Climate Change Impact Assessment Research Articles

Climate change impact assessment of growing degree days and thermal growing period of cotton in north-west India

ABSTRACT Temperature is an indispensable necessity of plant growth, which explains the 95% variability in plant development. Accumulated temperature, i.e. growing degree day (GDD) is a useful agro-climatic indicator that translates raw climatic data into meaningful decisions. In this study, the GDD concept is used to analyze spatio-temporal variability of accumulated growing degree days (AGDD) and thermal growing period of cotton for the past and future climates in the three different zones (north-east, central and south-west) of Punjab. During the baseline period, higher AGDD were accumulated in the south-western (2,441 °C day), followed by central (2,276.8 °C day) and north-eastern (2,073.8 °C day) zones. During the end of mid-century, AGDD of the central zone was increased by 4–11%, 3–27% for north-eastern, and 3–7% for south-western zones in contrast to the baseline period. This increase in AGDD of cotton might decrease the thermal growing period by 6–14%, 8–25%, and 4–8% for central, north-east and south-western zones, clearly indicating the thermal stress over the cotton crop. This study provides quantitative information for crop breeders and cotton scientists to develop new genetically modified cultivars and improved agronomic practices to mitigate the adverse effect of climate change.

Climate change impact on hydropower generation and adaptation through reservoir operation in a Himalayan river, Tamor

ABSTRACT Integrated assessment of climate change impact and water resource development scenario is crucial for planning and management. In the Himalayan river basin, it is of utmost importance considering the vulnerability to climate change and the pace of water resource development. This study focused on Tamor river basin (TRB), investigating the impacts of climate change on the energy generation from hydropower projects and analyzes the adaptation through reservoir operation. Analyzing the three run-of-river (RoR) hydropower projects and a storage project, this study projects future energy generation. Results showed that RoR is highly susceptible to the impacts, demonstrated by significant reduction during pre-monsoon up to -53% and increment at annual scale up to 28%. In Tamor storage project, the particle-swarm optimization approach generated operational strategies according to altered streamflow conditions. This resulted in adaptation to the projected decrease in March-June flow through flexible operation rules, yielding positive impact on energy generation (up to +7.3% on an annual scale). The new set of rules will adapt to the flow deficit and increase the dry season flow downstream, almost by double than the historical baseline. This research highlights the significance of reservoir project and its optimized operation in effectively managing water under changing climate.

Water resources management under climate change and anthropogenic pressure in the upper Bandama catchment in Northern Côte d'Ivoire

ABSTRACT The upper Bandama basin at Badikaha in the North of Côte d'Ivoire, subject to climate change, has recorded a rapid population growth that significantly affects water availability. This study applies the water evaluation and planning (WEAP) system model to explore how the water resources available currently can meet people's needs in the future, mainly for irrigation, mining activities, rural and urban water supply and cattle breeding. The outputs from two regional climate models RACMO 22T and CCLM 4-8-17 under representative concentration pathway (RCP) 4.5 and RCP 8.5 scenarios were used for the climate change impact assessment. Results predict an increase in mean annual temperature by 1.5°C while precipitation could decrease by 21% by 2090. The climate model outputs coupled with the WEAP model show that unmet water demand estimated to 50 million m3 in 2020 could reach 115 million m3 in 2050. Nevertheless, climate change mitigation scenarios by the WEAP model, including the implementation of dams, boreholes and the hydraulics infrastructure improvement reveal that water scarcity could be reduced significantly in the catchment.

Review on Potential Urban Development Site Selection Using Geospatial-Based Multi-Criteria Decision Analysis (MCDA) Techniques in the Context of Ethiopia

This review paper provides a comprehensive assessment of the opportunities and challenges in leveraging geospatial-based technologies, particularly Multi-Criteria Decision Analysis (MCDA) techniques, to enhance the effectiveness of urban development site selection in Ethiopia. The overarching findings highlight several critical focus areas for improvement. Firstly, the review emphasizes the need to strengthen the availability, quality, and accessibility of geospatial data through the development of robust data infrastructures and innovative data collection methods. Secondly, it recommends adopting a more inclusive and collaborative approach to stakeholder engagement, coupled with targeted capacity-building initiatives to enhance the technical skills and knowledge of urban planners, GIS experts, and local stakeholders. Thirdly, the paper suggests incorporating advanced spatial modeling and simulation techniques to capture the dynamic nature of urban growth patterns, as well as integrating climate change impact assessments and disaster risk analyses into the decision-making framework. Fourthly, it emphasizes the importance of strengthening institutional and organizational frameworks to promote cross-sectoral collaboration, data sharing, and integrated decision-making processes. Finally, the review underscores the significance of designing user-friendly and customizable Spatial Decision Support Systems (SDSS) that cater to the specific needs and constraints of the Ethiopian urban development context. The review concludes that the use of geospatial-based MCDA approaches holds immense potential in addressing Ethiopia's complex urban development challenges, as it enables a comprehensive evaluation of suitability factors and the exploration of alternative urban development strategies.

Assessment of Climate Change Impact on Potato-Potato Cropping System Under Semi-arid Environment and Designing of Adaptation Strategies

Assessment of Climate Change Impact on Potato-Potato Cropping System Under Semi-arid Environment and Designing of Adaptation Strategies

Assessment of Climate Change Impact on Future Distribution of Palm Trees in Niger, West Africa

Palm trees are multi-purpose species that are involved in several socio-economic and cultural aspects of Niger people. Indeed, palm trees significantly improve local population life. This study aims to assess the impact of future climate change on the geographical distribution of Borassus aethiopum Mart., Hyphaene thebaica (L.) Mart. and Phoenix dactylifera L. and to determine the suitable habitats for the conservation and sustainable management of these species in Niger. The maxEnt approach was used to model the species distribution. Four climatic models of CHELSA V2.1 were used: gfdl-esm4, ipsl-cm6a-lr, mpi-esm1-2h, mri-esm2-0 under two scenarios: ssp1-2.6 and ssp5-8.5 by periods 2011–2040 and 2041–2070. The mean AUC was 0.93 for Borassus aethiopum (0.93), 0.86 for Hyphaene thebaica, and 0.87 for Phoenix dactylifera. TSS test mean were 0.85, 0.69, and 0.75 respectively for Borassus aethiopum, Hyphaene thebaica, and Phoenix dactylifera. The current distribution for highly suitable habitats was 33,223 km2 (2.22%), 159,495 km2 (10.66%), and 108,189 km2 (7%) respectively for Borassus aethiopum, Hyphaene thebaica, and Phoenix dactylifera. The moderately suitable habitats were 83,019 km2 (5.55%) for Borassus aethiopum, 86,239 km2 (5.76%) for Hyphaene thebaica and 66,426 km2 (4%) Phoenix dactylifera. The lowly suitable habitats were 137,859 km2 (9.21%), 201,609 km2 (13.48%), and 333,181 km2 (22%) respectively Borassus aethiopum, Hyphaene thebaica, and Phoenix dactylifera. The highly and moderately suitable habitats for Borassus aethiopum will increase over the period 2011–2040 and 2041–2070. The highly suitable habitats of Hyphaene thebaica will be highly decreased by the period 2011–2040 and 2041–2070 than the other suitable habitats. All suitable habitats and all models of Phoenix dactylifera will decrease under the period 2041–2070. Phoenix dactylifera and Hyphaene thebaica will be much more affected by future climate change. This will also affect production rates for farmers in Niger.

Evaluating the impacts of anticipated sea level rise, climate change and land use land cover scenarios on the rice crop in Alappuzha, Kerala and strategies to build climate responsive agriculture

PurposeThis paper aims to inform the readers an overview of expected impacts of sea level rise (SLR) and climate change on rice crops area, yield and the urgent need to build climate responsive infrastructures to a coastal district, Alappuzha – a high-risk area which is already under mean sea level (MSL). This research carried out to understand the realities and impacts with respect to the exposures of rise in SLR and possible inundation extent of crop land. The extreme precipitation events have caused crop loss and damage, numerous casualties and enormous economic loss in this district during the recent past and project the likely impacts under anticipated climate change.Design/methodology/approachGlobal sea levels have already been risen noticeably as a result of climate change, and this trend is anticipated to continue. To reflect on the research objectives, the paper projects a climate change scenario analysis and impact assessment on the major crop grown, i.e. rice, using a crop simulation model, DSSAT 4.7 as the first part of the study. QGIS 3.28 version and Erdas Imagine software were used for land use land cover analysis and to delineate possible inundation in the major land use land cover, especially in agriculture area under SLR scenario. It points out the need to equip the district urgently with climate responsive agriculture strategies as majority of the area comes under 10 mts of elevation as per the Sentinel 2 data. For better adapting to the current and future climate change impacts in the aspects of built environment such as early warnings in farm sector in particular and forests, urban water management, transportation systems, building construction and operation and land use planning in general. Climate change is no longer a policy issue alone; now it is a common man’s nightmare. For a coastal state like Kerala, extreme climate events during 2018 and 2019 and 2021 have posed substantial impacts and damages on the environment and society. The impacts hit the vulnerable communities in multiple ways.FindingsFrom the analysis, it was revealed that there is an increasing trend in rainfall observed over the past three decades in Alappuzha district. It is projected that day and night time temperatures may increase in Alappuzha by 2.5°C and 2.6°C by 2100, respectively, under RCP 4.5. With unchecked pollution or emission reduction actions, warming may further rise and hence the median projection when SLR reaches 2.4 meters (8 ft) at Alappuzha to Cochin coast is 2130s. The possible inundation analysis shows that around 53.48% of the coastal agriculture land may be likely inundated if SLR is only with mitigation measures such as extreme carbon cuts, SLR rise can be delayed till 2200. Alappuzha is known as the rice bowl of Kerala; however, it is highly exposed to climate vulnerability in terms of its unique environmental geographical settings like coastal wetlands, lagoons and sand beaches. DSSAT simulations shows that Uma rice, a major ruling variety in the region, may have yield reductions of up to 13% in the near century for Alappuzha.Research limitations/implicationsThis paper in general explains the projected climate change perspectives for Alappuzha, a climate change hotspot of Kerala with respect to SLR and coastal agriculture. and a review of the progression of DRR in the built environment and mainstreaming CCA and DRR by government and other agencies in the state.Practical implicationsThis study underscores the urgent need for climate-responsive agricultural strategies in Alappuzha, Kerala, due to anticipated sea level rise, climate change, and land use changes. Equipping farmers with the knowledge and tools to adapt is essential for ensuring food security and sustainable livelihoods. Implementing climate-resilient practices and technologies will help mitigate adverse effects on rice crops, promoting economic stability and resilience in the region. Involving local stakeholders in the adaptation process is crucial, as their participation can enhance collaboration, increase awareness, and accelerate the adoption of sustainable agricultural practices, making the transition smoother and more effective.Social implicationsIt is the responsibility of the scientific community to inform the knowledge gained for the benefit of the society, especially on criticality of altering the existing land use pattern and building climate resilient coastal infrastructures. Studies such as this can stand as basis for implementing planned adaption actions. This is to conclude that instead of working in silos, mainstreaming climate change adaptation holistically across sectors is very necessary at this crucial hour. Participatory action plans and policies involving all local stakeholders can strengthen awareness and fasten the learning processes for adaptation including managed retreats.Originality/valueAt present, there are no specific studies, on the impacts of climate change and SLR on rice cropping systems in the district which specifically inform how to mainstream adaptation in the agriculture strategies in low lying coastal zones of Alappuzha.

Assessment of climate change impact and resource-use efficiency of lettuce production in vertical farming and greenhouse production in Finland: a case study

Abstract Purpose Our aim in this study was to examine lettuce production in vertical farming or in conventional greenhouse production in Northern European conditions from the perspective of climate change impact and environmental sustainability. Further, the goal was to identify practices and choices that could mitigate adverse effects and increase resource-use efficiency, allowing the development of more sustainable production systems. Methods This article provides new information of the environmental impacts of lettuce production in greenhouses and vertical farming in Finland, compared using the life cycle assessment (LCA) methodology. The impact categories used were climate change impact, cumulative energy demand, resource use of fossil energy sources, resource use of minerals and metals, land use, and water scarcity. The system boundaries covered the production chains from cradle to farmgate, including inputs in production, as well as direct emissions caused by fertiliser use and the onsite composting of organic waste. The environmental impacts of the two production systems with different energy scenarios were assessed: (1) a greenhouse either with average or renewable energy; and (2) vertical farming either with average or renewable energy and with or without waste heat recovery. The data for vertical farming were based on one Finnish production site and supplementary data for the construction materials. The greenhouse data were based on a previous LCA investigation of average Finnish lettuce production. Results The climate change and all other impact categories were lowest for lettuce produced in vertical farming with renewable energy and waste heat recovery. The climate change impact was largest for lettuce produced in greenhouse with average energy use. For energy use and energy resource use, the impacts of vertical farming were lower than greenhouse production, but for mineral and metal use and water scarcity, the impact of vertical farming was higher for average energy use without heat recovery. Direct land and irrigation water use on the production sites in Finnish circumstances represented only a small share of total land-use and water-use impacts on both production methods. Conclusion Paying attention to the energy source and heat recovery, the environmental sustainability can be advanced in both vertical and greenhouse production systems.

Linking local climate scenarios to global warming levels: applicability, prospects and uncertainties

Abstract Global warming levels (GWLs) are increasingly becoming a central concept in climate change studies. In recent years, their integrative quality for climate change impact analysis has been demonstrated, and methodological advancements have helped to compensate for some inherent shortfalls of the concept. However, their applicability at the regional level is debatable, and no study to date has examined the possibility of linking local climate scenarios to GWLs. For the case of Austria, we have evaluated the relation between global and local warming patterns, and whether version changes of global climate models could be incorporated into local climate scenarios by means of the GWL concept, without updating the actual data. We applied the time sampling approach, where GWLs are determined as periods when global mean temperature anomalies cross a certain threshold. GWL periods were sampled both from the global models in the background of the local climate scenarios (CMIP5), and from an equivalent ensemble of newer-generation climate models (CMIP6). Uncertainties resulting from sampling GWLs from different global climate model ensembles were examined, and prospects for local climate change impact assessments were discussed. Accounting for updated global climate model versions might be useful when the changes at certain GWLs are related to fixed reference periods, but temperature increments between GWLs remained relatively constant across model versions, even on the local level. The study bridges a significant gap to link regional and local climate projections to GWLs. Climate change impacts assessments that build on those datasets can benefit from the integrative character of GWLs, making studies comparable across multiple disciplines and model versions, and thus fostering a way to communicate local climate change impacts more comprehensible.

Climate trend analysis in the ramis catchment, upper wabi shebelle basin, Ethiopia, using the CMIP6 dataset

Climate change, a global concern, has significant implications for rainfall and temperature patterns. A critical knowledge gap exists in understanding these implications for the Ramis catchment of the Upper Wabi-Shebelle Basin. This research projects future rainfall and temperature patterns in the Ramis catchment of the Upper Wabe-Shebelle basin. The projection utilized a multimodel comprising eight distinct general circulation models from coupled model intercomparison phase six (CMIP6) data simulation. These models were selected based on their performance, considering two shared socioeconomic pathways (SSP2-4.5 and SSP5-8.5). The Quantile Mapping (QM) bias correction technique, implemented in R, was used to enhance the reliability of extracted data. The Mann‒Kendall (MK) trend test method was employed to analyze temperature and precipitation trends for two future periods, 2030–2060 and 2061–2090, annually and seasonally. The results suggest a decrease in rainfall during the spring and Winter seasons for 2030 to 2060 and 2061 to 2090 respectively, potentially leading to water scarcity that could impact crop growth and water supply. A decreasing trend in annual rainfall was observed from 2030 to 2060 under SSP2-4.5 and SSP5-8.5 scenarios. The study also uncovered significant and consistent warming trends in maximum and minimum temperatures across the Ramis catchment under both the SSP2-4.5 and SSP5-8.5 scenarios. Rainfall Anomaly Index (RAI) analysis predicts a minor increase in rainfall in the Ramis catchment from 2030 to 2090 under both scenarios, with a notable RAI decrease expected in 2043–2071, indicating potential drought conditions. These findings offer critical insights for regional climate change impact assessments across the Ramis catchment.

Pathways to identify and reduce uncertainties in agricultural climate impact assessments.

Both climate and impact models are essential for understanding and quantifying the impact of climate change on agricultural productivity. Multi-model ensembles have highlighted considerable uncertainties in these assessments, yet a systematic approach to quantify these uncertainties is lacking. We propose a standardized approach to attribute uncertainties in multi-model ensemble studies, based on insights from the Agricultural Model Intercomparison and Improvement Project. We find that crop model processes are the primary source of uncertainty in agricultural projections (over 50%), excluding unquantified hidden uncertainty that is not explicitly measured within the analyses. We propose multidimensional pathways to reduce uncertainty in climate change impact assessments.

Climate stress testing for water systems: Review and guide for applications

AbstractTogether with other “bottom‐up” methods, climate stress testing is becoming a prominent approach for climate change impact assessment of water systems. Compared with traditional approaches, stress testing is: (i) more focused on exploring the vulnerabilities of the system at hand; (ii) potentially more inclusive, being amenable to stakeholder involvement and (iii) well suited to identify robust policy options that better account for the deep uncertainty associated with multiple plausible futures. Stress testing is rapidly evolving and giving rise to new techniques and concepts, but few articles provide an accessible overview that can serve as an introduction to the field. Here, we review the underlying principles and concepts of climate stress testing, providing a guide to the main decisions involved in practical application. Topics include selection of stressors, characterizing and exploring the exposure space and data generation including the use of stochastic data. In a complex world where water decisions are made in the context of wider socio‐ecological systems, stress testing and other bottom‐up methods can support decisions that are not only robust to future uncertainty but also regarded as legitimate by affected communities.This article is categorized under: Engineering Water > Sustainable Engineering of Water Science of Water > Water and Environmental Change Water and Life > Stresses and Pressures on Ecosystems

Decarbonization frameworks to industrial-scale ammonia production: Techno-economic and environmental implications

Ammonia production traditionally relies on steam methane reforming (SMR), but it emits carbon and harms the environment. To address decarbonization frameworks of industrial-scale ammonia production process, a 100,000-ton ammonia manufacturing plant is presented using green ammonia synthesis methods. This study presents two promising hydrogen production methods for ammonia production, utilizing water electrolysis as scenario 1 and biomass gasification as scenario 2, while nitrogen is supplied using a cryogenic air separation unit (CASU). The techno-economic analysis shows that the ammonia production via SMR as the base case has lower total costs than Scenarios 1 and 2 due to not using green electricity. Through the environmental impact assessment of climate change, ozone depletion, terrestrial ecotoxicity, and natural land transformation, it is shown that Scenario 1 has lower impacts than the base case and Scenario 2 due to using green electricity. It is noted that the base case and Scenario 1 ensure the lowest production cost and environmental impacts, respectively, and Scenario 2 is the best balance between the economy and the environment.

Matching Spring Phenology Indicators in Ground Observations and Remote-Sensing Metrics

Accurate monitoring of leaf phenology, from individual trees to entire ecosystems, is vital for understanding and modeling forest carbon and water cycles, as well as assessing climate change impact. However, the accuracy of many remote-sensing phenological products remains difficult to directly corroborate using ground-based monitoring, owing to variations in the observed indicators and the scales used. This limitation hampers the practical implementation of remote-sensing phenological metrics. In our study, the start of growing season (SOS) from 2016 to 2021 was estimated for the continental USA using Sentinel-2 images. The results were then matched with several ground-based spring vegetation phenology metrics obtained by the USA National Phenology Network (USA-NPN). In this study, we focused on the relationships between the leaf-unfolding degree (LUD), the SOS, and the factors that drive these measures. Our results revealed that: (1) the ground-based leaves and increasing leaf size stages were significantly correlated with the SOS; (2) with the closest match being observed for a leaf spread of 13%; (2) the relationship between the SOS and LUD varied according to the species and ecoregion, and the pre-season cumulative radiation was found to be the main factor affecting the degree of matching between the ground observations and the metrics derived from the Sentinel-2 data. Our investigations provide a ground-based spring phenology metric that can be used to verify or evaluate remote-sensing spring phenology products and will help to improve the accuracy of remote-sensing phenology metrics.

Two decades of coral bleaching in selected islands of Pacific Ocean: A holistic impact assessment

Coral reefs are regarded as one of the most diverse, productive as well as sensitive ecosystems existing across the world. Major coral reefs across the Pacific Ocean exhibit a vast variety of species, the majority of which are under threat, largely due to changes in past conducive climatic and oceanic parameters. The present study involves the mapping of coral reefs at select islands of Great Barrier Reefs (Heron Island), Fiji (Namena Island), and Cook Island (Aitutaki Island) using Landsat 7 (ETM+) and Landsat 8 (OLI/ TIRS) satellite data for the years 2002 and 2020. Depth invariant bottom index (DII) is applied for water column correction and identification of bottom type submerged and heterogeneous coral reef classes. Maximum likelihood classifier (supervised classification) is performed to characterize various classes of the coral community. Turbidity values (10.4 – 53 Nephelometric Turbidity unit (NTU)), (4.74–26.1NTU), and (14.56–73.56 NTU) for Heron, Namena, and Aitutaki Islands indicate a pronounced effect of sedimentation due to an increase in Sea level rise and anthropogenic activities. Increasing trend of oceanic parameters viz. SST, PAR, salinity, and sea level rise indicated an adverse impact on coral health and triggered coral bleaching along these Islands especially due to El Niño events in the years 2015–2016. We identified the coral mortality for 18 years of period as 16.1 %, 20.2 % and 11. 2 % in Heron, Namena, and Aitutaki Island respectively. The study provides a holistic impact assessment of various anthropogenic activities and climate change on the health of the coral reef ecosystem.

Impact Assessment of Climate Change on Water Supply to Hsinchu Science Park in Taiwan

Impact Assessment of Climate Change on Water Supply to Hsinchu Science Park in Taiwan

Climate change impact assessment on the hydrological response of the Tawa basin for sustainable water management

Sustainable water resources planning and management are essential for meeting the needs of both current and future generations while mitigating environmental impacts. River basins, integral components of ecosystems, are pivotal in implementing well-balanced and responsible management strategies. River basins serve as crucial sources for freshwater supply, irrigation, hydropower generation, and industrial activities. In the face of climate change, it becomes imperative to prioritize the hydrological impact assessment of river basins. This prioritization aims to ensure the resilience of water systems, recognizing the heightened challenges posed by changing climatic conditions. The present study examines the projected changes in the mean and high flow of Tawa River, an important Narmada River tributary that is critical for agriculture and hydropower generation using two conceptual lumped hydrological models, MIKE 11 NAM and GRJ4 respectively, and thirteen CMIP6 global climate models (GCMs) for two shared socioeconomic pathways (SSPs), SSP2-45 and SSP5-85, in the near (2030–2060) and far (2070–2100) futures. Our findings reveal a significant rise in both mean monthly and extreme discharge levels for two scenarios: SSP2-4.5 and SSP5-8.5. Notably, the projections indicate that the mean annual discharge, extreme discharge levels, and their frequency are anticipated to rise considerably more dramatically in the period of far future (2070–2100), particularly under the SSP5-8.5 scenario. This study underlines the importance of establishing a mitigation strategy for sustainable water resources and increased community resilience to climate change in the Tawa River Basin.

Performance evaluation of CMIP6 models for application to hydrological modelling studies – A case study of Australia

Accurate estimation of climate change impacts on catchment hydrology is essential for effective future water management. The efficacy of such estimations is dependent on proper climate model selection. In this study, an attempt was made to formulate a methodology for climate model selection, evaluating eight climate models from the sixth phase of the Coupled Model Intercomparison Project (CMIP6). The models were assessed for their ability to simulate variables used in hydrological studies and large-scale atmospheric circulation influencing rainfall in Australia. Five statistical indicators Root Mean Square Error (RMSE), Spatial Correlation (SC), Percentage Bias (Pbias), Normalized Root Mean Square Error (NRMSE), and Nash-Sutcliffe Efficiency (NSE) were used to evaluate the performance, and the models were ranked through Compromise Programming (CP), a multiple criteria decision making technique. Results show that HadGEM3-GC31-LL performed well in most of the categories considered and was top top-ranked model overall followed by GFDL-ESM4, CESM2-CAM6-RT, and CanESM5 for Australia. Conversely, MIROC6 consistently ranked lower in most of the categories. In the context of simulating hydrological variables, CESM2-CAM6-RT, HadGEM3-GC31-LL, and GFDL-ESM4 emerged as the top three models. The robustness of the proposed methodology suggests its applicability for model selection, making it a replicable approach for climate change impact assessment studies in diverse regions.

Editorial: Assessment of Climate Change Impact on Water Resources Using Machine Learning Algorithms

Editorial: Assessment of Climate Change Impact on Water Resources Using Machine Learning Algorithms

Climate change impact and adaptation assessment for road drainage systems

Climate change exhibits a clear trend of escalating frequency and intensity of extreme weather events, posing heightened risks to drainage systems along the existing road networks. However, very few studies to date have investigated the consequences of projected future changes in rainfall on main road drainage and the resulting risk of road flooding. The work presented in this paper builds on the limited research by introducing a probabilistic model for assessing the impact of climate change on road drainage systems, incorporating climate uncertainty and drainage system variation. The probabilistic scenario-based model and associated framework offer a practical and innovative method for estimating the impact of short-duration storms under future climates for 2071–2100, in the absence of fine-resolution spatio-temporal data. The model also facilitates the assessment of the effectiveness of a climate adaptation strategy. An illustrative case-study of a road drainage system located in the south of Ireland is presented. It was found that the probability of road flooding during intense rainfall is projected to surpass the current acceptable limits set by Irish standards. Assessment of a proactive climate adaptation strategy implemented in 2015 indicated it may need to be adjusted to further reduce climate change impacts and optimise adaptation costs.