High Emission Scenario Research Articles

Differential flood insurance participation and housing market trajectories under future coastal flooding in the United States

Communities respond to flooding events based upon risk perceptions and available adaptive behaviors (e.g., emigrating, purchasing insurance, constructing levees). Across the United States, sea level rise, intensifying storm-surges, and extreme rainfall may alter human-flood dynamics. Here, we use calibrated Socio-Environmental models of contiguous US coastal census tracts and two shared socio-economic pathways (SSP245 and SSP585). We project that by 2100, total flood insurance claims will increase by +25% to +130% under low (SSP245) and high (SSP585) emissions scenarios, respectively. The increase in flood insurance claims will impact mainly socially vulnerable communities. Further, we project that active NFIP policies will increase from +30% under low emission scenario to +60% under high emission scenario. Our finding also suggests the growing debt of the National Flood Insurance Program under higher emissions. Raising the water elevation threshold for coastal flooding by +1 meter via levees may reduce future surge-related losses by 95% and 40% under low and high emission scenarios and stabilize housing markets. Our future projections of flood insurance claims, policy coverage, and the impact of water elevation serve as credible hypotheses for the evolution of human flood dynamics under climate change. They can inform national flood policy and future research.

Planned relocation may reduce communities’ future exposure to coastal inundation but effect varies with emission scenario and geography

The planned, permanent relocation of entire communities away from sea level rise (SLR) and coastal floods is an already occurring climate change adaptation strategy. Yet, planned relocations are fraught undertakings with multiple goals, and may or may not achieve their most basic objective: to reduce risk. Here we assess risk of future coastal flooding before and after moving, for three dates and three emissions scenarios, for 17 communities from a global dataset. Most communities achieved exposure reduction with less future inundation in destinations than origin sites, but the extent varies across time and emissions scenario. In all cases, origin sites have projected exposure to SLR plus a once-per-year flood, with increasing exposure under high emissions scenarios and towards 2100. In nine cases, even destination sites have projected inundation exposure under some scenarios. Small-island-to-small-island relocations had more projected inundation in destinations than moves from a small-island-to-mainland, or from mainland-to-mainland.

Mapping Climatic Regions of the Cerrado: General Patterns and Future Change

ABSTRACTThe Cerrado biome, renowned for its biodiversity and threatened by rapid land transformation, encompasses a vast savanna ecosystem in Brazil. The region is characterised by a seasonal climate, influenced by a myriad of meteorological systems creating diverse and non‐homogeneous rainfall regimes across the region. To account for this heterogeneity, we propose a novel classification of the Cerrado using rainfall data to delineate three distinct climatic regions: Eastern, Southern and Central‐West Cerrado. The Eastern region exhibited the driest and most seasonal climate, marked by high vapour pressure deficit (VPD) and predominantly open‐canopy vegetation. Conversely, the Southern region, characterised by lower seasonality, boasts a higher proportion of forest cover and lower mean VPD. The Central‐West region, encompassing diverse landscapes, featured areas with higher precipitation levels, particularly along the Amazônia border. Furthermore, we conducted trend analyses on observed station data and used CMIP6 models to evaluate future scenarios under differing emissions trajectories. While observed trends in mean rainfall were marginal, VPD demonstrated a notable upward trend of approximately 1% annually throughout the biome. Climate models indicated a substantial drying close to the Amazônia border, and wetter conditions in the southeast. All Cerrado regions are anticipated to experience amplified seasonality and VPD, with VPD projected to surge by approximately 30% (60%) under low (high) emissions scenarios by the end of the century. Notably, the transition from the dry to wet season was the most affected. Our study provides critical insights on how the climatic heterogeneity of the Cerrado shapes vegetation structure distribution and how future changes will exacerbate water stress throughout the biome. These findings underscore the importance of understanding climate variability for effective conservation and management strategies in the region.

Warming Leads to Lower Rice Quality in East Asia

AbstractRice quality, which is intricately connected to market value and human nutrition, is sensitive to weather conditions. However, the relative importance of the different climatic factors is poorly understood, and the impact of climate change on rice quality has been little studied on a large scale. Here, using more than 35 years of rice quality data, we present the first effort to determine the key climate variables driving rice quality in China and Japan. Results show a significant decline in high quality rice rate (HRR, an indicator of rice quality), mainly driven by warm nighttime temperatures when they exceed a critical threshold estimated at 18°C and 12°C in China and Japan, respectively. Climate projections suggest a continuing decreasing trend in HRR under moderate and high emission scenarios by 2100. These findings emphasize the importance of breeding new heat tolerant cultivars to maintain stable rice quality in the future.

Projecting dry-wet abrupt alternation across China from the perspective of soil moisture

Under a warmer climate, the enhancement of dry-wet abrupt alternation (DWAA) risk poses a great challenge for sustainable development. Here, we introduce a novel framework for DWAA detection based on our proposed soil moisture concentration index. By the end of this century, over humid southern China, the shift of soil moisture time series from anomalously wet to anomalously dry pattern, or the other way around, will be more abrupt. In addition, the proposed framework driven by Coupled Model Intercomparison Project Phase 6 simulations projects more widespread DWAA-affected areas over southwestern China, coastal regions of southeastern China, and the lower reaches of the Yangtze River, especially under a high emission scenario. The framework proposed in this study provides an efficient system for DWAA detection and prediction, and the findings of this study provide a reference for upgrading hydraulic infrastructure and mitigating future DWAA events.

Acclimation of Photosynthesis to CO2 Increases Ecosystem Carbon Storage due to Leaf Nitrogen Savings.

Photosynthesis is the largest flux of carbon between the atmosphere and Earth's surface and is driven by enzymes that require nitrogen, namely, ribulose-1,5-bisphosphate (RuBisCO). Thus, photosynthesis is a key link between the terrestrial carbon and nitrogen cycle, and the representation of this link is critical for coupled carbon-nitrogen land surface models. Models and observations suggest that soil nitrogen availability can limit plant productivity increases under elevated CO2. Plants acclimate to elevated CO2 by downregulating RuBisCO and thus nitrogen in leaves, but this acclimation response is not currently included in land surface models. Acclimation of photosynthesis to CO2 can be simulated by the photosynthetic optimality theory in a way that matches observations. Here, we incorporated this theory into the land surface component of the Energy Exascale Earth System Model (ELM). We simulated land surface carbon and nitrogen processes under future elevated CO2 conditions to 2100 using the RCP8.5 high emission scenario. Our simulations showed that when photosynthetic acclimation is considered, photosynthesis increases under future conditions, but maximum RuBisCO carboxylation and thus photosynthetic nitrogen demand decline. We analyzed two simulations that differed as to whether the saved nitrogen could be used in other parts of the plant. The allocation of saved leaf nitrogen to other parts of the plant led to (1) a direct alleviation of plant nitrogen limitation through reduced leaf nitrogen requirements and (2) an indirect reduction in plant nitrogen limitation through an enhancement of root growth that led to increased plant nitrogen uptake. As a result, reallocation of saved leaf nitrogen increased ecosystem carbon stocks by 50.3% in 2100 as compared to a simulation without reallocation of saved leaf nitrogen. These results suggest that land surface models may overestimate future ecosystem nitrogen limitation if they do not incorporate leaf nitrogen savings resulting from photosynthetic acclimation to elevated CO2.

Projections of Greenland periphery glaciers and ice caps’s change

Abstract Rapid global warming has caused drastic mass loss of Greenland’s peripheral glaciers and ice caps (GICs), which impacts on global sea level rise. To further clarity future GICs changes under different emission scenarios, we used the Open Global Glacier Model (OGGM) to simulate glaciers dynamic and runoff changes from 2015 to 2100. The results show that area and volume of GICs will decrease by 38.88% (SSP1-2.6) to 60.84% (SSP5-8.5) and 47.56% (SSP1-2.6) to 67.10% (SSP5-8.5) by 2100, with regions having larger glacierized areas and being farther from the ocean experiencing less volume loss. Meanwhile, Surface Mass Balance (SMB) of GICs in 2100 is -0.58±0.92, -1.18±1.13, -2.04±0.79 and -3.16±0.96 m w.e. a-1 under four emission scenarios. The runoff under high emission scenarios is greater than that under low emission scenarios, with peak water occurring later in regions with larger glacierized areas and being farther from the ocean.

Evaluating the tradeoffs between water conservation, aesthetic value, evaporative cooling and CO2 emissions in St. augustinegrass and buffalograss

Urban lawns comprise a significant portion of urban greenery and provide several ecosystem services. Nevertheless, maintaining lawns comes with significant water costs in semi-arid inland southern California, as they require consistent irrigation to stay healthy and productive. The main objective of this study was to evaluate the effect of a wide range of irrigation rates and frequencies applied autonomously by a smart ET-based controller on the aesthetic value, cooling potential, and CO2 efflux of two warm-season turfgrass species. For three years, we studied the responses of Buffalograss and St. Augustinegrass to six irrigation rates and two irrigation frequencies in Riverside, California. Under historical average climate conditions, the minimum irrigation rate for Buffalograss was 93 % ETo, and for St. Augustinegrass, it was 74 % ETo. Under projected future climate conditions, the estimated minimum irrigation rate for Buffalograss did not change, but for St. Augustinegrass, it increased by 4 % and 7 % in 2100 under low emission (RCP 4.5) and high emission (RCP 8.5) scenarios, respectively. On average, canopy minus air temperature in Buffalograss was 6.2 ℃, and in St. Augustinegrass, it was 1.1 ℃. The average CO2 efflux in Buffalograss was 122.3 µg CO2-C m−2 s−1, and in St. Augustinegrass, it was 182.8 µg CO2-C m−2 s−1. Our results showed that turfgrass aesthetic values, cooling potential, and CO2 efflux diminished as the irrigation rate decreased, but at different rates for each turfgrass species.

Lessons learnt from a real-time attribution and contextualisation trial in a National Meteorological and Hydrological Service

Abstract When a record hot month occurs, timely and credible attribution and contextualisation information can enhance public understanding and future preparedness. This is particularly effective if provided in real time by a National Meteorological and Hydrological Service (NMHS). Many NMHSs are working to integrate research-based attribution methods into their operational services. In this study, researchers and climate service staff collaborated to assess the feasibility of delivering such information swiftly and aligned with standard NMHS data and procedures. The record warm July (winter) temperatures of Tasmania, Australia in 2023 were chosen to illustrate the trial. Rapid results were available three days after the event. Approximately half of the unusual warmth was attributed to climate change, with the likelihood of breaking the previous record at least 17 times higher in the current climate compared to a stationary pre-industrial climate (14% vs. 0.4%). The warming trend became evident in the 1980s, and by 2060, average July temperatures in Tasmania match the record temperature of July 2023 under a high emissions scenario. However, average July minimum temperatures were not well modelled, necessitating the addition of a higher-resolution forecast-based attribution method. In subsequent analysis, almost all the forecast temperature anomaly, and reduced storm activity, was attributable to climate change. Statistical analysis revealed that a weak El Niño partly offset the unusual warmth. To expedite these additional approaches, information drawn from real-time forecasts could be used. Lessons learnt from this trial include technical improvements to align better with NMHS protocols including using consistent datasets and baselines, and refining and automating the method suite. Logistical and communication enhancements included training staff to run the suite, improving communication materials, and developing delivery channels. These learnings provide key considerations for NMHSs as they move towards providing timely and credible climate attribution and contextualisation information as part of their operational services.

Measuring rising heat and flood risk along the belt-and-road initiative

China’s global infrastructure financing flagship, the Belt and Road Initiative (BRI) encompasses countries hosting over 60% of the global population and one-third of worldwide GDP. It is based mainly on long-term loans that will mature decades into the future, and timely repayments are only possible if they remain commercially viable. But despite its vast global scope, little is known about the climate risks that could imperil the operations of BRI projects over the next few decades, and, consequently, threaten their long-term sustainability. We narrow this gap by estimating the impacts of future climate change on 217 BRI projects across 70 countries and 9 sectors in two dimensions. First, the effects of increased heat stress on human physical work capacity are calculated using the wet bulb globe temperature and an assessment of the workload for each selected BRI project. Second, the potential structural damages from more frequent flooding incidents are measured by return period (RP), where a shorter RP signals heightened risk. Both have direct impacts on human productivity and infrastructural integrity, which are essential to maintaining the operational viability and financial stability of BRI projects. We compared projected changes on both measures for the mid- and late-twentieth centuries (2041–2060 and 2081–2100) to the historical baseline (1981–2010). We found that BRI projects face escalating vulnerability to climatic risks on both counts. The results underscore a broad variance across different future carbon emission scenarios measured under the Shared Socioeconomic Pathways (including SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). BRI’s aggregated climatic risks are substantially elevated under a high carbon emission scenario compared to a low emission scenario. By the end of the twentieth century, labor workability under SSP3-7.0 (31%) could potentially decrease three times more compared to SSP1-2.6 (10%). Under an intermediate-emission scenario (SSP2-4.5), floods with a historical return period of 10 years could have a return period of 5 years in the future. Significantly hampering the utilization and economic return generation potential of infrastructure projects. In addition, regional geography contributes to risk heterogeneity, with 100-year floods occurring every 15 years in South Asia and every 24 years in Sub-Saharan Africa. Such climate risk implications, potentially overlooked by development financiers, represent significant risks to the sustenance of the BRI, estimated to be worth $1 trillion.

The increasing influence of atmospheric moisture transport on hydrometeorological extremes in the Euromediterranean region with global warming

The Euromediterranean area is a key region in which the link between atmospheric moisture transport and hydrometeorological extremes concerns. Atmospheric rivers, the main moisture transport mechanism affecting the region, play a notable role in extreme precipitation there. Moreover, moisture transport deficits from two of the major oceanic moisture sources of the planet, the North Atlantic Ocean and the Mediterranean Sea, are strongly related to drought occurrence in that region. Here, we examine the projected changes in these relationships with global warming, under a high-emission scenario (shared socioeconomic pathway 5–8.5). Here we show that, for the mid-21st century, a moderate increase in the influence of moisture transport on winter precipitation maxima is projected, in line with its increasing concurrence with atmospheric rivers. A stronger increase is estimated for the relationship between moisture transport deficits and drought occurrence, for which probabilities between two and three times greater than those observed in the present climate are obtained for the mid- and end-21st century. This highlights the increasing importance of moisture transport from the ocean in future droughts in the region, especially in the context of reduced local moisture inputs from terrestrial evaporation as a consequence of drier soil.

Major distribution shifts are projected for key rangeland grasses under a high-emission scenario in East Africa at the end of the 21st century

Grassland landscapes are important ecosystems in East Africa, providing habitat and grazing grounds for wildlife and livestock and supporting pastoralism, an essential part of the agricultural sector. Since future grassland availability directly affects the future mobility needs of pastoralists and wildlife, we aim to model changes in the distribution of key grassland species under climate change. Here we combine a global and regional climate model with a machine learning-based species distribution model to understand the impact of regional climate change on different key grass species. The application of a dynamical downscaling step allows us to capture the fine-scale effects of the region’s complex climate, its variability and future changes. We show that the co-occurrence of the analysed grass species is reduced in large parts of eastern Africa, and particularly in the Turkana region, under the high-emission RCP8.5 scenario for the last 30 years of the 21st century. Our results suggest that future climate change will alter the natural resource base, with potentially negative impacts on pastoralism and wildlife in East Africa.

Modeling climate-related global risk maps of rice bacterial blight caused by Xanthomonas oryzae (Ishiyama 1922) using geographical information system (GIS).

Rice is a critical staple crop that feeds more than half of the world's population. Still, its production confronts various biotic risks, notably the severe bacterial blight disease produced by Xanthomonas oryzae. Understanding the possible effects of climate change on the geographic distribution of this virus is critical to ensuring food security. This work used ecological niche modeling and the Maxent algorithm to create future risk maps for the range of X. oryzae under several climate change scenarios between 2050 and 2070. The model was trained using 93 occurrence records of X. oryzae and five critical bioclimatic variables. It has an excellent predictive performance, with an AUC of 0.889. The results show that X. oryzae's potential geographic range and habitat suitability are expected to increase significantly under low (RCP2.6) and high (RCP8.5) emission scenarios. Key climatic drivers allowing this development include increased yearly precipitation, precipitation during the wettest quarter, and the wettest quarter's mean temperature. These findings are consistent with broader research revealing that climate change is allowing many plant diseases and other dangerous microbes to spread across the globe. Integrating these spatial predictions with data on host susceptibility, agricultural practices, and socioeconomic vulnerabilities can help to improve targeted surveillance, preventative, and management methods for reducing the growing threat of bacterial blight to rice production. Proactive, multidisciplinary efforts to manage the changing disease dynamics caused by climate change will be critical to assuring global food security in the future decades.

Divergent future trends in global land greening and carbon sequestration under climate change scenarios

Abstract Over the past four decades, global land greening has promoted carbon (C) storage in terrestrial ecosystems. However, whether the future trajectory of this positive greening effect on ecosystem C sequestration is sustainable under various climate scenarios remains uncertain. Here, using projections from ten Earth system models, we found divergent trends in the relationship between global land greening and C storage among three distinct shared socioeconomic pathways (SSPs). We identified global transition times for their positive relationships, which will occur in 2034, 2038, and 2048 for SSP1-2.6, SSP2-4.5, and SSP5-8.5, respectively. We found a widespread decoupling trend of vegetation greening and ecosystem C storage under medium to high emission scenarios, particularly in the tundra, boreal forest, and grassland regions, by delving deeper into six transition modes. These findings underscore the highly uncertain role of vegetation greening in land C sequestration under prospective climate change scenarios.

Southern Hemisphere Winter Storm Tracks Respond Differently to Low and High CO2 Forcings

Abstract In the Southern Hemisphere, Earth system models project an intensification of winter storm tracks by the end of the twenty-first century. Previous studies using idealized models showed that storm track intensity saturates with increasing temperatures, suggesting that the intensification of the winter storm tracks might not continue further with increasing greenhouse gases. Here, we examine the response of midlatitude winter storm tracks in the Southern Hemisphere to increasing CO2 from two to eight times preindustrial concentrations in more realistic Earth system models. We find that at high CO2 levels (beyond 4×CO2), winter storm tracks no longer exhibit an intensification across the extratropics. Instead, they shift poleward, weakening the storm tracks at lower midlatitudes and strengthening at higher midlatitudes. By analyzing the eddy kinetic energy (EKE) budget, the nonlinear storm-track response to an increase in CO2 levels in the lower midlatitudes is found to stem from a scale-dependent conversion of eddy available potential energy to EKE. Specifically, in the lower midlatitudes, this energy conversion acts to oppositely change the EKE of long and short scales at low CO2 levels, but at high CO2 levels, it mostly reduces the EKE of shorter scales, resulting in a poleward shift of the storms. Furthermore, we identify a “tug of war” between the upper and lower temperature changes as the primary driver of the nonlinear-scale-dependent EKE response in the lower midlatitudes. Our results suggest that in the highest emission scenarios beyond the twenty-first century, the storm tracks’ response may differ in magnitude and latitudinal distribution from projected changes by 2100. Significance Statement The Southern Hemisphere winter storm track is projected to intensify by the end of the century, with the most significant intensification occurring in the higher midlatitudes. However, we show that the intensification is not a linear function of the radiative forcing associated with increasing CO2 levels. In fact, our study shows a poleward shift at very high CO2 levels, with the storm track moving southward. This suggests that the Southern Hemisphere winter storm track may require time-sensitive adaptation strategies, as the impacts of global warming on the storm track may not be a linear function of CO2 concentration in the atmosphere.

Substantial reduction in population exposure to sea level changes along the Chinese mainland coast through emission mitigation

Abstract Rising sea level increases the exposure to flooding and related damage in coastal areas with high population density and substantial economic activity. As global temperatures continue to rise due to climate change, sea levels have been consistently increasing and are projected to continue this upward trend. This study assesses the future exposure at provincial and city levels populations coastal mainland China coast to local sea level changes under five greenhouse gas (GHG) emission scenarios from IPCC-AR6, as well as two low-confidence scenarios accounting for the potential impact of uncertain ice sheet processes with low- and high-GHG emissions. We incorporate spatial heterogeneity into regional sea level projections and population projections from 2020 to 2100, extreme sea levels (ESLs) of 10-, 50-, and 100 year return periods (RP), and local coastal protection standards. Our findings indicate that the inundated areas expand continuously within the century with heightened exposure under higher emission scenarios. Although the coastal population is projected to decline, the fraction of the coastal population exposed to flooding increases across all scenarios, with accelerated growth under higher GHG emissions and higher ESLs. Zhejiang and Jiangsu emerge as the provinces most exposed to sea-level rise, whereas Taizhou, Nantong, Wuxi, Panjin, and Huzhou are identified as the top five cities with the highest population exposure to local sea level rise (SLR). Transitioning towards a sustainable scenario (i.e. SSP1-2.6) rather than a fossil fuel-intensive one (i.e. SSP5-8.5) can reduce the local SLR and substantially mitigate these exposures. Compared to the median projections under SSP5-8.5, aligning GHG emissions with SSP1-2.6 could reduce population exposure substantially in all coastal provinces, especially in Jiangsu, where population exposure to 100 year RP coastal floods would be reduced by ∼1.6 M in 2050 and by ∼5.4 M in 2100.

Faster dieback of rainforests altering tropical carbon sinks under climate change

Carbon sinks in the tropical rainforests are restricting the global warming to attain unprecedented heights. However, deforestation and climate change is switching them to a net carbon source at some of the deforested patches. Using machine learning algorithm we predict that more than 50% of the tropical rainforests will undergo rapid “Savannisation”/transformation by the end of 21st century under high emission scenarios. Climate change projects ‘El Niño-like’ warming condition, which decreases precipitation in the rainforests and favors atmospheric dryness. In Central Amazonia vegetation degradation saturates the carbon sink and more than 25% of the rainforests will transform into a net carbon source due to increase in soil microbial respiration. This transition will accelerate if Eastern Pacific/Global temperature warms beyond 1.5◦K/2.3◦K (by 2050’s) and will undergo a steeper transit by ~2075 (2.45◦K/3.8◦K warming). This alteration will exacerbate global warming and has consequences for policies that are intended to stabilize Earth’s climate.

Observational constraint on climate model projections of global compound hot–dry events and the socioeconomic risks under climate change

Abstract The frequency of compound hot-dry events (fHD) is projected to increase significantly with future warming, yet associated uncertainties remain considerable and poorly constrained. In this study, we constrain future projections of fHD (2070-2099) using observations of recent trends in temperature (T) and precipitation (P) (1980-2014) during the warm-seasons. The physical mechanism is that the variance of fHD across climate models is dominated by their projected changes in P (ΔP), which can be constrained by recent trends in T and P. Compared to the raw projections, the observationally constrained fHD is reduced by 9.68%~18.74%, with uncertainty narrowed by 3.79%~10.66% under the high emission scenario. The highest decline of fHD is located in regions with low population and GDP, and globally, population and GDP exposures to fHD are reduced by 6.02%~10.73% and 6.51%~12.03%, respectively. The observationally constrained fHD with lower uncertainty provides more reliable information for risk management under climate change.

Asymmetric responses of EVI and tree ring growth to extreme climate on the northeastern margin of the Tibetan Plateau.

Extreme climate events have increased in terms of their amplitudes, frequency and severity, greatly affecting ecosystem functions and the balance of the global carbon cycle. However, there are still uncertainties about how extreme climate change will affect tree growth. This study characterized the responses of tree growth to extreme climate on the northeastern Tibetan Plateau from 2000 to 2020. Meanwhile, a back propagation neural network was used to predict tree growth trends under two future emission scenarios from 2020 to 2050. This study revealed that: (1) the tree-ring width index (RWI) showed a decreasing trend (- 0.04/decade) in the eastern region, but the enhanced vegetation index (EVI) showed an increasing trend (0.05/decade) from 2000 to 2020. While both RWI and EVI in the middle and western regions showed increasing trends. (2) The responses of RWI and EVI to extreme climate were regionally asymmetric. In the eastern region, extreme precipitation inhibited tree radial growth, while extreme warm nights promoted tree canopy growth. In two other regions, both extreme precipitation and extreme warm nights promoted tree growth. (3) The model predicts that there was no significant change in RWI and EVI in the western region, but both RWI and EVI showed an increasing trend in the middle and eastern regions under the low emission scenario. Under the high emission scenario, the growth of tree stem and canopy in all three regions shows a general decreasing trend. The results of this study both improved the understanding of the differences in carbon allocation between tree stem (RWI) and canopy (EVI) and identified vulnerability thresholds for tree populations.

Projecting urban flood risk through hydrodynamic modeling under shared socioeconomic pathways

Under future climate change, accurate risk assessment of urban flooding disasters is paramount for effective adaptation and mitigation strategies. However, conventional indicator-based assessment methods often fall short of accurately capturing the complexity of flooding dynamics. Current research predominantly focuses on predicting future hazard shifts while overlooking changes in other critical indicators. In this study, we establish a comprehensive index system for risk assessment, and quantified future changes in most indicators, utilizing the InfoWorks ICM model for hazard simulation and the CLUMondo model for land use predictions. Based on risk assessment results and regional characteristics, we further analyze the key factors driving future risk and discuss corresponding measures. The results indicate an exacerbation of future urban flood risk, with an 18% increase in high risk areas, primarily concentrated in the center of the study area. The dominant indicators are inundation depth and land use over the whole study area. However microtopography significantly affects risk in low-lying areas. Overall, under higher emission scenarios, the influence of GDP and population rises. These findings offer methodological insights for future urban flood risk assessment research and provide policymakers with valuable guidance to develop targeted adaptation measures in response to climate change.