Climate Change Adaptation Research Articles

Supporting justice in Local Government: Climate Response in Aotearoa New Zealand

While climate justice concerns are increasingly incorporated into policy at international scales, there is less research on climate justice and policy at local scales. Recognising how structural inequalities intersect with climate change influences how rights, responsibilities, distribution of resources and procedures for adaptation are understood and implemented. We describe how some local governments in Aotearoa New Zealand are using recognition practices to improve their understanding of the impacts of climate change, and re-allocating resourcing so mana whenua and communities are better able to participate in climate adaptation procedures. We suggest national policy and legislative changes that could support local governments’ climate justice recognition practices.

Climate Adaptation of Roads to Flooding Hazards—A Review

Flooding hazards due to climate change are increasingly becoming a frequent global occurrence. The aim of this study is to provide a comprehensive review of the various structural mitigation and adaptation strategies available to engineers and designers at various stages of road construction and rehabilitation to increase the resilience of roads to flooding damage. The criteria for categorising the various strategies available were the time of intervention with respect to the occurrence of the hazard. Thus, all studied strategies were separated into pre-construction design changes, post-construction mitigation and adaptation options like Sustainable Urban Drainage Systems (SuDS). The main findings were that changing the specifications of commonly used materials can provide increased flood resilience, and a preliminary design for flooding can reduce post-flooding rehabilitation. The study can be used as a guide for the different options available to deliver a design that takes flooding into consideration.

Climate change and its influence on water systems increases the cost of electricity system decarbonization

The electric sector simultaneously faces two challenges: decarbonization to mitigate, and adaptation to manage, the impacts of climate change. In many regions, these challenges are compounded by an interdependence of electricity and water systems, with water needed for hydropower generation and electricity for water provision. Here, we couple detailed water and electricity system models to evaluate how the Western Interconnection grid can both adapt to climate change and develop carbon-free generation by 2050, while accounting for interactions and climate vulnerabilities of the water sector. We find that by 2050, due to climate change, annual regional electricity use could grow by up to 2% from cooling and water-related electricity demand, while total annual hydropower generation could decrease by up to 23%. To adapt, we show that the region may need to build up to 139 GW of additional generating capacity between 2030 and 2050, equivalent to nearly thrice California’s peak demand, and could incur up to $150 billion (+7%) in extra costs.

Variations of riskification: Climate change adaptation in four European cities

AbstractThis study explores the manifestations of riskification in climate change adaptation (CCA) across four European cities, examining the roles of actors, discourses, and tools. Through comparative analysis, it aims to delineate local riskification, identifying similarities and differences among the cases. Three intervening factors – ideational frameworks, organization of government, and actor networks – are assessed to comprehend the amplification or deceleration of riskification processes locally. Findings reveal that ideational frameworks shape responses to climate change challenges within each case, while government organization influences CCA strategies and funding mechanisms. Actor networks play a pivotal role in shaping CCA efforts, including measurement, modeling, and monitoring. Despite commonalities, the analysis revealed that the intervening factors are further conditioned in each specific case, albeit in different ways, by aspects not initially considered: the influence of risk culture, risk memory, and technocratic governance in local CCA in each situation. These nuances produce variations of riskification that are locally distinct but equally depoliticize climate change risks, overshadowing broader societal implications and impeding transformative approaches. In particular, the dominance of riskified CCA approaches with technocratic characteristics and limited urgency may hinder innovative strategies required for addressing complex CCA challenges.

How to account for spatial trade-offs in planning for urban climate adaptation? Optimizing green and grey infrastructures

Urban Nature-Based Solutions have emerged as sound strategies for urban climate change adaptation, but they lack effective decision-support tools. This paper proposes a decision-support framework that relies on Multi-Objective Optimization (MOO), the consideration of actual space availability, the consideration of the simultaneous objectives of climate change adaptation and water management, the integration of demand for co-benefits, and the participatory exploration of trade-offs for decision-makers. The MOO is applied to the case study of the French city of Bordeaux, to identify the optimal location of Groundwater Recharge Infrastructures (GRI) that include Nature-Based Solutions. It provides decision-makers with spatially explicit solutions for developing GRI, with the objectives of maximizing groundwater recharge, maximizing urban cooling, while minimizing opportunity costs, in the context of urban climate change adaptation. Results indicate an array of solutions between two polar strategies: large scale specialized grey solutions in most effective recharge areas, or diffused Nature-Based Solutions to satisfy citizen demand for multiple benefits. The participatory trade-off analysis proposed in this paper is a novel way to co-design spatial climate change adaptation strategies in urban contexts.

Towards Accurate Flood Predictions: A Deep Learning Approach Using Wupper River Data

The increasing frequency and severity of floods due to climate change underscores the need for precise flood forecasting systems. This study focuses on the region surrounding Wuppertal in Germany, known for its high precipitation levels, as a case study to evaluate the effectiveness of flood prediction through deep learning models. Our primary objectives are twofold: (1) to establish a robust dataset from the Wupper river basin, containing over 19 years of time series data from three sensor types such as water level, discharge, and precipitation at multiple locations, and (2) to assess the predictive performance of nine advanced machine learning algorithms, including Pyraformer, TimesNet, and SegRNN, in providing reliable flood warnings 6 to 48 h in advance, based on 48 h of input data. Our models, trained and validated using k-fold cross-validation, achieved high quantitative performance metrics, with an accuracy reaching up to 99.7% and F1-scores up to 91%. Additionally, we analyzed model performance relative to the number of sensors by systematically reducing the sensor count, which led to a noticeable decline in both accuracy and F1-score. These findings highlight critical trade-offs between sensor coverage and predictive reliability. By publishing this comprehensive dataset alongside performance benchmarks, we aim to drive further innovation in flood risk management and resilience strategies, addressing urgent needs in climate adaptation.

Before and after disaster: Homeowner protective actions in a changing climate

Communities face a growing threat from increasingly severe weather events driven by a changing climate. The threat is especially acute in US coastal communities where current regulations have proven ineffective in stemming mounting hurricane losses. Absent meaningful regulatory reforms, climate adaptation in coastal zones will largely depend on the voluntary actions of homeowners. We introduce a novel research methodology to study those actions in a post-hurricane landscape where damage necessitates reconstruction decisions. The methodology includes (1) a modular survey instrument robust enough to document diverse damage experiences and recovery journeys, (2) indices that measure homeowner protective actions over time and holistic damage exposure, and (3) a sampling strategy that uses secondary data to target households likely to be engaged in recovery actions, maximizing yields in settings characterized by low response rates. The efficacy of this research methodology is demonstrated through the study of 373 homeowners in Calcasieu Parish, Louisiana, a community still recovering from Hurricane Laura. On average, homeowners invested in protection before the storm, increased that protection level after the storm, and intend to continue to invest in protections for their homes. However, despite homeowners’ promising actions, homes in Calcasieu Parish achieve at best half of the measures necessary to stem the losses in future hurricanes, underscoring the need for policies that better incentivize and message whole-house climate adaptation strategies. Future research aims to use the data and indices to identify factors with greatest potential to motivate these whole-house adaptations.

Strategic Management Practices and Climate Change Mitigation of Total Energies Kenya Limited

Climate change is a major challenge to humanity’s existence as it leads to potential shift of weather patterns accelerating the vulnerability of the ecosystems. Realization of Climate change mitigation and adaptation objectives requires effective strategic management practices. Successful strategic management practices guarantee effective reduction of climate change impact and improved environmental sustainability. Failure to incorporate strategic management in the company’s short and long-term goals may result in lack of vision and failure to meet set environmental sustainability objectives within the set timelines. The aim of this study was to determine how strategic management practices has influenced the climate change mitigation within the oil sector in Kenya. The study was anchored on four theories; Triple Bottom Line Theory, Resource Based View Theory, Strategic Leadership Theory and Balanced Score Card Model. Descriptive research design was used for this study with a target populations of 360 employees of TEMK. Proportionate random sampling design was applied with 20% target sample size. Structured questionnaires with close ended question questions was employed as data collection instruments. Cronbach’s alpha measure was used to gauge the reliability of the questionnaire with result above 0.7 considered acceptable. The collected data was analyzed through coding of the questionnaire in SPSS. Multicollinearity test was done to show the occurrence of relationships among two or three independent variables. Variance Inflation (VIF) score was used for multicollinearity test and Normality test was done to ascertain the normality of error terms. A multiple regression equation was developed to show the connection between dependent and independent variables. Further analysis was done through percentages, means, standards deviations, regression and correlations. The analyzed data was presented through graphs, bar charts, histograms, pie charts and tables for easy and quick understanding. The study found out that climate financing, technological investments and climate change policies implementation have significant positive impact on the mitigation of climate change within the oil sector. The study concludes that factors such as climate financing, technological investments and climate change policies implementation have positive impact on the mitigation of climate change in the oil sector in Kenya. The study recommends that, in order to enhance climate financing, the government should establish enabling economic conditions through favorable tax regimes on projects related to climate change mitigation. Also, the study recommends that the oil sector should lobby for green financing by local banks to support investments on climate change. Further, the study recommends that in order to exploit the use of technological investments, the oil sector should enhance investment in renewable energy and energy efficient technologies.

Identifying future challenges for climate change adaptation through insights from participatory scenario-downscaling in Mumbai

Populations in many coastal urban areas are increasingly exposed to climate-related hazards. At the same time, the number of people residing in coastal cities is growing, and, especially in the Global South, these cities are characterised by rapid urbanisation and social inequality. However, the progress of adaptation is lagging, and there is a limited understanding of how future socioeconomic urban developments will affect cities’ social vulnerability and challenges to adaptation. We use the case study of Mumbai to apply a participatory scenario approach, in which we downscale the global Shared Socioeconomic Pathway (SSP) narratives to the local level. Our results stress the relevance of addressing social inequality in urban change processes across different sectors, including labour, housing, transport, and health and streamlining urban planning across different governance scales. Our study lays the ground for integrated modelling of future vulnerability and exposure scenarios and the development of local adaptation pathways.

How to Measure Evapotranspiration in Landscape-Ecological Studies? Overview of Concepts and Methods

Abstract Evapotranspiration (ET) is a key component of the hydrological cycle, encompassing evaporation processes from soil and water surfaces and plant transpiration (Sun et al., 2017). Accurate estimation of ET is vital for effective water resource management, agricultural planning, and environmental monitoring (Gowda et al., 2008). However, the complex interactions between land surface conditions, vegetation, and atmospheric factors make direct measurement of ET challenging, leading to the development of various estimation methods. Remote sensing has become a widely used approach for estimating ET over large areas because it provides spatially comprehensive data (Xiao et al., 2024). Methods like the Surface Energy Balance Algorithm for Land and the Surface Energy Balance System utilise satellite-derived thermal imagery and meteorological inputs to calculate ET by analysing the energy exchanges between the land surface and the atmosphere. These methods are advantageous for their broad spatial coverage, making them particularly useful for regional to global scale studies. However, they require careful calibration and validation, and their accuracy can be affected by the spatial resolution of the satellite data and the quality of meteorological inputs. In addition to remote sensing, several other ET estimation methods are commonly employed. The Penman-Monteith equation is one of the most widely accepted methods, integrating meteorological data—such as air temperature, humidity, wind speed, and solar radiation— with biophysical properties of vegetation to estimate ET. This method has been validated extensively, making it a standard reference in ET studies. Empirical methods like the Hargreaves-Samani equation provide simpler alternatives that require fewer data inputs, making them suitable for regions with limited meteorological information but with a trade-off in accuracy. Direct measurement techniques offer highly accurate ET data, including lysimeters and eddy covariance systems. Lysimeters measure water loss directly from a soil column, while eddy covariance systems assess the exchange of water vapour and energy between the surface and the atmosphere. Despite their precision, these methods are limited by high costs, maintenance requirements, and their applicability to small-scale, homogeneous areas (Howell, 2005). Choosing the appropriate ET estimation method depends on the scale of the study, data availability, and the specific application. Remote sensing and models like Penman-Monteith offer scalability and broad applicability, while direct measurements provide precise data at localised scales. Integrating these methods can improve the reliability of ET estimates, enhance water resource management, and aid in climate adaptation efforts.

Inequity in Population Exposure to Accelerated Warming

AbstractRecent temperature records have triggered debate about whether global warming is accelerating. Here, we examine for acceleration and explore possible causes for regional differences using gridded surface temperature data. We find that global and regional warming is accelerating, and on average, regions with low Human Development Index (HDI) experienced much higher accelerated warming in comparison to regions with high HDI. However, some regions of low HDI with a large population experienced slow acceleration due to high local aerosol emissions. Since aerosol negative forcing impacts are short‐lived and localized, rapid future reduction of aerosol emissions without a concurrent reduction in GHG emissions could have major compounding impacts. Such a pathway, similar to most 21st century scenarios, could expose a large fraction of the world's most vulnerable people to sudden warming acceleration and heat stress associated impacts. These results call for targeted climate adaptation strategies directing attention to low‐socioeconomic aerosol masked regions.

Accounting for Climate and Inherent Soil Quality in United Nations (UN) Land Degradation Analysis: A Case Study of the State of Arizona (USA)

Climate change and land degradation (LD) are some of the most critical challenges for humanity. Land degradation (LD) is the focus of the United Nations (UN) Convention to Combat Desertification (UNCCD) and the UN Sustainable Development Goal (SDG 15: Life on Land). Land degradation is composed of inherent and anthropogenic LD, which are both impacted by inherent soil quality (SQ) and climate. Conventional LD analysis does not take into account inherent SQ because it is not the result of land use/land cover change (LULC), which can be tracked using remote sensing platforms. Furthermore, traditional LD analysis does not link anthropogenic LD to climate change through greenhouse gas (GHG) emissions. This study uses one of the indicators for LD for SDG 15 (15.3.1: Proportion of land that is degraded over the total land area) to demonstrate how to account for inherent SQ in anthropogenic LD with corresponding GHG emissions over time using the state of Arizona (AZ) as a case study. The inherent SQ of AZ is skewed towards low-SQ soils (Entisols: 29.3%, Aridisols: 49.4%), which, when combined with climate, define the inherent LD status. Currently, 8.6% of land in AZ has experienced anthropogenic LD primarily because of developments (urbanization) (42.8%) and agriculture (32.2%). All six soil orders have experienced varying degrees of anthropogenic LD. All land developments in AZ can be linked to damages from LD, with 4862.6 km2 developed, resulting in midpoint losses of 8.7 × 1010 kg of total soil carbon (TSC) and a midpoint social cost of carbon dioxide emissions (SC-CO2) of $14.7B (where B = billion = 109, USD). Arizona was not land degradation neutral (LDN) based on an increase (+9.6%) in the anthropogenic LD overall and an increase in developments (+29.5%) between 2001 and 2021. Considering ongoing climate change impacts in AZ, this increase in urbanization represents reverse climate change adaptation (RCCA) because of the increased population. The state of AZ has 82.0% of the total state area for nature-based solutions (NBS). However, this area is dominated by soils with inherently low SQ (e.g., Entisols, Aridisols, etc.), which complicates efforts for climate change adaptation.

Extreme Weather, agricultural insurance and farmer's climate adaptation technologies adoption in China

We explore how farmers adjust their climate adaptation behaviors and participation in agricultural insurance in response to extreme weather events. A random effects model is constructed to clarify the relationships between extreme weather events, agricultural insurance and climate adaptation technologies (CAT). Using survey data from 622 farmers in China, Probit models and instrumental variable analysis show that extreme weather events significantly increase farmers' adoption of CAT and their participation in agricultural insurance. Furthermore, agricultural insurance significantly promotes farmers' adoption of CAT. Agricultural insurance influences the adoption of CAT through both substitutive and complementary effects, the complementary effects are more pronounced. Therefore, we recommended the continued promotion of CAT and agricultural insurance to strengthen farmers' resilience to extreme weather events.

Editorial: Modelling approaches for climate variability and change mitigation and adaptation in resource constrained farming systems

Editorial: Modelling approaches for climate variability and change mitigation and adaptation in resource constrained farming systems

Temporal ecotrophic impacts of fisheries and climate change in the Aegean Sea

Mediterranean fisheries face a crisis with rapidly depleting stocks due to overexploitation, exacerbated by various stressors, including climate change, alien species and pollution. To address these challenges, modelling tools like ECOPATH with ECOSIM (EwE) are being used to assess marine ecosystems within the context of the ecosystem-based fisheries management (EBFM). In this study, an ECOSIM model was developed for the Aegean Sea based on a previously developed ECOPATH configuration (calibration period: 2006-2021; projection period: 2022-2050), to assess the current state of the food web and predict future conditions. Forecast scenarios incorporating fisheries and climatic stressors were explored to propose management measures that will ensure fisheries sustainability. The baseline simulation demonstrated a decline in biomass and catch in most functional groups (FGs). Fishing effort reduction scenarios led to biomass increase in several FGs, but resulted in lower catches. Climate scenarios with sea surface temperature time series from the Intergovernmental Panel on Climate Change triggered varied responses among FGs, with biomass gains observed in the demersal compartment, while the most negatively affected pelagic groups were mackerels and horse mackerels. Combined fisheries and climatic scenarios revealed synergistic effects, emphasizing the complex ecological interactions in the Aegean Sea. Ecological indicators from the ECOIND analysis highlighted losses in the demersal compartment in relation with the fisheries and climate scenarios, while trophic-based indices exhibited the most notable variations, suggesting cascading effects in the food web. The findings of this study will provide valuable insights for fisheries management and climate adaptation strategies in the Aegean Sea.

Climate change adaptation and land tenure: exploring pastoral adaptation strategies under communal and private land ownership in Kenya

ABSTRACT Climate change adaptation is critically important for communities in the Global South, especially for those depending on climate-sensitive resources for their livelihoods, such as pastoralist communities. Land is a key asset for the ability of such communities to adapt. However, our understanding of the ways in which pastoral adaptation strategies develop under different land tenure systems – and how such strategies shape local land tenure systems – remains limited. This article conceptualises the relationship between local climate change adaptation strategies and land tenure and examines how adaptation strategies develop under communal and private tenure systems in southern Kenya. The article draws on primary data from a household survey (n = 160) and in-depth qualitative interviews in Kajiado County, Kenya, where Maasai pastoralists are adapting under both communal and private land tenure systems. We find that adaptation strategies vary with the different land tenure systems and we show how the tenure systems shape and are shaped by local adaptation strategies. We further find that wealth and social status influence the ability of households to benefit from and influence land tenure systems. The article contributes to our knowledge on autonomous local climate change adaption by adding insights on the role of land tenure as an important contextual factor. It further highlights the role of pastoralists’ agency as they develop their adaptation strategies and adjust livelihoods beyond livestock and mobility, and how this interacts with communal and private land tenure.

Insights from the international workshop on "Adapting agriculture to climate change and air pollution".

An international workshop on "Adapting Agriculture to Climate Change and Air Pollution" took place at Nanjing University of Information Science and Technology, Nanjing, China, during 23-27 October, 2023. Experts working in various multi-disciplinary areas of agroecosystem and environmental research gathered for academic communication and discussions. Two discussion groups focused on "agriculture under air pollution and climate change: current challenges and priorities for the future" and "adapting agriculture to air pollution and climate change: current status and next steps." Insights derived from the discussions are summarized in this article and include opinions about current issues, knowledge gaps' identification, and potential priorities and actions that could be taken. The first discussion mainly addresses ozone impact estimates; ozone metrics for impact and risk assessments; ozone monitoring; air pollution impacts and policy; and thepivotal role of agriculture and consumer choices. The second discussion covers adaptation and mitigation; greenhouse gases and energy efficiency; concerns about the link between adaptation and mitigation; local food, planetary-health diets and carbon footprint; irrigation and climate change adaptation; scientific evidence and policy-making; air pollution and crop adaptation; machine learning and crop modeling; and challenges faced by smallholder farmers and large-scale enterprises. Hence, this report could be useful for reseach, educational, and policy purposes, collating opinions of experts working in diverse research areas.

Enhancing Traditional Ecological Knowledge in Agricultural Waste Management: Evidences to Strengthen India’s National Action Plan on Climate Change

Agricultural waste management is a significant challenge in the context of climate change and environmental sustainability. Traditional Ecological Knowledge (TEK) has fostered effective resource management culturally over the years among farmers. However, there is a lack of research on how traditional ecological knowledge based practices can contribute towards climate action policies with respect to resource management. In this context, the current qualitative study was undertaken to assess the potential of indigenous/ traditional agricultural waste management practices in promoting resource sustainability and climate resilience, thereby analysing their ability to enhance the efficacy of the National Action Plan on Climate Change (NAPCC) in India. The research was carried out in three states of India, namely Haryana, Andhra Pradesh, and Tamil Nadu. A total of eleven farmers were selected through purposive random sampling and interviewed in-depth using semi-structured questionnaires, out of which the responses of nine farmers were included in the final data, after screening. Proper qualitative analysis of the data using thematic analysis method revealed that the farmers commonly preferred and adopted in-situ, location-specific traditional practices for agricultural waste management, thus ensuring better resource optimisation and sustainability. Traditional practices like the use of paddy straw as manure, vermicompost, traditional cisterns, Jeevamirtham, and Panchagavya have strengthened the commitment of TEK-based practices towards sustainability. The findings emphasized the integration of modern and traditional practices of agricultural waste management, combined with community-based initiatives, to better achieve the objectives of NAPCC. The insights suggested that promotion of traditional practices of agricultural waste management requires better incentives for farmers, more community based interventions by the government, and participatory decision-making with multiple stakeholders. Climate action can be enhanced by creation of traditional knowledge networks, online database, formulation of innovative hybrid models for agricultural waste management and promotion of community efforts to collectively enhance climate change adaptation in agriculture under the ageis of NAPCC. Traditional Ecological Knowledge should be rightfully incorporated into NAPCC to promote sustainability, strengthen climate resilience, thereby fostering a stronger policy framework.

Factors Influencing Rural Women’s Adoption of Climate Change Adaptation Strategies: Evidence from the Chivi District of Zimbabwe

The socio-cultural leadership system in rural communities of developing countries is generally gender-biased, thus rendering female-headed households (FHHs) vulnerable to climate change risk. This study explored the factors influencing FHHs’ adoption of a climate change adaptation strategy (CCAS) in Chivi District, Zimbabwe. We used a multistage sampling technique and logistic regression to evaluate 107 women household heads’ livelihood and their decision to adopt the CCAS in Ward 25 of the Chivi District. The results show that the age of the female head significantly influenced the CCAS decision (R2 = −0.073), along with marital status (R2 = 0.110), agricultural training (R2 = 0.133), club membership (R2 = 0.084), and farm size (R2 = 0.014). Access to formal agricultural training plays a prominent role. At the same time, the institutional framework showed variations and laxity on the part of the local government, as access to extension services varies significantly. In addition, education level was reported to have an insignificant (p = 0.098) influence on CCAS adoption. Overall, multiple institutional and socio-economic factors are essential in influencing CCAS decisions. Hence, central and local governments are encouraged to improve outreach strategies on deploying supporting tools, extension agents, and vital stakeholders for strategic information dissemination to sensitize rural dwellers and community leaders on women’s and FHHs’ crucial role in food security and their resilience to climate change risk. Moreover, the educational syllabus can be enhanced at all rural education levels to reshape the norms of future generations against the customary impact of old age on farming approaches and to encourage women’s participation in decision making and interventions, particularly those sensitive to their societal contributions.

Examining the nexus of social vulnerability, land cover dynamics, and heat exposure in Reno, Nevada, USA

Intense heat is a persistent urban challenge whose impacts are detrimental to human health. Heat-related effects disproportionately impact underserved populations. Modification of urban landscapes through increased imperviousness intensifies surface temperatures, leading to heightened heat exposure risks. While climate adaptation efforts have advanced, they are inadequate in addressing the uncertainties of climate change and the long-term risks of climate-related hazards. In addition, despite the numerous heat vulnerability studies across U.S. cities, the City of Reno is largely understudied. To address these gaps, the research examined the relationship between the spatiotemporal patterns of social vulnerability, changes in biophysical properties, and the heat hazard in Reno, Nevada. We utilized CDC census data to map the Social Vulnerability Index (SVI) and Landsat satellite data from 1990 to 2023 to analyze Land Surface Temperature (LST) trends for a temporal comparative study of heat patterns. Additionally, we employed the Normalized Difference Vegetation Index (NDVI) for vegetation extent. The zonal statistics tool helped assess the influence of different land use features on surface temperatures. The results showed that regions identified as social vulnerability hotspots often coincided with areas highly exposed to extreme temperatures and vice versa. Our findings also revealed an extension of heat vulnerability hotspots from the urban core to suburban regions. We observed a decline in mean LST values in regions covered by vegetation and a rise in mean surface temperatures in regions encompassed with imperviousness. These findings underscore the need for increased vegetation for heat mitigation.