Special Report On Emissions Scenarios Research Articles

Assessment of the Impacts of Climate Change on European Ozone Levels

The objective of this study is to investigate the potential impact of future climate change on ozone air quality in Europe. To provide a full assessment, simulations with the global chemical transport model GEOS-CHEM driven by the NASA Goddard Institute for Space Studies general circulation model (NASA/GISS GCM) are conducted. To isolate the effects from changes in climate and anthropogenic emissions four types of simulations are performed: (1) present-day climate and emissions (2) future climate following the IPCC Special Report on Emission Scenarios (SRES) A1B scenario and present-day anthropogenic emissions of ozone precursors (3) present-day climate and future emissions and (4) future climate and future emissions. Results indicate that climate change impact on its own leads to an increase of less than 3 ppb in western and central Europe whereas decreases are evident for the rest of the areas with the highest (about 2.5 ppb) in southeastern Europe (Italy, Greece). Increases are attributed to the increases of isoprene biogenic emissions due to increasing temperatures whereas decreases are associated with the increase of water vapor over sea which tends to decrease the lifetime of ozone as well as the increased wind speeds in the 2050 climate. When future emissions are implemented in the future climate simulations, the greatest increases are seen in the southwest and southeast Mediterranean (about 16 ppb) due to the increased isoprene biogenic emissions under higher levels of NO x in the model. Decreases up to 2 ppb of ozone are shown for France, Switzerland, Northern Italy and northern Europe.

Climate change and water resources in the Bagmati River Basin, Nepal

This paper characterizes potential hydrological impact of future climate in the Bagmati River Basin, Nepal. For this research, basinwide future hydrology is simulated by using downscaled temperature and precipitation outputs from the Hadley Centre Coupled Model, version 3 (HadCM3), and the Hydrologic Engineering Center's Hydrologic Modeling System (HEC-HMS). It is predicted that temperature may rise maximally during the summer rather than winter for both A2 and B2 Special Report on Emissions Scenarios (SRES) scenarios. Precipitation may increase during the wet season, but it may decrease during other seasons for A2 scenario. For B2 scenario, precipitation may increase during all the seasons. Under the A2 scenario, premonsoon water availability may decrease more in the upper than the middle basin. During monsoons, both upper and middle basins show increased water availability. During the postmonsoon season, water availability may decrease in the upper part, while the middle part shows a mixed trend. Under the B2 scenario, water availability is expected to increase in the entire basin. The analysis of the projected hydrologic impact of climate change is expected to support informed decision-making for sustainable water management.

Projection of multi-site daily temperatures over the Montréal area, Canada

This study presents a post-adjustment procedure for a multivariate multi-site statistical downscaling model (MMSDM) which can simultaneously downscale multiple predictands at multiple observation sites by combining multivariate multiple linear regression and the stochastic randomization procedure. In the post-adjustment procedure, bias and determinant adjustment factors correct the systematic bias on the downscaled series using atmosphere-ocean coupled global climate model (AOGCM) predictors, and prevent the propagation of systematic error to the projected future predictands. The MMSDM with the post-adjustment procedure is applied to project a realistic series of 2 predictands (daily Tmax and Tmin) for 10 observation sites in the region of Montreal (southern Quebec, Canada). The Canadian CGCM3 reference outputs (1961-2000) and future outputs under the A1B and A2 SRES scenarios (2061-2100) were employed as AOGCM predictors. On average over the 10 observation sites, the monthly means of the daily Tmax and Tmin were increased by 2.0-4.7 and 2.7-5.4°C while seasonal 90th percentile of daily Tmax and 10th percentile of daily Tmin (Tmax90 and Tmin10) were increased by 2.1-4.5 and 2.7-5.8°C for the A1B and A2 scenarios with the MMSDM, respectively. Future Tmax and Tmin series showed higher increases in winter than in the other seasons, as anticipated from AOGCMs or regional climate models over the same area. The average diurnal temperature ranges of future series suggest small increases in spring and autumn. Finally, the projected series yielded frost seasons that are 23 and 28 d shorter, whereas 23 and 27 more days are projected for the length of the growing season than in the present-day climate series.

Interactions between land use change, regional development, and climate change in the Poyang Lake district from 1985 to 2035

Land use change and climate change are two major global modifications of our environment and are predicted to continue in the future. To assess how climate change affects land use and regional development in the Poyang Lake district in China, we use agent-based modeling and simulate the physical and socio-economic drivers within two interactive sub-models for urban expansion and rural development. The modeling outputs from 1985 to 2005 show good agreement with the observed land use change. Possible land use changes and regional development paths until 2035 are examined for three SRES scenarios including A1B (rapid growth), A2 (regional-diversified growth) and B1 (growth with clean technologies). The results show that climate change induced impacts on land use change and regional development are highly relevant and may even amplify the complex interactions. In particular, cropland, forest, water area, urban, and grassland are more sensitive to these changes than unused land. The more environmental friendly B1 scenario results in less concerning land use changes.

기후변화 시나리오에 따른 건물부분의 영향

According to the Fourth Assessment Report of Intergovernmental Panel on Climate Change(IPCC) Working Group III, climate change is already in progress around the world, and it is necessary to execute mitigation in order to minimize adverse impacts. This paper suggests future climate change needs, employing IPCC Special Report on Emissions Scenarios(SRES) to predict temperature rises over the next 100 years. This information can be used to develop sustainable architecture applications for energy efficient buildings and renewable energy. Such climate changes could also affected the present supplies of renewable energy sources. This paper discusses one recent Fourth Assessment Report of IPCC (Mitigation of Climate Change) and the Hadley Centre climate simulation of relevant data series for South Korea. Result of this research may improve consistency and reliability of simulation weather data or climate change in order to take advantage of SRES and PRECIS QUMP. It is expected that these calculated test reference years will be useful to the designers of solar energy systems, as well as those who need daily solar radiation data for South Korea. Also, those results may contribute zero carbon and design of sustainable architecture establishing future typical weather data that should be gone ahead to energy efficient building design using renewable energy systems.

Impact of future climate change on wheat production in relation to plant-available water capacity in a semiaridenvironment

Conceptions encompassing climate change are irreversible rise of atmospheric carbon dioxide (CO2) concentration, increased temperature, and changes in rainfall both in spatial- and temporal-scales worldwide. This will have a major impact on wheat production, particularly if crops are frequently exposed to a sequence, frequency, and intensity of specific weather events like high temperature during growth period. However, the process of wheat response to climate change is complex and compounded by interactions among atmospheric CO2 concentration, climate variables, soil, nutrition, and agronomic management. In this study, we use the Agricultural Production Systems sIMulator (APSIM)-wheat model, driven by statistically downscaled climate projections of 18 global circulation models (GCMs) under the 2007 Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES) A2 CO2 emission scenario to examine impact on future wheat yields across key wheat growing regions considering different soil types in New South Wales (NSW) of Australia. The response of wheat yield, yield components, and phenology vary across sites and soil types, but yield is closely related to plant available water capacity (PAWC). Results show a decreasing yield trend during the period of 2021–2040 compared to the baseline period of 1961–1990. Across different wheat-growing regions in NSW, grain yield difference in the future period (2021–2040) over the baseline (1961–1990) varies from +3.4 to −14.7 %, and in most sites, grain number is decreased, while grain size is increased in future climate. Reduction of wheat yield is mainly due to shorter growth duration, where average flowering and maturing time are advanced by an average of 11 and 12 days, respectively. In general, larger negative impacts of climate change are exhibited in those sites with higher PAWC. Current wheat cultivars with shorter growing season properties are viable in the future climate, but breading for early sowing wheat varieties with longer growing duration will be a desirable adaptation strategy for mitigating the impact of changing climate on wheat yield.

Future projections of heat waves around Japan simulated by CMIP3 and high‐resolution Meteorological Research Institute atmospheric climate models

AbstractFuture changes in heat wave characteristics around Japan are investigated using Coupled Model Intercomparison Project Phase 3 (CMIP3) model outputs, and high‐resolution present‐day (1979–2003) and future (2075–2099) climate simulations under the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A1B emission scenario. The high‐resolution simulations are conducted using 20, 60, and 180 km mesh atmospheric general circulation models (AGCMs), as well as a 5 km mesh regional climate model (RCM) nested within the 20 km mesh AGCM. The CMIP3 models project that the frequency of heat wave days (HWF) will increase 22.8, 22.3, and 26.5 d yr–1 in northern, eastern, and western Japan, respectively. The multimodel ensemble spread of future changes in HWF averaged around Japan is large (4–58 d yr–1). The spread is affected by the climate sensitivity of the models and the simulated magnitude of the interannual variation of the daily maximum temperature in present‐day climate. In the atmospheric model simulations, the 5 and 20 km mesh models can qualitatively simulate observed HWF distributions, which are affected by steep backbone mountain ranges in Japan. The 5 and 20 km mesh models project large (>30 d yr–1) increases in HWF in the coastal areas of Japan. The duration of heat wave days is projected to increase in areas with increasing HWF.

Projection of fire potential to future climate scenarios in the Alpine area: some methodological considerations

In Europe, wildfires are an issue not only for the Mediterranean area, but also in the Alpine regions in terms of increasing number of events and severity. In this study we evaluate the impact of climate change on the fire potential in the Alps in the past and in future scenarios. The Fine Fuel Moisture Code (FFMC) of the Canadian Forest Fire Danger Rating System, which successfully distinguishes among recorded fire/no fire events, is applied to projections of Regional Climate Models (RCMs) calculated on the SRES scenario A1B. We compare two different techniques: 1) a single model run of the COSMO-CLM RCM at 18 km resolution, and 2) a combination of 25-km resolution RCMs from the ENSEMBLES project, combined with the Multimodel SuperEnsemble technique and a new probabilistic Multimodel SuperEnsemble Dressing. The single-model RCM allows for a greater coherence among the input parameters, while the Multimodel techniques permit to reduce the model biases and to downscale to a higher resolution where long term records of observations are available. The projected changes with the Multimodel in the scenario give an estimation of increasing wildfire potential in the mid XXI century. In particular the frequency of severe wildfire potential days is shown to increase dramatically. The single (independent) COSMO model gives a weaker signal and in some regions of the study area the predicted changes are opposite to the ones by the Multimodel. This is mainly due to increasing precipitation amounts simulated especially in the northern parts of the Alps. However, there are also some individual models included in the Multimodel ensemble that show a similar signal. This confirms the ambiguity of any impact study based on a single climate model due to the uncertainty of the projections of the climate models.

Performance assessment of different data mining methods in statistical downscaling of daily precipitation

Summary In this paper, nonlinear Data-Mining (DM) methods have been used to extend the most cited statistical downscaling model, SDSM, for downscaling of daily precipitation. The proposed model is Nonlinear Data-Mining Downscaling Model (NDMDM). The four nonlinear and semi-nonlinear DM methods which are included in NDMDM model are cubic-order Multivariate Adaptive Regression Splines (MARS), Model Tree (MT), k -Nearest Neighbor ( k NN) and Genetic Algorithm-optimized Support Vector Machine (GA-SVM). The daily records of 12 rain gauge stations scattered in basins with various climates in Iran are used to compare the performance of NDMDM model with statistical downscaling method. Comparison between statistical downscaling and NDMDM results in the selected stations indicates that combination of MT and MARS methods can provide daily rain estimations with less mean absolute error and closer monthly standard deviation and skewness values to the historical records for both calibration and validation periods. The results of the future projections of precipitation in the selected rain gauge stations using A2 and B2 SRES scenarios show significant uncertainty of the NDMDM and statistical downscaling models.

Modeling the potential impacts of climate change on streamflow in agricultural watersheds of the Midwestern United States

The ability to predict spatial variation in streamflow at the watershed scale is essential to understanding the potential impacts of projected climate change on aquatic systems in this century. However, problems associated with single outlet-based model calibration and validation procedures can confound the prediction of spatial variation in streamflow under future climate change scenarios. The goal of this study is to calibrate and validate a distributed hydrologic model, the Soil and Water Assessment Tool (SWAT), using distributed streamflow data (1978–2009), and to assess the potential impacts of climate change on future streamflow (2051–2060 and 2086–2095) for the Rock River (RRW), Illinois River (IRW), Kaskaskia River (KRW), and Wabash River (WRW) watersheds in the Midwestern United States, primarily in Illinois. The potential impacts of climate change on future water resources are assessed using SWAT streamflow simulations driven by projections from nine global climate models (GCMs) under a maximum of three SRES scenarios (A1B, A2, and B1). Results from model validation indicate reasonable spatial and temporal predictions of streamflow, suggesting that a multi-site calibration strategy is necessary to accurately predict spatial variation in watershed hydrology. Compared with past streamflow records, predicted future streamflow based on climate change scenarios will tend to increase in the winter but decrease in the summer. According to 26 GCM projections, annual streamflows from 2051 – 2060 (2086–2095) are projected to decrease up to 45.2% (61.3%), 48.7% (49.8%), 48.7% (56.6%), and 41.1% (44.6%) in the RRW, IRW, KRW, and WRW, respectively. In addition, under the projected changes in climate, intra- and inter-annual streamflow variability generally does not increase over time. Results suggest that increased temperature could change the rate of evapotranspiration and the form of precipitation, subsequently influencing monthly streamflow patterns. Moreover, the spatially varying pattern of streamflow variability under future climate conditions suggests different buffering capabilities among regions. As such, regionally specific management strategies are necessary to mitigate the potential impacts of climate change and preserve aquatic ecosystems and water resources.

Projected shifts of wine regions in response to climate change

This research simulates the impact of climate change on the distribution of the most important European wine regions using a comprehensive suite of spatially informative layers, including bioclimatic indices and water deficit, as predictor variables. More specifically, a machine learning approach (Random Forest, RF) was first calibrated for the present period and applied to future climate conditions as simulated by HadCM3 General Circulation Model (GCM) to predict the possible spatial expansion and/or shift in potential grapevine cultivated area in 2020 and 2050 under A2 and B2 SRES scenarios. Projected changes in climate depicted by the GCM and SRES scenarios results in a progressive warming in all bioclimatic indices as well as increasing water deficit over the European domain, altering the climatic profile of each of the grapevine cultivated areas. The two main responses to these warmer and drier conditions are 1) progressive shifts of existing grapevine cultivated area to the north–northwest of their original ranges, and 2) expansion or contraction of the wine regions due to changes in within region suitability for grapevine cultivation. Wine regions with climatic conditions from the Mediterranean basin today (e.g., the Languedoc, Provence, Cotes Rhone Meridionales, etc.) were shown to potentially shift the most over time. Overall the results show the potential for a dramatic change in the landscape for winegrape production in Europe due to changes in climate.

Climate extremes indices in the CMIP5 multimodel ensemble: Part 2. Future climate projections

This study provides an overview of projected changes in climate extremes indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI). The temperature‐ and precipitation‐based indices are computed with a consistent methodology for climate change simulations using different emission scenarios in the Coupled Model Intercomparison Project Phase 3 (CMIP3) and Phase 5 (CMIP5) multimodel ensembles. We analyze changes in the indices on global and regional scales over the 21st century relative to the reference period 1981–2000. In general, changes in indices based on daily minimum temperatures are found to be more pronounced than in indices based on daily maximum temperatures. Extreme precipitation generally increases faster than total wet‐day precipitation. In regions, such as Australia, Central America, South Africa, and the Mediterranean, increases in consecutive dry days coincide with decreases in heavy precipitation days and maximum consecutive 5 day precipitation, which indicates future intensification of dry conditions. Particularly for the precipitation‐based indices, there can be a wide disagreement about the sign of change between the models in some regions. Changes in temperature and precipitation indices are most pronounced under RCP8.5, with projected changes exceeding those discussed in previous studies based on SRES scenarios. The complete set of indices is made available via the ETCCDI indices archive to encourage further studies on the various aspects of changes in extremes.

Participatory design of farm level adaptation to climate risks in an arable region in The Netherlands

In the arable farming region Flevoland in The Netherlands climate change, including extreme events and pests and diseases, will likely pose risks to a variety of crops including high value crops such as seed potato, ware potato and seed onion. A well designed adaptation strategy at the farm level can reduce risks for farmers in Flevoland. Currently, most of the impact assessments rely heavily on (modelling) techniques that cannot take into account extreme events and pests and diseases and cannot address all crops, and are thus not suited as input for a comprehensive adaptation strategy at the farm level.To identify major climate risks and impacts and develop an adaptation measure portfolio for the most relevant risks we complemented crop growth modelling with a semi-quantitative and participatory approach, the Agro Climatic Calendar (ACC), A cost-benefit analysis and stakeholder workshops were used to identify robust adaptation measures and design an adaptation strategy for contrasting scenarios in 2050.For Flevoland, potential yields of main crops were projected to increase, but five main climate risks were identified, and these are likely to offset the positive impacts. Optimized adaptation strategies differ per scenario (frequency of occurrence of climate risks) and per farm (difference in economic loss). When impacts are high (in the +2°C and A1 SRES scenario) drip irrigation was identified as the best adaptation measure against the main climate risk heat wave that causes second-growth in seed and ware potato. When impacts are smaller (the +1°C and B2 SRES scenario), other options including no adaptation are more cost-effective.Our study shows that with relatively simple techniques such as the ACC combined with a stakeholder process, adaptation strategies can be designed for whole farming systems. Important benefits of this approach compared to modelling techniques are that all crops can be included, all climate factors can be addressed, and a large range of adaptation measures can be explored. This enhances that the identified adaptation strategies are recognizable and relevant for stakeholders.

Estimating future burned areas under changing climate in the EU-Mediterranean countries

The impacts of climate change on forest fires have received increased attention in recent years at both continental and local scales. It is widely recognized that weather plays a key role in extreme fire situations. It is therefore of great interest to analyze projected changes in fire danger under climate change scenarios and to assess the consequent impacts of forest fires. In this study we estimated burned areas in the European Mediterranean (EU-Med) countries under past and future climate conditions. Historical (1985–2004) monthly burned areas in EU-Med countries were modeled by using the Canadian Fire Weather Index (CFWI).Monthly averages of the CFWI sub-indices were used as explanatory variables to estimate the monthly burned areas in each of the five most affected countries in Europe using three different modeling approaches (Multiple Linear Regression — MLR, Random Forest — RF, Multivariate Adaptive Regression Splines — MARS). MARS outperformed the other methods. Regression equations and significant coefficients of determination were obtained, although there were noticeable differences from country to country.Climatic conditions at the end of the 21st Century were simulated using results from the runs of the regional climate model HIRHAM in the European project PRUDENCE, considering two IPCC SRES scenarios (A2–B2). The MARS models were applied to both scenarios resulting in projected burned areas in each country and in the EU-Med region. Results showed that significant increases, 66% and 140% of the total burned area, can be expected in the EU-Med region under the A2 and B2 scenarios, respectively.

Low probability, high impact: the implications of a break-up of China for carbon dioxide emissions

The transition from autocracy to democracy may lead a country to break-up. The break-ups of the USSR and Yugoslavia led to sharp falls in the level of emissions (while pre- and post-crisis trends are similar). If something like that would happen in China, an event with an unknown but small probability, projected emissions would fall by 50 % or more. The effect of a break-up on emissions in 2050 is larger than the difference between the SRES scenarios.

Using Carbon Capture and Storage CCS Techniques in Mulla Abdulla and Taza Power Plants to Mitigate the Impact of Climate Change

In the IPCC Intergovernmental Panel on Climate Change Special Report on Emission Scenarios (SRES), it was projected that the number of CO2 emission sources from the electric power and industrial sectors will increase significantly until 2050. Because fossil fuel-fired power plants are responsible for around one-third of total global CO2 emissions, they are prime candidates for the application of CO2 capture and storage techniques. The aim of this work is to mitigate the impact of climate change by reducing the amount of CO2 emitted to the atmosphere in Mulla Abdulla and Taza power plants in Kirkuk/ Iraq using CCS techniques, and to calculate the cost of the system components.

The impacts of climate change on river flow regimes at the global scale

Summary This paper presents an assessment of the impacts of climate change on a series of indicators of hydrological regimes across the global domain, using a global hydrological model run with climate scenarios constructed using pattern-scaling from 21 CMIP3 (Coupled Model Intercomparison Project Phase 3) climate models. Changes are compared with natural variability, with a significant change being defined as greater than the standard deviation of the hydrological indicator in the absence of climate change. Under an SRES (Special Report on Emissions Scenarios) A1b emissions scenario, substantial proportions of the land surface (excluding Greenland and Antarctica) would experience significant changes in hydrological behaviour by 2050; under one climate model scenario (Hadley Centre HadCM3), average annual runoff increases significantly over 47% of the land surface and decreases over 36%; only 17% therefore sees no significant change. There is considerable variability between regions, depending largely on projected changes in precipitation. Uncertainty in projected river flow regimes is dominated by variation in the spatial patterns of climate change between climate models (hydrological model uncertainty is not included). There is, however, a strong degree of consistency in the overall magnitude and direction of change. More than two-thirds of climate models project a significant increase in average annual runoff across almost a quarter of the land surface, and a significant decrease over 14%, with considerably higher degrees of consistency in some regions. Most climate models project increases in runoff in Canada and high-latitude eastern Europe and Siberia, and decreases in runoff in central Europe, around the Mediterranean, the Mashriq, central America and Brasil. There is some evidence that project change in runoff at the regional scale is not linear with change in global average temperature change. The effects of uncertainty in the rate of future emissions is relatively small.

Revisiting the Indian summer monsoon–ENSO links in the IPCC AR4 projections: A cautionary outlook

The climate change experiments under the fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC), namely the twentieth century simulations (20C3M) and Special Report on Emissions Scenarios (SRES) A1B, are revisited to study whether these models can reproduce the ENSO and ENSO Modoki patterns as the two important modes from statistical linear analysis as observed. The capability of the models in simulating realistic ENSO/ENSO Modoki teleconnections with the Indian summer monsoon, and also the implications for the future are also explored. Results from the study indicate that only ~1/4th of the models from 20C3M capture either ENSO or ENSO Modoki pattern in JJAS. Of this 1/4th, only two models simulate both ENSO and ENSO Modoki as important modes. Again, out of these two, only one model simulates both ENSO and ENSO Modoki as important modes during both summer and winter.It is also shown that the two models that demonstrate ENSO Modoki as well as ENSO associated variance in both 20C3M and SRESA1B represent the links of the ISMR with ENSO reasonably in 20C3M, but indicate opposite type of impacts in SREA1B. With the limited skills of the models in reproducing the monsoon, the ENSO and ENSO Modoki, it is difficult to reconcile that the teleconnections of a tropical driver can change like that. All these indicate the challenges associated with the limitations of the models in reproducing the variability of the monsoons and ENSO flavors, not to speak of failing in capturing the potential impacts of global warming as they are expected to. More research in improving the current day simulations, improving model capacity to simulate better by improving the Green House Gases (GHG) and aerosols in the models are some of the important and immediate steps that are necessary.

Estimating climate change, CO2 and technology development effects on wheat yield in northeast Iran

Wheat is the main food for the majority of Iran's population. Precise estimation of wheat yield change in future is essential for any possible revision of management strategies. The main objective of this study was to evaluate the effects of climate change, CO2 concentration, technology development and their integrated effects on wheat production under future climate change. This study was performed under two scenarios of the IPCC Special Report on Emission Scenarios (SRES): regional economic (A2) and global environmental (B1). Crop production was projected for three future time periods (2020, 2050 and 2080) in comparison with a baseline year (2005) for Khorasan province located in the northeast of Iran. Four study locations in the study area included Mashhad, Birjand, Bojnourd and Sabzevar. The effect of technology development was calculated by fitting a regression equation between the observed wheat yields against historical years considering yield potential increase and yield gap reduction as technology development. Yield relative increase per unit change of CO2 concentration (1ppm(-1)) was considered 0.05% and was used to implement the effect of elevated CO2. The HadCM3 general circulation model along with the CSM-CERES-Wheat crop model were used to project climate change effects on wheat crop yield. Our results illustrate that, among all the factors considered, technology development provided the highest impact on wheat yield change. Highest wheat yield increase across all locations and time periods was obtained under the A2 scenario. Among study locations, Mashhad showed the highest change in wheat yield. Yield change compared to baseline ranged from -28% to 56% when the integration of all factors was considered across all locations. It seems that achieving higher yield of wheat in future may be expected in northeast Iran assuming stable improvements in production technology.

Assessment of Climate Change Impact on the Gharesou River Basin Using SWAT Hydrological Model

AbstractThe evaluation of climate change and its side effects on the hydrological processes of the basin can increasingly help in dealing with the challenges that water resource managers and planners face in future courses. These side effects are investigated using the simulation of hydrological processes with the help of physical rainfall‐runoff model. Hydrological models provide a framework for examining the relationship between climate and water resources. This research aims at the investigation of the effect of climate change on the runoff of Gharesou, which is one of the main branches of the “Karkheh” River in Iran during the periods 2040–2069. To achieve this, the distributed hydrological model Soil and Water Assessment Tool (SWAT) – a model that is sensitive to the changes in land, water, and climate – has been used with the aim of evaluating the impact of climate change on the hydrology of the Gharesou Basin. For this reason, first, the continuous distributed model of rainfall‐runoff SWAT for the period 1971–2000 has been calibrated and validated. Next, with the aim of evaluating the impact of climate change and global warming on the basin hydrology for the period 2040–2069, HadCM3‐AR4 global climate model data under the A2 scenario – from the SRES scenario set‐haves been downscaled. Eventually, the downscaled climate data haves been introduced in the SWAT model, and the future runoff changes have been studied. The results showed that the temperature increases in most of the months, and the precipitation rate exhibits a change in the range of ±30%. Moreover, the produced runoff in this period changes from −90 to 120% during different months.