NBS were combined showed the highest spatial cooling extent, followed by waterbody, woodland, and grassland areas. The database generated can validate city-scale environmental models and assist city planners to incorporate NBS into urban dwellings based on the opportunity, need and scope, aligning with Sustainable Development Goals 11 (sustainable cities and communities) and 13 (climate action).

In Ethiopia, the impacts of climate change are expected to have significant consequences for agriculture and food security. This study investigates both past (1981–2010) and future (2041–2070) climate trends and their influence on the length of the growing season (LGS) in the North-Western Ethiopian highlands. Climate observations were obtained from the National Meteorological Agency of Ethiopia, while the best performing and highest resolution models from the CMIP5 experiment and RCP6 (Coupled Models Intercomparison Project and representative concentration pathway 6) were used for the analysis. Standard statistical methods were applied to compute soil water content, evaluate climate variability and trends, and assess their impact on the length of the growing season. Maximum temperature (tasmax) and minimum temperature (tasmin) inter-annual variability anomalies show that the region has experienced cooler years than hotter years in the past. However, in the future, the coolest years are expected to decrease by −1.2 °C, while the hottest years will increase by +1.3 °C. During the major rainfall season (JJAS), the area has received an adequate amount of rainfall in the past and is very likely to receive similar rainfall in the future. On the other hand, the rainfall amount in the season February to May (FMAM) is expected to assist only with early planting. For the season October to January (ONDJ), the rainfall amount may help lengthen the growing season of JJAS if properly utilized; otherwise, the season has the potential to destroy crops before and during the harvesting time. The soil water content changes in the future remain close to those of the past period. The length of growing seasons has less variable onset and cessation dates, while in the future, the length of the growing period (LGP) of 174 to 177 days will be suitable for short- and long-cycle crops, as well as double cropping, benefiting crop production yield in the North-Western Ethiopian highlands in the future.

The knowledge derived from successful case studies can act as a driver for the implementation and upscaling of nature-based solutions (NBS). This work reviewed 547 case studies to gain an overview of NBS practices and their role in reducing the adverse impact of natural hazards and climate change. The majority (60 %) of case studies are situated in Europe compared with the rest of the world where they are poorly represented. Of 547 case studies, 33 % were green solutions followed by hybrid (31 %), mixed (27 %), and blue (10 %) approaches. Approximately half (48 %) of these NBS interventions were implemented in urban (24 %), and river and lake (24 %) ecosystems. Regarding the scale of intervention, 92 % of the case studies were operationalised at local (50 %) and watershed (46 %) scales while very few (4 %) were implemented at the landscape scale. The results also showed that 63 % of NBS have been used to deal with natural hazards, climate change, and loss of biodiversity, while the remaining 37 % address socio-economic challenges (e.g., economic development, social justice, inequality, and cohesion). Around 88 % of NBS implementations were supported by policies at the national level and the rest 12 % at local and regional levels. Most of the analysed cases contributed to Sustainable Development Goals 15, 13, and 6, and biodiversity strategic goals B and D. Case studies also highlighted the co-benefits of NBS: 64 % of them were environmental co-benefits (e.g., improving biodiversity, air and water qualities, and carbon storage) while 36 % were social (27 %) and economic (9 %) co-benefits. This synthesis of case studies helps to bridge the knowledge gap between scientists, policymakers, and practitioners, which can allow adopting and upscaling of NBS for disaster risk reduction and climate change adaptation and enhance their preference in decision-making processes.

A number of Nature Based Solutions (NBS) are being used around the world in order to address various hydrometeorological hazards as a more environmentally friendly alternative to hard structures. Such a solution has been created in the Spercheios river basin in Central Greece, which is susceptible to heavy rainfall and river bank overflow due to flood water from upstream, in order to mitigate flood and drought impacts under current and future climate conditions. Here a first attempt is made to use actual measurements taken from various sources in the river, including in-situ and satellite data, in order to establish early experimental evidence of the NBS efficiency in the area. The measurements include data from automated hydrological stations from the OpenHi network, satellite remote sensing data and field measurements performed along the Spercheios River basin. For each measurement used, different analysis has been performed based on data availability and pertinence to the NBS efficiency. Preliminary results presented here show that the NBS functions as designed and provides protection against flooding in the area, and can potentially diminish the risk of drought. The results are in agreement with the numerical outputs already presented in our previous work.

With ongoing climate change, the number, frequency, and intensity of events of extremely hot days during summers called heatwaves are progressing. Vulnerability of the population is one aspect responsible for the risk induced by such heatwaves. In society, certain characteristics make one group of people more vulnerable to heatwaves than others, such as poverty, access to cooling facilities, age, gender etc. The current research identifies such vulnerability factors or indicators of population to help in devising heat management strategies. This research focuses on a small bucolic region (Guildford) in Surrey county of the United Kingdom as mostly risk or vulnerability factors are underestimated and ignored in such regions compared to city population. Twelve heat vulnerability factors or indicators (house type, sex, age, ethnicity, place density, access to central heating, residence type: communal, health condition, household composition, disability, accommodation tenure i.e. rented or owned, and education level) were selected after reviewing several literatures to include in the study based on their data availability. Census data on such vulnerability indicators at lower output scale were collected. Principal component analysis was performed, and four major principal components were identified from these 12 factors which explained most of the variance (82 %) in the data. The corresponding loading value of each of these factors were utilised to find heat vulnerability indices for each lower output area and these indices were mapped using QGIS. It was noted that not only people living in town centre which is generally considered hotter and so are highly vulnerable, but outskirt regions were also significantly vulnerable compared to other lesser vulnerable regions. Such a vulnerability map can help authorities for site focused heat mitigation strategies application, early warnings, and preparation during summers, particularly during excessively hot days i.e., heatwaves. Nature-based permanent solution can be encouraged in regions of such highly vulnerable identified regions.

Climate change is increasing the probability of extreme precipitation in many regions, which will lead to an increased risk of major flooding events. Recent years have seen an interest in the use of so-called nature-based solutions (NbS) to help respond and reduce the risk posed by such extreme events. This paper provides an analysis of the use of NbS to help reduce flood risk at the open-air laboratory Germany (OAL-Germany), which is part of the EU Horizon 2020 project OPERANDUM. OAL-Germany is located in the Biosphere Reserve Lower Saxony Elbe Valley. Following major flooding events which occurred in OAL-Germany in 2002 and 2013, a cooperative flood management NbS was implemented over the period 2014-2015 and has been in place since then. The NbS consisted of cutting back woody vegetation in certain locations along the riverbank which impeded overbanking during flood events, and the use of various grazing animals to try and prevent the regrowth of such woody vegetation. The objective of this study is to evaluate the efficiency of NBS against flood risk under present-day climate change scenarios and assess future flood inundations and velocities in OAL-Germany. The daily precipitation data obtained from the EURO-CORDEX project dataset for 1971–2000 and 2051–2080 represented historical and future simulations, respectively. The hydrologic model HEC-HMS was integrated with the hydraulic model HEC-RAS to simulate discharge, flood velocity, and water depth/inundations of past and future events. For HEC-RAS model boundary conditions, daily flow data with long-term quality-controlled data, obtained from the Global Runoff Data Centre were used. The model was simulated for two scenarios: (1) pre-NBS implementation, considering the landcover of mixed forest; and (2) post-NBS implementation using pastureland, which is the current NBS/landcover in place. The results of the simulation show that the pastureland released the floodwater from the main river system faster than the previous landcover. Overall, the floodwater velocity of pastureland increased by 21%, while flood depth showed a decrease of 2% compared with mixed forest. Therefore, if the modelled NBS had actually been in place in 2012, then it is reasonable to expect that they would have contributed to a reduction in flood risk further downstream from the modelled NBS areas, in the June 2013 flood event. This study can help to improve NBS uptake and upscaling, which is critical to improve NBS planning, implementation, and effectiveness assessment. Keywords: Nature-based solutions; HEC-RAS Model; Flood depth; Flood Velocity; Roughness coefficients; Climate Change Acknowledgments This work has been carried out under the framework of OPERANDUM (OPEn-air laboRAtories for Nature baseD solUtions to Manage hydro-meteo risks) project, which is funded by the European Union's Horizon 2020 research and innovation programme under the Grant Agreement No: 776848.

Nature-based Solutions function (NBS) as an umbrella concept for ecosystem-based approaches that are an alternative to traditional engineering solutions for Disaster Risk Reduction. Their rising popularity is explained partly by their entailing additional benefits (so-called co-benefits) for the environment, society, and economy. The few existing frameworks for assessing co-benefits are lacking guidance on co-benefit pre-assessment that is required for the NBS selection and permission process. Going beyond these, this paper develops a comprehensive guidance on quantitative pre-assessment of potential co-benefits and disbenefits of NBS tackling Disaster Risk Reduction. It builds on methods and frameworks from existing NBS literature and related disciplines. Furthermore, this paper discusses the evaluation of the quantified results of the pre-assessment. In particular, the evaluation focuses on the significance of change of the estimated co-benefits and disbenefits as well as the sustainability of the NBS. This paper will support decision-making in planning processes on suitability and sustainability of Nature-based Solutions and assist in the preparation of Environmental Impact Assessments of projects.

Heatwaves pose a protracted health risk depending on its intensity and exposure time. Not only cities but countryside areas are also exposed to risk of summertime heat which has not been recently updated at the bucolic scale. This study aims to associate temperature and mortality and explore its temporal variation. A Poisson regression model combined with a distributed lag non-linear model was applied over daily mortality and maximum temperature data from 1981 to 2018 to formulate the lagged response of summer temperature. The relative risk (RR) and mortality attributable fraction (AF) with respect to minimum mortality temperature (MMT) in Southeast England and Aberdeenshire, UK was calculated. The RR and AF for high and extreme (95th and 99th percentile) temperature with respect to MMT have increased (RR- 1% and 7%; AF- 1.33 and 1.9 times, respectively) in Southeast England but reduced in Aberdeenshire (RR- 2% and 6%; AF- 0.49 and 0.15 times, respectively) in last two decades. However, lagged risk persists for very extreme temperature after several days of exposure at both sites and the hazard cannot be underestimated and neglected. Hence, action is needed to update the heat action plan for extreme temperature management formulating appropriate heat-mitigation strategies focused on vulnerable populations.