Global warming due to anthropogenic emission of green-house gases has induced climate change which is disturbing and will continue to impact the ecology and energy balance of our earth environment. The duration, frequency and intensity of extreme hot days in summers called heatwaves have increased with the beginning of the 21st century worldwide and have been projected to increase. Associated human health loss or damage can be managed or mitigated by planning proper management strategies, such as nature-based green and/or blue solutions in advance, along with proper evaluation of the risk of heat. Since heat stress is more pronounced in urban and built areas, most studies for heatwave risk assessment have been limited to big cities. The risk variation in semi-urban, sub-urban and rural areas has not been much investigated. The heat risk develops with time because of changing climate and socio-demographics, and risk assessment is needed to be done utilising recent data on climate and population characteristics. In this study, the heatwave or extreme hot (99 percentile) temperature risk has been estimated by using statistical approach on summer daily temperature and mortality data from Aberdeenshire and South East (SE) England, UK for the duration 1981-2018. A distributed-lag nonlinear model from Poisson regression family was applied to model the relationship between daily temperature and mortality. We calculated relative risk (RR) and mortality attributable fraction (AF) due to high temperature by comparing the extreme heat with the minimum mortality temperature. AF was calculated by dividing the number of excess deaths due to heat from all the days of the time-series by the total number of deaths. The overall risk in SE England was noted 56 % higher (RR 1.067) than Aberdeenshire (RR 1.043), with 36% more excess death in SE England (AF 0.15% and 0.11% respectively) due to different levels of people’s adaptation and resilience to different climate conditions. The outcome of this study can help in site focused mitigation strategies to certain areas at most risk and develop a scientific framework for early warning, planning and managing the health impacts of heatwave in more rustic regions.
Under climate change scenarios, it is important to evaluate the changes in recent behavior of heavy precipitation events, the resulting flood risk, and the detrimental impacts of the peak flow of water on human well-being, properties, infrastructure, and the natural environment. Normally, flood risk is estimated using the stationary flood frequency analysis technique. However, a site’s hydroclimate can shift beyond the range of historical observations considering continuing global warming. Therefore, flood-like distributions capable of accounting for changes in the parameters over time should be considered. The main objective of this study is to apply non-stationary flood frequency models using the generalized extreme value (GEV) distribution to model the changes in flood risk under two scenarios: (1) without nature-based solutions (NBS) in place and; (2) with NBS i.e. wetlands, retention ponds and weir/low head dam implemented. In the GEV model, the first two moments i.e. location and scale parameters of the distribution were allowed to change as a function of time-variable covariates, estimated by maximum likelihood. The methodology is applied to OPEn-air laboRAtories for Nature baseD solUtions to Manage hydro-meteo risks, which is in Europe. The time-dependent 100-year design quantiles were estimated for both the scenarios. We obtained daily precipitation data of climate models from the EURO-CORDEX project dataset for 1951–2020 and 2022–2100 representing historical and future simulations, respectively. The hydrologic model, HEC-HMS was used to simulate discharges/flood hydrograph without and with NBS in place for these two periods: historical (1951-2020) and future (2022-2100). The results showed that the corresponding time-dependent 100-year floods were remarkably high for the without NBS scenario in both the periods. Particularly, the high emission scenario (RCP 8.5) resulted in dramatically increased flood risks in the future. The simulation without NBS also showed that flooded area is projected to increase by 25% and 40% for inundation depth between 1.5 and 3.5 m under RCP 4.5 and RCP 8.5 scenarios, respectively. For inundation depth above 3.5 m, the flooded area is anticipated to rise by 30% and 55% in both periods respectively. With the implementation of NBS, the flood risk was projected to decrease by 20% (2022–2050) and 45% (2071–2100) with a significant decrease under RCP 4.5 and RCP 8.5 scenarios. This study can help improve existing methods to adapt to the uncertainties in a changing environment, which is critical to develop climate-proof NBS and improve NBS planning, implementation, and effectiveness assessment.
The COVID-19 pandemic elicited a global response to limit associated mortality, with social distancing and lockdowns being imposed. In India, human activities were restricted from late March 2020. This ‘anthropogenic emissions switch-off’ presented an opportunity to investigate impacts of COVID-19 mitigation measures on ambient air quality in five Indian cities (Chennai, Delhi, Hyderabad, Kolkata, and Mumbai), using in-situ measurements from 2015 to 2020. For each year, we isolated, analysed and compared fine particulate matter (PM2.5) concentration data from 25 March to 11 May, to elucidate the effects of the lockdown. Like other global cities, we observed substantial reductions in PM2.5 concentrations, from 19 to 43% (Chennai), 41–53 % (Delhi), 26–54 % (Hyderabad), 24–36 % (Kolkata), and 10–39 % (Mumbai). Generally, cities with larger traffic volumes showed greater reductions. Aerosol loading decreased by 29 % (Chennai), 11 % (Delhi), 4% (Kolkata), and 1% (Mumbai) against 2019 data. Health and related economic impact assessments indicated 630 prevented premature deaths during lockdown across all five cities, valued at 0.69 billion USD. Improvements in air quality may be considered a temporary lockdown benefit as revitalising the economy could reverse this trend. Regulatory bodies must closely monitor air quality levels, which currently offer a baseline for future mitigation plans.
Nature-based solutions (NBS) are being promoted as adaptive measures against predicted increasing hydrometeorological hazards (HMHs), such as heatwaves and floods which have already caused significant loss of life and economic damage across the globe. However, the underpinning factors such as policy framework, end-users' interests and participation for NBS design and operationalisation are yet to be established. We discuss the operationalisation and implementation processes of NBS by means of a novel concept of Open-Air Laboratories (OAL) for its wider acceptance. The design and implementation of environmentally, economically, technically and socio-culturally sustainable NBS require inter- and transdisciplinary approaches which could be achieved by fostering co-creation processes by engaging stakeholders across various sectors and levels, inspiring more effective use of skills, diverse knowledge, manpower and resources, and connecting and harmonising the adaptation aims. The OAL serves as a benchmark for NBS upscaling, replication and exploitation in policy-making process through monitoring by field measurement, evaluation by key performance indicators and building solid evidence on their short- and long-term multiple benefits in different climatic, environmental and socio-economic conditions, thereby alleviating the challenges of political resistance, financial barriers and lack of knowledge. We conclude that holistic management of HMHs by effective use of NBS can be achieved with standard compliant data for replicating and monitoring NBS in OALs, knowledge about policy silos and interaction between research communities and end-users. Further research is needed for multi-risk analysis of HMHs and inclusion of NBS into policy frameworks, adaptable at local, regional and national scales leading to modification in the prevalent guidelines related to HMHs. The findings of this work can be used for developing synergies between current policy frameworks, scientific research and practical implementation of NBS in Europe and beyond for its wider acceptance.
The adoption of Nature-Based Solutions (NBSs) represents a novel means to mitigate natural hazards. In the framework of the OPERANDUM project, this study introduces a methodology to assess the efficiency of the NBSs and a series of Open-Air Laboratories (OALs) regarded as a proof-of-concept for the wider uptake of NBSs. The OALs are located in Finland, Greece, UK, Italy, and Ireland. The methodology is based on a wide modeling activity, incorporated in the context of future climate scenarios. Herein, we present a series of models’ chains able to estimate the efficiency of the NBSs. While the presented models are mainly well-established, their coupling represents a first fundamental step in the study of the long-term efficacy and impact of the NBSs. In the selected sites, NBSs are utilized to cope with distinct natural hazards: floods, droughts, landslides, salt intrusion, and nutrient and sediment loading. The study of the efficacy of NBSs to mitigate these hazards belongs to a series of works devoted to the implementation of NBSs for environmental purposes. Our findings prove that land management plays a crucial role in the process. Specifically, the selected NBSs include intensive forestry; the conversion of urban areas to grassland; dunes; marine seagrass; water retention ponds; live cribwalls; and high-density plantations of woody vegetation and deep-rooted herbaceous vegetation. The management of natural resources should eventually consider the effect of NBSs on urban and rural areas, as their employment is becoming widespread.
To bring to fruition the capability of nature-based solutions (NBS) in mitigating hydro-meteorological risks (HMRs) and facilitate their widespread uptake require a consolidated knowledge-base related to their monitoring methods, efficiency, functioning and the ecosystem services they provide. We attempt to fill this knowledge gap by reviewing and compiling the existing scientific literature on methods, including ground-based measurements (e.g. gauging stations, wireless sensor network) and remote sensing observations (e.g. from topographic LiDAR, multispectral and radar sensors) that have been used and/or can be relevant to monitor the performance of NBS against five HMRs: floods, droughts, heatwaves, landslides, and storm surges and coastal erosion. These can allow the mapping of the risks and impacts of the specific hydro-meteorological events. We found that the selection and application of monitoring methods mostly rely on the particular NBS being monitored, resource availability (e.g. time, budget, space) and type of HMRs. No standalone method currently exists that can allow monitoring the performance of NBS in its broadest view. However, equipments, tools and technologies developed for other purposes, such as for ground-based measurements and atmospheric observations, can be applied to accurately monitor the performance of NBS to mitigate HMRs. We also focused on the capabilities of passive and active remote sensing, pointing out their associated opportunities and difficulties for NBS monitoring application. We conclude that the advancement in airborne and satellite-based remote sensing technology has signified a leap in the systematic monitoring of NBS performance, as well as provided a robust way for the spatial and temporal comparison of NBS intervention versus its absence. This improved performance measurement can support the evaluation of existing uncertainty and scepticism in selecting NBS over the artificially built concrete structures or grey approaches by addressing the questions of performance precariousness. Remote sensing technical developments, however, take time to shift toward a state of operational readiness for monitoring the progress of NBS in place (e.g. green NBS growth rate, their changes and effectiveness through time). More research is required to develop a holistic approach, which could routinely and continually monitor the performance of NBS over a large scale of intervention. This performance evaluation could increase the ecological and socio-economic benefits of NBS, and also create high levels of their acceptance and confidence by overcoming potential scepticism of NBS implementations.
Global warming induced climate change is bringing periods of extremely hot summer days called heatwaves across the world. Its frequency, intensity and magnitude have escalated multifold in recent decades and have been predicted to keep intensifying. Many past studies have only focused on cities for heatwave risk assessment overlooking the risks in suburban and rural areas. The aim of this work is to form a scientific framework for preparing and managing the human-health impacts of heatwaves in more pastoral regions. We associated the extreme temperature with mortality to evaluate its risk using recent data on daily-deaths and maximum temperature from nine counties of southeast England for the period of 1981-2014. The reproduced methodology will also be applied to OPERANDUM project’s test regions called open-air laboratories across Europe. The relationship between temperature and daily-deaths has been examined using a poisson regression model combined with a distributed-lag nonlinear model (DLNM). We computed the absolute excess (numbers) and relative excess (fraction) deaths owed to temperature or relative risk (RR) of mortality by comparing the extremely hot temperature (99th percentile) with the minimum mortality temperature (MMT). Total heat ascribed mortality is given by the sum of the contributions from all the days of the time-series, and its ratio with the total number of deaths. Significant and non-linear associations between temperature and daily-deaths were noticed. The overall cumulative RR at the extremely hot vs. MMT was 1.292 (95% CI: 1.251–1.333). The results of this study can help in location-centric heat management action plans to certain areas at most risk.
Droughts are comprehensive and complex naturally occurring hazards in any climatic region around the world and often result in the loss of life and severe ecosystem damage. Drought monitoring is usually based on single-variables that may not represent the corresponding risk appropriately to its multiple causation and impact characteristics under current and future climate scenarios. In order to address this issue, the multidimensional copulas function, which is a flexible statistical tool, could be applied to develop multivariate drought indicators and solve the complicated and nonlinear associations. The aim of this paper is to develop reliable designing, monitoring and prediction indicators for the proper assessment and intervention of drought risk by nature-based solutions (NBS). Using a copula-based multivariate drought indicator (CMDI) that considers all possible variables related to meteorological, agricultural and hydrological droughts is essential for better drought risk assessment and intervention. The CMDI was developed by integrating univariate marginal cumulative distribution functions of meteorological (precipitation), agricultural (soil moisture) and hydrological (streamflow) variables into their joint cumulative distribution function. CMDI was then applied to the selected study catchment (Po Valley, Italy and Spercheios River, Greece) using hydro-meteorological data from gauging stations and ERA5 gridded data for the period 1979-2017. The result of CMDI showed moderate, severe and extreme drought frequencies in the two selected catchments. The constructed CMDI captured more severe to extreme drought occurrence than the considered single drought indicators. This proved that the CMDI could appropriately represent the complex and interrelated natural variables. The uncertainty analysis based on Monte Carlo experiments confirmed that CMDI is a more robust and reliable approach for assessing, planning and designing a nature-based intervention for drought risk. The findings of this research can provide a reliable way to develop approaches that can be used for assessing and predicting non-linearly related variables or any risk that may occur simultaneously or cumulatively over time.
The impact of weather- and climate-related hydro-meteorological hazards (HMHs) is amongst the greatest global challenges society is facing today. The concept of nature-based solution (NBS) is becoming popular for HMH management but the lack of knowledge on NBS designing and effectiveness is hindering its wider acceptance. This work discusses HMH risk analysis, relevant data, the role of NBS and its operationalisation by bringing co-design concept and testing them in OPERANDUM project’s open-air laboratories (OALs). HMH risk assessment employs different methodologies with respect to exposure, vulnerability and adaptation interaction of the elements at risk. The classification and effectiveness of any NBS depend on its location, design, typology and environmental conditions. OALs, via the collaboration of researchers and end-users, can foster increasing uptake, upscaling, replication and implementation of NBS projects as compared to traditional grey infrastructure approach. Multi-hazard risk analysis and inclusion of NBS into policy plans can foster NBS operationalisation processes across all sectors and at levels by fostering participatory processes such as co-design, co-creation and co-management among municipalities, researches, policy-makers, funding agencies and other stakeholders; and can inspire more effective use of skills, knowledge, manpower, as well as economic, social and cultural resources. NBS data monitoring, its standardisation, accessible storage and compliance with existing standard metadata is needed. The monitoring and evaluation manuals and guidelines are needed to decrease uncertainty about performance and overall cost-effectiveness of NBS and overcome potential hurdles to create long-term stability and enhance the wider uptake of NBS.
Nature-based solutions (NBS) are increasingly being implemented as suitable approaches for reducing vulnerability and risk of social-ecological systems (SES) to hydro-meteorological hazards. Understanding vulnerability and risk of SES is crucial in order to design and implement NBS projects appropriately. A systematic literature review was carried out to examine the suitability of, or gaps in, existing frameworks for vulnerability and risk assessment of SES to hydro-meteorological hazards. The review confirms that very few frameworks have been developed in the context of NBS. Most of the frameworks have emphasised social systems over ecological systems. Furthermore, they have not explicitly considered the temporal dimension of risk reduction measures. The study proposes an indicator-based vulnerability and risk assessment framework in the context of NBS (VR-NBS) that addresses both the above limitations and considers established NBS principles. The framework aims to allow for a better consideration of the multiple benefits afforded by NBS and which impact all the dimensions of risk. A list of 135 indicators is identified through literature review and surveys in NBS project sites. This list is composed of indicators representing the social sub-system (61% of total indicators) and the ecological sub-system (39% of total indicators). The list will act as a reference indicator library in the context of NBS projects and will be regularly updated as lessons are learnt. While the proposed VR-NBS framework is developed considering hydro-meteorological hazards and NBS, it can be adapted for other natural hazards and different types of risk reduction measures.
Nature-based solutions (NBS) for hydro-meteorological risks (HMRs) reduction and management are becoming increasingly popular, but challenges such as the lack of well-recognised standard methodologies to evaluate their performance and upscale their implementation remain. We systematically evaluate the current state-of-the art on the models and tools that are utilised for the optimum allocation, design and efficiency evaluation of NBS for five HMRs (flooding, droughts, heatwaves, landslides, and storm surges and coastal erosion). We found that methods to assess the complex issue of NBS efficiency and cost-benefits analysis are still in the development stage and they have only been implemented through the methodologies developed for other purposes such as fluid dynamics models in micro and catchment scale contexts. Of the reviewed numerical models and tools MIKE-SHE, SWMM (for floods), ParFlow-TREES, ACRU, SIMGRO (for droughts), WRF, ENVI-met (for heatwaves), FUNWAVE-TVD, BROOK90 (for landslides), TELEMAC and ADCIRC (for storm surges) are more flexible to evaluate the performance and effectiveness of specific NBS such as wetlands, ponds, trees, parks, grass, green roof/walls, tree roots, vegetations, coral reefs, mangroves, sea grasses, oyster reefs, sea salt marshes, sandy beaches and dunes. We conclude that the models and tools that are capable of assessing the multiple benefits, particularly the performance and cost-effectiveness of NBS for HMR reduction and management are not readily available. Thus, our synthesis of modelling methods can facilitate their selection that can maximise opportunities and refute the current political hesitation of NBS deployment compared with grey solutions for HMR management but also for the provision of a wide range of social and economic co-benefits. However, there is still a need for bespoke modelling tools that can holistically assess the various components of NBS from an HMR reduction and management perspective. Such tools can facilitate impact assessment modelling under different NBS scenarios to build a solid evidence base for upscaling and replicating the implementation of NBS. [Display omitted]
Hydro-meteorological hazards (HMHs) have had a strong impact on human societies and ecosystems. Their impact is projected to be exacerbated by future climate scenarios. HMHs cataloguing is an effective tool to evaluate their associated risks and plan appropriate remediation strategies. However, factors linked to HMHs origin and triggers remain uncertain, which poses a challenge for their cataloguing. Focusing on key HMHs (floods, storm surge, landslides, droughts, and heatwaves), the goal of this review paper is to analyse and present a classification scheme, key features, and elements for designing nature-based solutions (NBS) and mitigating the adverse impacts of HMHs in Europe. For this purpose, we systematically examined the literature on NBS classification and assessed the gaps that hinder the widespread uptake of NBS. Furthermore, we critically evaluated the existing literature to give a better understanding of the HMHs drivers and their interrelationship (causing multi-hazards). Further conceptualisation of classification scheme and categories of NBS shows that relatively few studies have been carried out on utilising the broader concepts of NBS in tackling HMHs and that the classification and effectiveness of each NBS are dependent on the location, architecture, typology, green species, environmental conditions as well as interrelated non-linear systems. NBS are often more cost-effective than hard engineering approaches used within the existing systems, especially when taking into consideration their potential co-benefits. We also evaluated the sources of available data for HMHs and NBS, highlighted gaps in data, and presented strategies to overcome the current shortcomings for the development of the NBS for HMHs. We highlighted specific gaps and barriers that need to be filled since the uptake and upscaling studies of NBS in HMHs reduction is rare. The fundamental concepts and the key technical features of past studies reviewed here could help practitioners to design and implement NBS in a real-world situation.
Hydro-meteorological risk (HMR) management involves a range of methods, such as monitoring of uncertain climate, planning and prevention by technical countermeasures, risk assessment, preparedness for risk by early-warnings, spreading knowledge and awareness, response and recovery. To execute HMR management by risk assessment, many models and tools, ranging from conceptual to sophisticated/numerical methods are currently in use. However, there is still a gap in systematically classifying and documenting them in the field of disaster risk management. This paper discusses various methods used for HMR assessment and its management via potential nature-based solutions (NBS), which are actually lessons learnt from nature. We focused on three hydro-meteorological hazards (HMHs), floods, droughts and heatwaves, and their management by relevant NBS. Different methodologies related to the chosen HMHs are considered with respect to exposure, vulnerability and adaptation interaction of the elements at risk. Two widely used methods for flood risk assessment are fuzzy logic (e.g. fuzzy analytic hierarchy process) and probabilistic methodology (e.g. univariate and multivariate probability distributions). Different kinds of indices have been described in the literature to define drought risk, depending upon the type of drought and the purpose of evaluation. For heatwave risk estimation, mapping of the vulnerable property and population-based on geographical information system is a widely used methodology in addition to a number of computational, mathematical and statistical methods, such as principal component analysis, extreme value theorem, functional data analysis, the Ornstein–Uhlenbeck process and meta-analysis. NBS (blue, green and hybrid infrastructures) are promoted for HMR management. For example, marshes and wetlands in place of dams for flood and drought risk reduction, and green infrastructure for urban cooling and combating heatwaves, are potential NBS. More research is needed into risk assessment and management through NBS, to enhance its wider significance for sustainable living, building adaptations and resilience.