Impacts of climate change on water resources in the Yellow River basin and identification of global adaptation strategies

Climate change is a global environmental issue, which is challenging water resources management and practices. This study investigates the impact of climate change on water resources of the Yellow River basin, a major grain-producing area in China, and provides recommendations on strategies to increase adaptive capacity and resilience in the basin region. Results show that the recorded stream flows of the Yellow River declined from 1951 to 2010 and have decreased significantly in the middle and lower reaches. The variable infiltration capacity (VIC) model performs well as a tool to simulate monthly discharge of both the tributary catchments and the whole Yellow River basin. Temperature across the Yellow River basin over 2021–2050 is expected to continue to rise with an average rates of approximately 0.039–0.056 °C/annum. The average annual precipitation in the basin is projected to increase by 1.28–3.29 % compared with the 1991–2010 baseline. Runoff during 2021–2050 is projected to decrease by 0.53–9.67 % relative to 1991–2010 with high decadal and spatial variability. This is likely due to the model’s projections of a significant rise in temperature and changes in precipitation patterns. Climate change will likely aggravate the severity and frequency of both water shortages and flooding in the basin region. It is therefore essential to devote sufficient attention on structural and non-structural measures for the Yellow River basin to cope with climate change. At the global level, strategies to increase adaptive capacity and build resilience to climate change focus on public education to improve awareness of climate risks, implementing the integrated water resources management and planning based on impact assessments.     

Re-thinking water policy priorities in the Mediterranean region in view of climate change

Water is scarce in Mediterranean countries: cities are crowded with increasing demand; food is produced with large amounts of water; ecosystems demand more water that is often available; drought affects all. As climate change impacts become more noticeable and costlier, some current water management strategies will not be useful. According to the findings of CIRCE, the areas with limited water resources will increase in the coming decades with major consequences for the way we produce food and we protect ecosystems. Based on these projections this paper discusses water policy priorities for climate change adaptation in the Mediterranean. We first summarise the main challenges to water resources in Mediterranean countries and outline the risks and opportunities for water under climate change based on previous studies. Recognising the difficulty to go from precipitation to water policy, we then present a framework to evaluate water availability in response to natural and management conditions, with an example of application in the Ebro basin that exemplifies other Mediterranean areas. Then we evaluate adaptive capacity to understand the ability of Mediterranean countries to face, respond and recover from climate change impacts on water resources. Social and economic factors are key drivers of inequality in the adaptive capacity across the region. Based on the assessment of impacts and adaptive capacity we suggest thresholds for water policy to respond to climate change and link water scarcity indicators to relevant potential adaptation strategies. Our results suggest the need to further prioritise socially and economically sensitive policies.     

Future production of rainfed wheat in Iran (Khorasan province): climate change scenario analysis

Projecting staple crop production including wheat under future climate plays a fundamental role in planning the required adaptation and mitigation strategies for climate change effects especially in developing countries. The main aim of this study was to investigate the direction and magnitude of climate change impacts on grain yield of rainfed wheat (Triticum aestivum L.) production and precipitation within growing season. This study was performed for various regions in Khorasan province which is located in northeast of Iran. Climate projections of two General Circulation Models (GCM) for four locations under three climate change scenarios were employed in this study for different future time periods. A stochastic weather generator (LARS-WG5) was used for downscaling to generate daily climate parameters from GCMs output. The Decision Support System for Agrotechnology Transfer (DSSAT) Version 4.5 was employed to evaluate rainfed wheat performance under future climate. Grain yield of rainfed wheat and precipitation during growth period considerably decreased under different scenarios in various time periods in contrast to baseline. Highest grain yield and precipitation during growth period was obtained under B1 scenario but A1B and A2 scenarios resulted in sharp decrease (by ?57 %) of grain yield. Climate change did not have marked effects on evapotranspiration during the rainfed wheat growth. A significant correlation was detected between grain yield, precipitation and evapotranspiration under climate change for both GCMs and under all study scenarios. It was concluded, that rainfed wheat production may decline during the next 80 years especially under A2 scenario. Therefore, planning the comprehensive adaptation and mitigation program is necessary for avoiding climate change negative impact on rainfed wheat production.     

Application of real option analysis for planning under climate change uncertainty: a case study for evaluation of flood mitigation plans in Korea

With concerns regarding global climate change increasing, recent studies on adapting to nonstationary climate change recommended a different planning strategy that could spread risks. Uncertainty in global climate change should be considered in any decision-making processes for flood mitigation strategies, especially in areas within a monsoon climate regime. This study applied a novel planning method called real option analysis (ROA) to an important water resources planning practice in Korea. The proposed method can easily be applied to other watersheds that are threatened by flood risk under climate change. ROA offers flexibility for decision-makers to reflect uncertainty at every stage during the project planning period. We successfully implemented ROA using a binomial tree model, including two real options—delay and abandon—to evaluate flood mitigation alternatives for the Yeongsan River Basin in Korea. The priority ranking of the four alternatives between the traditional discount cash flow (DCF) and ROA remained the same; however, two alternatives that were assessed as economically infeasible using DCF, were economically feasible using ROA. The binomial decision trees generated in this study are expected to be informative for decision-makers to conceptualize their adaptive planning procedure.     

Adaptive management of marine mega-fauna in a changing climate

Management of marine mega-fauna in a changing climate is constrained by a series of uncertainties, often related to climate change projections, ecological responses, and the effectiveness of strategies in alleviating climate change impacts. Uncertainties can be reduced over time through adaptive management. Adaptive management is a framework for resource conservation that promotes iterative learning-based decision making. To successfully implement the adaptive management cycle, different steps (planning, designing, learning and adjusting) need to be systematically implemented to inform earlier steps in an iterative way. Despite the critical role that adaptive management is likely to play in addressing the impacts of climate change on marine mega-fauna few managers have successfully implemented an adaptive management approach. We discuss the approaches necessary to implement each step of an adaptive management cycle to manage marine mega-fauna in a changing climate, highlighting the steps that require further attention to fully implement the process. Examples of sharks and rays (Selachimorpha and Batoidea) on the Great Barrier Reef and little penguins, Eudyptula minor, in south-eastern Australia are used as case studies. We found that successful implementation of the full adaptive management cycle to marine mega-fauna needs managers and researchers to: (1) obtain a better understanding of the capacity of species to adapt to climate change to inform the planning step; (2) identify strategies to directly address impacts in the marine environment to inform the designing step; and (3) develop systematic evaluation and monitoring programs to inform the learning step. Further, legislation needs to flexible to allow for management to respond.     

Assessing high impacts of climate change: spatial characteristics and relationships of hydrological ecosystem services in northern Japan (Teshio River watershed)

Ecosystem services (ESs) provide information on the tendency of ecosystems to reach and form a state of equilibrium. The process of ES changes is important in order to identify the climate change-related causes that occur regionally to globally. ES-based management plays an important role in mitigation strategies for the negative impact of global climate change on ecosystem. Therefore, it is necessary to evaluate spatial characteristics and relationships among these multiple services from different spatial scales which could aid in multiple ES sustainable development from local to global scales. In this study, we developed a framework for analyzing the spatial characteristics and interactive relationships of multiple ESs. We analyzed the spatial distributions of six hydrological ESs that are important in the northernmost part of Japan (Teshio River watershed) by using hydrology and nutrient model (Soil and Water Assessment Tool, SWAT) under baseline climate conditions and climate change derived from the global circulation model (GCM). We then explored the spatial characteristic scales of ESs by multiscale analysis (lacunarity estimation) to reveal provision flow and spatial distribution characteristics for hydrological ESs. We observed a strong relationship between the spatial characteristics of land uses and ES provision. The spatial characteristics of individual hydrological ESs were totally different and had different spatial homogeneity and cluster (indicated by initial lacunarity index and lacunarity dimension). The results also showed trade-offs between inorganic nutrient retention (provision ESs) and organic nutrient and sediment retentions (regulating ESs), and synergies between organic nutrient retention and sediment retention under all climate change scenarios. The different stakeholders will take different mitigation programs (e.g., establishing riparian vegetation, planning nutrient management practices, and integrating climate change model into systematic conservation planning of ESs) to avoid negative impacts of climate change on ESs. Application of this proposed framework to study the spatial characteristics and relationships of hydrological ESs under climate change could provide understanding on the impact of climate change on ES changes and solutions to mitigate strategies to cope with those changes in the future.     

全球增温1.5℃和2.0℃对淮河中上游径流影响预估

论文应用第5次耦合模式比较计划(Coupled Model Intercomparison Project Phase 5,CMIP5)中5个全球气候模式(Global Climate Models,GCMs)和3种典型浓度路径(Representative Concentration Pathways,RCPs)在全球增温1.5℃和2.0℃下的预估结果,分析了淮河中上游地区未来的气候变化特征。进一步基于SWAT(Soil and Water Assessment Tool)水文模型定量预估了气候变化对该区域径流量的影响,并量化了预估结果的不确定性。结果表明:SWAT模型在淮河中上游对月径流量具有较好的模拟能力。在全球增温1.5℃和2.0℃下,淮河中上游年平均气温分别较基准期(1986—2005年)增加1.1℃和1.7℃;年降水量较基准期分别相应增加4%和7%;基于SWAT模型预估的年径流量较基准期分别增加5%和8%。未来气候变化不会改变月径流分布特征,年内径流仍集中在盛夏和初秋(6—9月)。预估的月丰水流量明显增加,尤其当全球增温达到2.0℃后,出现洪涝的风险明显增大。未来降水量和径流量预估都存在较大的不确定性,不确定性主要来源于GCMs,在全球增温2.0℃下预估的不确定性更大。     

What does it mean when climate models agree? A case for assessing independence among general circulation models

Climate modelers often use agreement among multiple general circulation models (GCMs) as a source of confidence in the accuracy of model projections. However, the significance of model agreement depends on how independent the models are from one another. The climate science literature does not address this. GCMs are independent of, and interdependent on one another, in different ways and degrees. Addressing the issue of model independence is crucial in explaining why agreement between models should boost confidence that their results have basis in reality.     

Groundwater-dependent irrigation costs and benefits for adaptation to global change

The effects of a 1.5 °C global change on irrigation costs and carbon emissions in a groundwater-dependent irrigation system were assessed in the northwestern region of Bangladesh and examined at the global scale to determine possible global impacts and propose necessary adaptation measures. Downscaled climate projections were obtained from an ensemble of eight general circulation models (GCMs) for three representative concentration pathways (RCPs), RCP2.6, RCP4.5, and RCP8.5 and were used to generate the 1.5 °C warming scenarios. A water balance model was used to estimate irrigation demand, a support vector machine (SVM) model was used to simulate groundwater levels, an energy-use model was used to estimate carbon emissions from the irrigation pump, and a multiple linear regression (MLR) model was used to simulate the irrigation costs. The results showed that groundwater levels would likely drop by only 0.03 to 0.4 m under a 1.5 °C temperature increase, which would result in an increase in irrigation costs and carbon emissions ranging from 11.14 to 148.4 Bangladesh taka (BDT) and 0.3 to 4% CO₂ emissions/ha, respectively, in northwestern Bangladesh. The results indicate that the impacts of climate change on irrigation costs for groundwater-dependent irrigation would be negligible if warming is limited to 1.5 °C; however, increased emissions, up to 4%, from irrigation pumps can have a significant impact on the total emissions from agriculture. This study revealed that similar impacts from irrigation pumps worldwide would result in an increase in carbon emissions by 4.65 to 65.06 thousand tons, based only on emissions from groundwater-dependent rice fields. Restricting groundwater-based irrigation in regions where the groundwater is already vulnerable, improving irrigation efficiency by educating farmers and enhancing pump efficiency by following optimum pumping guidelines can mitigate the impacts of climate change on groundwater resources, increase farmers’ profits, and reduce carbon emissions in regions with groundwater-dependent irrigation.     

Integrated scenario modelling of energy,greenhouse gas emissions and forestry

Preventing dangerous climate change requires actions on several sectors. Mitigation strategies have focused primarily on energy, because fossil fuels are the main source of global anthropogenic greenhouse gas emissions. Another important sector recently gaining more attention is the forest sector. Deforestation is responsible for approximately one fifth of the global emissions, while growing forests sequester and store significant amounts of carbon. Because energy and forest sectors and climate change are highly interlinked, their interactions need to be analysed in an integrated framework in order to better understand the consequences of different actions and policies, and find the most effective means to reduce emissions. This paper presents a model, which integrates energy use, forests and greenhouse gas emissions and describes the most important linkages between them. The model is applied for the case of Finland, where integrated analyses are of particular importance due to the abundant forest resources, major forest carbon sink and strong linkage with the energy sector. However, the results and their implications are discussed in a broader perspective. The results demonstrate how full integration of all net emissions into climate policy could increase the economic efficiency of climate change mitigation. Our numerical scenarios showed that enhancing forest carbon sinks would be a more cost-efficient mitigation strategy than using forests for bioenergy production, which would imply a lower sink. However, as forest carbon stock projections involve large uncertainties, their full integration to emission targets can introduce new and notable risks for mitigation strategies.     

气候变化对湿地景观格局的影响研究综述

气候变化是影响湿地景观格局变化的主要自然因素。文章从气候变化对湿地水资源面积、湿地土地利用格局、湿地植被空间格局及湿地生物多样性格局的影响研究等方面进行了综述,并对完善气候变化下湿地景观格局变化的研究方法和技术手段进行了探讨。指出:应用气候模型进行未来气候预测时,应合理选择气候变化情景,并确保不同模型的时空尺度匹配;应用"3S"技术提取湿地类型信息、观测湿地土地覆盖变化时要确保信息的精度,不同来源的数据必须采取制图综合等手段;实现气候变化下湿地景观结构与生态过程相结合的动态格局分析。     

Vulnerability of agro-ecological zones in India under the earth system climate model scenarios

India being a developing economy dependent on climate-sensitive sector like agriculture is highly vulnerable to impacts of global climate change. Vulnerability to climate change, however, differs spatially within the country owing to regional differences in exposure, sensitivity, and adaptive capacity. The study uses the Hadley Centre Global Environment Model version 2-Earth System (HadGEM-ES) climate projections to assess the dynamics in vulnerability across four climate change exposure scenarios developed using Representative Concentration Pathways (RCPs). The analysis was carried out at subnational (district) level; the results were interpreted and reported for their corresponding agro-ecological zones. Vulnerability of each district was quantified using indicators capturing climatic variability, ecological and demographic sensitivity, and socio-economic capacity. Our analysis further assigns probabilities to vulnerability classes of all the 579 districts falling under different agro-ecological zones. The results of the vulnerability profile show that Western plains, Northern plains, and central highlands of the arid and semi-arid agro-ecological zones are the most vulnerable regions in the current scenario (1950–2000). In the future scenario (2050), it extends along districts falling within Deccan plateau and Central (Malwa) highlands, lying in the arid and semi-arid zones, along with regions vulnerable in the current scenario, recording the highest vulnerability score across all exposure scenarios. These regions exhibit highest degree of variation in climatic parameters, ecological fragility, socio-economic marginality, and limited accessibility to resources, generating conditions of high vulnerability. The study emphasizes on the priority to take up adaptive management actions in the identified vulnerable districts to not only reduce risks of climate change, but also enhance their inherent capacity to withstand any future changes in climate. It provides a systematic approach to explicitly identify vulnerable regions, where regional planners and policy makers can build on existing adaptation decision-making by utilizing an interdisciplinary approach in the context of global change scenario.     

Estimating the non-market benefits of climate change adaptation of river ecosystem services: A choice experiment application in the Aoos basin,Greece

Mountains are important global reservoirs of water resources. However they are highly vulnerable to climate change as limited alterations in temperature and precipitation may cause harmful effects to water systems. Southern Europe and especially Greece are expected to undergo a drought trend over the next decades, resulting in less recharge for the aquifers and water services reduction. Thus, climate change may distort both natural and socioeconomic characteristics of freshwater ecosystem services deteriorating the general social welfare related to them. This paper examines the economic impacts of climate change on river uses of the Aoos basin in Greece. In this regard, a choice experiment is conducted to estimate the value changes in different ecological and economic services in a mountain community. The econometric simulations using conditional logit, random parameters logit and latent class models reveal that despite existing preference heterogeneity, respondents on average derive positive and significant welfare effects from climate change adaptation measures. The findings of the survey may assist in adaptation planning for the Aoos River basin, with possible extensions to other river systems enduring similar climate change indications.     

基于不确定性的水资源优化配置模型及其实证研究

针对城市水资源系统中存在的不确定性,将可信性模糊机会约束规划模型与区间规划相结合,提出了不确定环境下的可信性模糊-区间线性规划(FILP)模型,将其应用于某城市水资源优化配置与科学管理中,构建了城市水资源优化配置FILP模型.该模型以城市的经济、社会与环境的可持续发展为目标,以供需水量等为不确定性约束,以各水源在各子区不同部门间的分配为决策变量,利用改进的风险显性区间规划算法进行求解得到一定置信度和意愿水平下的水资源优化配置风险-收益权衡方案.实证研究表明,该模型反映了不确定性因素对水资源系统收益的影响,能够为实际的优化决策提供方法支持.     

Assessing high-impact spots of climate change: spatial yield simulations with Decision Support System for Agrotechnology Transfer (DSSAT) model

Drybeans (Phaseolus vulgaris L.) are an important subsistence crop in Central America. Future climate change may threaten drybean production and jeopardize smallholder farmers’ food security. We estimated yield changes in drybeans due to changing climate in these countries using downscaled data from global circulation models (GCMs) in El Salvador, Guatemala, Honduras, and Nicaragua. We generated daily weather data, which we used in the Decision Support System for Agrotechnology Transfer (DSSAT) drybean submodel. We compared different cultivars, soils, and fertilizer options in three planting seasons. We analyzed the simulated yields to spatially classify high-impact spots of climate change across the four countries. The results show a corridor of reduced yields from Lake Nicaragua to central Honduras (10–38 % decrease). Yields increased in the Guatemalan highlands, towards the Atlantic coast, and in southern Nicaragua (10–41 % increase). Some farmers will be able to adapt to climate change, but others will have to change crops, which will require external support. Research institutions will need to devise technologies that allow farmers to adapt and provide policy makers with feasible strategies to implement them.     

基于SWAT-WEAP联合模型的西辽河支流水资源脆弱性研究

气候变化与人类活动对水循环及水资源安全的影响是近代水科学面临的主要科学问题。以西辽河支流老哈河流域为研究区,探索了一种水文模型耦合方法(SWAT-WEAP),以水短缺量为指标,同等考虑水资源供给端与需求端,对气候变化与不同人类利用情景下水资源系统脆弱性进行定量分析,结果表明:①暖干化气候情景比暖湿化气候情景明显加剧了老哈河流域水资源系统的脆弱性,降水减少10%导致的水短缺量比降水导致10%所缓解的短缺量要多31.17%;②气候变化对流域农业灌溉用水影响最大,对城乡生活用水和工业用水影响相对很小;③老哈河流域水资源系统脆弱性的主要驱动力之一源自农业不合理灌溉,发展畜牧业、 改变种植结构与高效节水灌溉是缓解水短缺、 降低水资源系统脆弱性最为有效的措施,也是应对气候变化最为有效的方式;④基于供水端的措施(如水库)在暖干化气候时由于水资源供给来源受限,其缓解作用有所减弱。     

SPARROW模型在水环境管理中的应用及发展趋势

模型是研究水环境变化、进行水环境管理的重要工具.SPARROW（spatially referenced regressions on watershed attributes）是一个基于质量平衡方法将监测数据与流域特征和污染物来源信息相关联的非线性流域回归模型,具有数据需求量少、结构透明、普适性强等优点.为深刻理解SPARROW模型在水环境管理中的应用现状及未来发展趋势,笔者对SPARROW模型的原理以及其在营养物背景浓度模拟、水质评价、水质目标管理、气候变化对水环境影响等方面应用的国内外研究现状进行了系统梳理.结果表明:①通过选择合适的参考点,SPARROW模型可以有效模拟流域背景营养物通量和浓度,为流域水质标准的制定提供参照依据.②SPARROW模型可将营养物监测获得的数据信息外推至未监测区域,在水质监测数据数量有限的情况下进行水质评价.③SPARROW模型可模拟不同土地使用条件、资源管理等情境下河流营养物负荷,为水质的管理与决策提供支撑.④气候变化情景下,基于SPARROW模型进行气候变化对水环境影响的研究可以支撑水环境管理方案的制定,以应对未来气候变化导致的营养物输出增加.针对SPARROW模型目前在应用中存在的问题进行了分析与讨论,建议未来在应用SPARROW模型时,加强以下几个方面的研究:①进一步开发高锰酸盐指数、化学需氧量（COD）、氨氮等相关模块;②将SPARROW模型与机器学习模型相结合,提高量化模型参数的能力,使模型更好地应用于不同尺度、不同流域的水质相关研究.      

Modeling of the Mendoza river watershed as a tool to study climate change impacts on water availability

Unmitigated anthropogenic climate change is set to exacerbate current stresses on water resources management and creates the need to develop strategies to face climate change impacts on water resources, especially in the long term. Insufficient information on possible impacts on water availability limits the organization and promotion of efforts to adapt and improve the resilience and efficiency of water systems. To document the potential impacts of climate change in the region of Mendoza, Argentina, we perform a hydrological modeling of the Mendoza River watershed using a SWAT model and project climate change scenarios to observe hydrological changes. The results show the impact of higher temperature on glaciers as river flow increases due to glacier melting; at the same time, runoff decreases as precipitation is reduced. Furthermore, the runoff timing is shifted and an earlier melting becomes more important in more pronounced climate change scenarios. Scenarios show a reduction in water availability that ranges between 1 and 10%. An additional scenario under stronger climate change conditions without glaciers data shows a reduction of the river flow by up to 11.8%. This scenario would correspond to a future situation in which glaciers have completely melted. These situations would imply a reduction in the water availability and the possibility of future unsatisfied water uses, in particular for irrigation, which received most of the available water in Mendoza, on which agricultural activities and regional economy depends.     

Climate change impacts on groundwater resources in Mekong Delta under representative concentration pathways (RCPs) scenarios

Groundwater is the essential resource for various uses and have a great economic importance especially in the areas like Mekong Delta, which is the home for some 18 million people and produces a half of Vietnam’s rice and contributes substantial part of the country’s gross domestic product (GDP). Sustainable use of the groundwater resource is threatened by its uncontrolled abstraction and climate change. This study assesses groundwater resources in Mekong Delta aquifer system in the context of climate change. A set of models are used for the purpose. Groundwater recharge and its spatial variation are estimated using WETSPASS model, groundwater level and storage are estimated using MODFLOW and future climatic conditions in the area are developed by downscaling the data of five General Circulation Models (GCMs) retrieved from CMIP5 data portal. Two representative concentration pathways (RCPs) scenarios (RCP4.5 and RCP8.5) are considered for projecting future conditions of groundwater resources. Results reveal that the future average annual temperature is projected to increase by 1.5 °C and 4.9 °C by the end of the 21st century under RCP4.5 and RCP8.5 scenarios, respectively. Future rainfall is projected to increase in wet season and decrease in dry season. Groundwater recharge is projected to decline in short-, medium-, and long-terms. As a result, groundwater levels and storage are also projected to decline in future. These findings may help decision-makers and stakeholders for devising sustainable groundwater management strategies in Mekong Delta.     

Ecosystem-based adaptation to climate change: defining hotspot municipalities for policy design and implementation in Brazil

We developed an indicator that defines priority municipalities in order to facilitate the deployment of preventive policies and strategies for ecosystem-based adaptation to climate change (EbA) in Brazilian municipalities. Based on the premises that poor people are the population most vulnerable to climate change and that conservation and sustainable use of biodiversity and ecosystems are adaptive to climate change, our indicator uses three parameters: (1) poverty, (2) proportion of natural-vegetation cover, and (3) exposure to climate change. Thus, we searched for Brazilian municipalities that simultaneously belonged to the quartile of municipalities with the highest percentage of poverty, the quartile with the highest percentage of natural-vegetation cover, and the quartile with the highest exposure indices in two global climate models (Eta-HadGEM, Eta-Miroc). We found 398 (7.1%) EbA hotspots among 5565 Brazilian municipalities, which comprise 36% of the total area of native remnants in the country and are home to 22% of the poor people in Brazil. In their majority, these municipalities cover significant portions of the Amazon, Cerrado, Caatinga, and Atlantic forest, and indeed, these regions are recognised as some of the most vulnerable to climate change in the world. Considering the relevance of these biomes for the global water and nutrient cycle (Amazon), global food security (Cerrado), vulnerability to desertification (Caatinga), and biodiversity (all) we discuss the adaptive strategies in place, the need to bring them to scale, and existing policy gaps. Finally, in an effort to guide international and national investment and policies, we discuss how the approach described here can be applied to societies inhabiting tropical forests, savannas, and semiarid zones in other parts of the world. In particular, we propose that the indicator developed here is a simple and fast way to achieve early detection of priority municipalities for deployment of EbA action and policies, particularly in tropical developing countries.