A2 Emission Scenarios Research Articles

Statistical downscaling of general circulation model outputs to precipitation, evaporation and temperature using a key station approach

Using a key station approach, statistical downscaling of monthly general circulation model outputs to monthly precipitation, evaporation, minimum temperature and maximum temperature at 17 observation stations located in Victoria, Australia was performed. Using the observations of each predictand, over the period 1950–2010, correlations among all stations were computed. For each predictand, the station which showed the highest number of correlations above 0.80 with other stations was selected as the first key station. The stations that were highly correlated with that key station were considered as the member stations of the first cluster. By employing this same procedure on the remaining stations, the next key station was found. This procedure was performed until all stations were segregated into clusters. Thereafter, using the observations of each predictand, regression equations (inter-station regression relationships) were developed between the key stations and the member stations for each calendar month. The downscaling models at the key stations were developed using reanalysis data as inputs to them. The outputs of HadCM3 pertaining to A2 emission scenario were introduced to these downscaling models to produce projections of the predictands over the period 2000–2099. Then the outputs of these downscaling models were introduced to the inter-station regression relationships to produce projections of predictands at all member stations.

OPTIMIZED SHIFTS IN SOWING TIMES OF FIELD CROPS TO THE PROJECTED CLIMATE CHANGES IN AN AGRO-CLIMATIC ZONE OF PAKISTAN

SUMMARYThis paper evaluates 30-year (2013–2042) projections of the selected climatic parameters in cotton/wheat agro-climatic zone of Pakistan. A statistical bias correction procedure was adopted to eliminate the systematic errors in output of three selected general circulation models (GCM) under A2 emission scenario. A transfer function was developed between the GCM outputs and the observed time series of the climatic parameters (base period: 1980–2004) and applied to GCM future projections. The predictions detected seasonal shifts in rainfall and increasing temperature trend which in combination can affect the crop water requirements (CWR) at different phonological stages of the two major crops (i.e. wheat and cotton). CROPWAT model is used to optimize the shifts in sowing dates as a climate change adaptation option. The results depict that with reference to the existing sowing patterns, early sowing of wheat and late sowing of cotton will favour decreased CWR of these crops.

Modelling the current and potential future distributions of the sunn pest Eurygaster integriceps (Hemiptera: Scutelleridae) using CLIMEX

The sunn pest, Eurygaster integriceps (Hemiptera: Scutelleridae), is an economically significant pest throughout Western Asia and Eastern Europe. This study was conducted to examine the possible risk posed by the influence of climate change on its spread. CLIMEX software was used to model its current global distribution. Future invasion potential was investigated using two global climate models (GCMs), CSIRO-Mk3.0 (CS) and MIROC-H (MR), under A1B and A2 emission scenarios for 2030, 2070 and 2100. Dry to temperate climatic areas favour sunn pests. The potential global range for E. integriceps is expected to extend further polewards between latitudes 60° N and 70° N. Northern Europe and Canada will be at risk of sunn pest invasion as cold stress boundaries recede under the emission scenarios of these models. However, current highly suitable areas, such as South Africa and central Australia, will contract where precipitation is projected to decrease substantially with increased heat stress. Estimating the sunn pest's potential geographic distribution and detecting its climatic limits can provide useful information for management strategies and allow biosecurity authorities to plan ahead and reduce the expected harmful economic consequences by identifying the new areas for pest invasion. © 2016 Society of Chemical Industry.

Potential change in forest types and stand heights in central Siberia in a warming climate

Previous regional studies in Siberia have demonstrated climate warming and associated changes in distribution of vegetation and forest types, starting at the end of the 20th century. In this study we used two regional bioclimatic envelope models to simulate potential changes in forest types distribution and developed new regression models to simulate changes in stand height in tablelands and southern mountains of central Siberia under warming 21st century climate. Stand height models were based on forest inventory data (2850 plots). The forest type and stand height maps were superimposed to identify how heights would change in different forest types in future climates. Climate projections from the general circulation model Hadley HadCM3 for emission scenarios B1 and A2 for 2080s were paired with the regional bioclimatic models. Under the harsh A2 scenario, simulated changes included: a 80%–90% decrease in forest-tundra and tundra, a 30% decrease in forest area, a ∼400% increase in forest-steppe, and a 2200% increase in steppe, forest-steppe and steppe would cover 55% of central Siberia. Under sufficiently moist conditions, the southern and middle taiga were simulated to benefit from 21st century climate warming. Habitats suitable for highly-productive forests (≥30–40 m stand height) were simulated to increase at the expense of less productive forests (10–20 m). In response to the more extreme A2 climate the area of these highly-productive forests would increase 10%–25%. Stand height increases of 10 m were simulated over 35%–50% of the current forest area in central Siberia. In the extremely warm A2 climate scenario, the tall trees (25–30 m) would occur over 8%–12% of area in all forest types except forest-tundra by the end of the century. In forest-steppe, trees of 30–40 m may cover some 15% of the area under sufficient moisture.

Projecting water yield and ecosystem productivity across the United States by linking an ecohydrological model to WRF dynamically downscaled climate data

Abstract. Quantifying the potential impacts of climate change on water yield and ecosystem productivity is essential to developing sound watershed restoration plans, and ecosystem adaptation and mitigation strategies. This study links an ecohydrological model (Water Supply and Stress Index, WaSSI) with WRF (Weather Research and Forecasting Model) using dynamically downscaled climate data of the HadCM3 model under the IPCC SRES A2 emission scenario. We evaluated the future (2031–2060) changes in evapotranspiration (ET), water yield (Q) and gross primary productivity (GPP) from the baseline period of 1979–2007 across the 82 773 watersheds (12-digit Hydrologic Unit Code level) in the coterminous US (CONUS). Across the CONUS, the future multi-year means show increases in annual precipitation (P) of 45 mm yr−1 (6 %), 1.8° C increase in temperature (T), 37 mm yr−1 (7 %) increase in ET, 9 mm yr−1 (3 %) increase in Q, and 106 gC m−2 yr−1 (9 %) increase in GPP. We found a large spatial variability in response to climate change across the CONUS 12-digit HUC watersheds, but in general, the majority would see consistent increases all variables evaluated. Over half of the watersheds, mostly found in the northeast and the southern part of the southwest, would see an increase in annual Q (> 100 mm yr−1 or 20 %). In addition, we also evaluated the future annual and monthly changes of hydrology and ecosystem productivity for the 18 Water Resource Regions (WRRs) or two-digit HUCs. The study provides an integrated method and example for comprehensive assessment of the potential impacts of climate change on watershed water balances and ecosystem productivity at high spatial and temporal resolutions. Results may be useful for policy-makers and land managers to formulate appropriate watershed-specific strategies for sustaining water and carbon sources in the face of climate change.

Circulation patterns related to debris-flow triggering in the Zermatt valley in current and future climates

The principal objective of this study was to investigate the types of large-scale meteorological situations that are conducive to the precipitation and temperature conditions most likely to trigger debris flows in the Zermatt valley, Switzerland, under current and future climates. A two-dimensional Bayesian probability calculation was applied to take account of uncertainties in debris-flow triggering. Precipitation quantities exceeding the 95th percentile of daily precipitation amounts were found to have a significantly higher probability to coincide with observed debris flows. A different relationship exists for extreme temperatures, however. Southerly air flows, weak horizontal pressure gradients over Europe, and westerly flows are mostly associated with observed debris flows and 95th precipitation percentile exceedances. These principal flow directions are well represented in the regional climate model (RCM) HIRHAM control simulations for events exceeding the 95th precipitation percentile and the 30th temperature percentile. Under the IPCC A2 emission scenario, westerly and southerly flows are mostly responsible for these precipitation and temperature conditions under the hypothesis of slow adaptation to climate change (HS1/HC1). Under the hypothesis of rapid adaptation to climate change (HS1/HS1), southerly flows and weak horizontal pressure gradients are likely to gain in importance. In both scenarios for the future, southeasterly flows are among the principal flow directions responsible for the joint exceedance of the 95th precipitation percentile and the 30th temperature percentile, while these were absent in observations and the control simulation.

Analyses of Observed and Anticipated Changes in Extreme Climate Events in the Northwest Himalaya

In this study, past (1970-2005) as well as future long term (2011-2099) trends in various extreme events of temperature and precipitation have been investigated over selected hydro-meteorological stations in the Sutlej river basin. The ensembles of two Coupled Model Intercomparison Project (CMIP3) models: third generation Canadian Coupled Global Climate Model and Hadley Centre Coupled Model have been used for simulation of future daily time series of temperature (maximum and minimum) and precipitation under A2 emission scenario. Large scale atmospheric variables of both models and National Centre for Environmental Prediction/National Centre for Atmospheric Research reanalysis data sets have been downscaled using statistical downscaling technique at individual stations. A total number of 25 extreme indices of temperature (14) and precipitation (11) as specified by the Expert Team of the World Meteorological Organization and Climate Variability and Predictability are derived for the past and future periods. Trends in extreme indices are detected over time using the modified Mann-Kendall test method. The stations which have shown either decrease or no change in hot extreme events (i.e., maximum TMax, warm days, warm nights, maximum TMin, tropical nights, summer days and warm spell duration indicators) for 1970–2005 and increase in cold extreme events (cool days, cool nights, frost days and cold spell duration indicators) are predicted to increase and decrease respectively in the future. In addition, an increase in frequency and intensity of extreme precipitation events is also predicted.

Copula-based bivariate flood frequency analysis in a changing climate—A case study in the Huai River Basin, China

Copula-based bivariate frequency analysis can be used to investigate the changes in flood characteristics in the Huai River Basin that could be caused by climate change. The univariate distributions of historical flood peak, maximum 3-day and 7-day volumes in 1961–2000 and future values in 2061–2100 projected from two GCMs (CSIRO-MK3.5 and CCCma-CGCM3.1) under A2, A1B and B1 emission scenarios are analyzed and compared. Then, bivariate distributions of peaks and volumes are constructed based on the copula method and possible changes in joint return periods are characterized. Results indicate that the Clayton copula is more appropriate for historical and CCCma-CGCM3.1 simulating flood variables, while that of Frank and Gumbel are better fitted to CSIRO-MK3.5 simulations. The variations of univariate and bivariate return periods reveal that flood characteristics may be more sensitive to different GCMs than different emission scenarios. Between the two GCMs, CSIRO-MK3.5 evidently predicts much more severe flood conditions in future, especially under B1 scenario, whereas CCCma-CGCM3.1 generally suggests contrary changing signals. This study corroborates that copulas can serve as a viable and flexible tool to connect univariate marginal distributions of flood variables and quantify the associated risks, which may provide useful information for risk-based flood control.

Regional climate change scenarios applied to viticultural zoning in Mendoza, Argentina.

Due to the importance of the winemaking sector in Mendoza, Argentina, the assessment of future scenarios for viticulture is of foremost relevance. In this context, it is important to understand how temperature increase and precipitation changes will impact on grapes, because of changes in grapevine phenology and suitability wine-growing regions must be understood as an indicator of climate change. The general objective is to classify the suitable areas of viticulture in Argentina for the current and future climate using the MM5 regional climate change simulations. The spatial distribution of annual mean temperature, annual rainfall, and some bioclimatic indices has been analyzed for the present (1970-1989) and future (2080-2099) climate under SRES A2 emission scenario. In general, according to projected average growing season temperature and Winkler index classification, the regional model estimates (i) a reduction of cool areas, (ii) a westward and southward displacement of intermediate and warm suitability areas, and (iii) the arise of new suitability regions (hot and very hot areas) over Argentina. In addition, an increase of annual accumulated precipitation is projected over the center-west of Argentina. Similar pattern of change is modeled for growing season, but with lower intensity. Furthermore, the evaluation of projected seasonal precipitation shows a little precipitation increase over Cuyo and center of Argentina in summer and a little precipitation decrease over Cuyo and northern Patagonia in winter. Results show that Argentina has a great potential for expansion into new suitable vineyard areas by the end of twenty-first century, particularly due to projected displacement to higher latitudes for most present suitability winegrowing regions. Even though main conclusions are based on one global-regional model downscaling, this approach provides valuable information for implementing proper and diverse adaptation measures in the Argentinean viticultural regions. It has been concluded that regional climate change simulations are an adequate methodology, and indeed, the MM5 regional model is an appropriate tool to be applied in viticultural zoning in Mendoza, Argentina.

Assessment of climate change impacts on river hydrology and habitat suitability of Oxynoemacheilus bergianus. Case study: Kordan River, Iran

Iran is located in a geographical location that is not immune from climate change effects. Therefore, it is necessary to assess the influence of climate change on water resources since this part of the ecosystem is the first component that will be affected by climate change. The main purpose of this study is to assess climate change impacts on environmental flows by using hydrological indicators in Kordan River, Iran. In this regard, at first, the future climate change in the region was projected by using HadCM3 general circulation model in three 30-year periods, 2011–2040, 2041–2070, and 2071–2099, considering the A2 and B1 emission scenarios. Afterwards, Kordan River streamflow was simulated by using the SWAT model for the baseline period (1985–2010) and the future and hydrological indicators, such as magnitude, duration, timing, and frequency of extreme flows, were analyzed. Results showed a reduction in discharge. Under the A2 scenario, discharge decreased from 3.31 to 2.66 m3/s, while under the B1 scenario, this reduction was up to 2.86 m3/s for 100 years into the future. In addition to reduction of discharge, the occurrence time of maximum and minimum flows is projected to change as well. This phenomenon will change the habitat suitability and introduce some risks for aquatic life. Finally, in order to analyze Kordan River habitat suitability, we chose Oxynoemacheilus bergianus, which can be a suitable index for the ecosystem. In this regard, Habitat Suitability Index (HSI) was used, which is obtained based on river characteristics such as water depth, velocity, and water temperature. According to the results, the percentage of time that HSI is at a rate between 0.4 and 0.6 is expected to decrease from 100–70% to 80–60% under both scenarios by 2071–2099.

Impacts of future climate change on river discharge based on hydrological inference: A case study of the Grand River Watershed in Ontario, Canada

Over the recent years, climate change impacts have been increasingly studied at the watershed scale. However, the impact assessment is strongly dependent upon the performance of the climatic and hydrological models. This study developed a two-step method to assess climate change impacts on water resources based on the Providing Regional Climates for Impacts Studies (PRECIS) modeling system and a Hydrological Inference Model (HIM). PRECIS runs provided future temperature and precipitation projections for the watershed under the Intergovernmental Panel on Climate Change SRES A2 and B2 emission scenarios. The HIM based on stepwise cluster analysis is developed to imitate the complex nonlinear relationships between climate input variables and targeted hydrological variables. Its robust mathematical structure and flexibility in predictor selection makes it a desirable tool for fully utilizing various climate modeling outputs. Although PRECIS and HIM cannot fully cover the uncertainties in hydro-climate modeling, they could provide efficient decision support for investigating the impacts of climate change on water resources. The proposed method is applied to the Grand River Watershed in Ontario, Canada. The model performance is demonstrated with comparison to observation data from the watershed during the period 1972–2006. Future river discharge intervals that accommodate uncertainties in hydro-climatic modeling are presented and future river discharge variations are analyzed. The results indicate that even though the total annual precipitation would not change significantly in the future, the inter-annual distribution is very likely to be altered. The water availability is expected to increase in Winter while it is very likely to decrease in Summer over the Grand River Watershed, and adaptation strategies would be necessary.

Hydrological Impact Assessment of Climate Change on Lake Tana’s Water Balance, Ethiopia

The aim of this study is to evaluate the hydrological impacts of climate change on the water balance of Lake Tana in Ethiopia. Impact assessments are by downscaled General Circulation Model (GCM) output and hydrological modeling. For A2 and B2 emission scenarios, precipitation, maximum and minimum temperature estimates from the HadCM3 GCM were used. GCM output was downscaled using the Statistical DownScaling Model (SDSM 4.2). Impact analyses were applied for three future time periods: early, mid and late 21st century. Over-lake evaporation is estimated by Hardgrave’s method, and over-lake precipitation is estimated by inverse distance weighing interpolation, whereas inflows from gauged and ungauged catchments are simulated by the HBV hydrological model. Findings indicate increases in maximum and minimum temperature on annual base for both emission scenarios. The projection of mean annual over lake precipitation for both A2 and B2 emission scenarios shows increasing pattern for 21st century in comparison to the baseline period. The increase of mean annual precipitation for A2 emission scenario is 9% (112 mm/year), 10% (125 mm/year) and 11% (137 mm/year) for the three future periods respectively. B2 emission scenario mean annual precipitation shows increase by 9% (111 mm/year), 10% (122 mm/year) and 10% (130 mm/year) respectively for the three future periods. Findings indicate consistent increases of lake storage for all three future periods for both A2 and B2 emission scenarios.

Variation of water resources indices in a changing climate

Climate change affects on different hydrological and meteorological parameters. This study investigates the effects of climate change on temperature, precipitation, evapotranspiration and runoff in the Zayandeh-Rud River Basin, Iran. 15 GCM models of Fourth Assessment Report of the IPCC (AR4) was used for prediction the effects of climate change. Three climate change pattern (ideal, medium and critical) were defined based on weighting method. Seasonal and annual changes in temperature showed that summer has the maximum and autumn has the minimum temperature increase. Decreasing the precipitation from -2.59% to -29.82% observed in all climate change patterns. Evapotranspiration changes by 6.8%-7.8% in different climate change patterns. Also, the surface runoff decreased for ideal, medium and critical patterns. Ratio of evapotranspiration in the East of the basin to precipitation in the West part was considered as an indicator of agricultural water balance (EPR). The amount of EPR index of ideal, medium and critical patterns respectively obtained as 26, 43 and 52% in the A2 emission scenario and 13, 25 and 36% in the B1 emission scenario. The results showed that, in this region, water resources management is essential due to the lack of water resources in the future.

Development of an Integrated Agricultural Planning Model Considering Climate Change

The goal of this study is to develop an agriculture planning model in order to sustain the future water use under the estimation of crop water requirement, water availability and future climate projection. For this purpose, the Citarum river basin which is located in West Java - Indonesia is selected as the study area. Two emission scenarios A2 and B2 were selected. For the crop water requirement estimation, the output of HadCM3 AOGCM is statistically downscale using SDSM and used as the input for WEAP model developed by SEI (Stockholm Environmental Institute). The reliability of water uses is assessed by comparing the irrigation water demand and the water allocation for the irrigation area. The water supply resources are assessed using the water planning tool. This study shows that temperature and precipitation over the study area are projected to increase in the future. The water availability was projected to increase under both A2 and B2 emission scenarios in the future. The irrigation water requirement is expected to decrease in the future under A2 and B2 scenarios. By comparing the irrigation water demand and water allocation for irrigation, the reliability of agriculture water use is expected to change in the period of 2050s and 2080s while the reliability will not change in 2020s. The reliability under A2 scenario is expected to be higher than B2 scenario. The combination of WEAP and SDSM is significance to use in assessing and allocating the water resources in the region.

Regional climate change scenarios over southern South America for future climate (2080-2099) using the MM5 Model. Mean, interannual variability and uncertainties

This work focuses on evaluating the climate change projected by the end of the 21st century under the SRES A2 emission scenario over southern South America using the regional model MM5. The model projects: (i) an increase of precipitation over central Argentina, Uruguay and southern Brazil during summer and fall; (ii) a decrease in precipitation over most of the study domain during winter and spring; (iii) an important decrease in precipitation over central and southern Chile, through the year. In general, the projected temperature increase depends on the season and the examined area; particularly, it is highest over tropical and subtropical latitudes in spring and over high latitudes in summer. The MM5 model projects: (i) an increase of the interannual precipitation variability of precipitation over central Argentina and Uruguay regardless the season; (ii) a slight decrease in interannual temperature variability over large extents of Argentina for summer and winter; (iii) a slight increase in interannual temperature variability at transition seasons; with highest values over central Chile in autumn and over north central Argentina in spring. From the reliability assessment of regional climate projections, it can be concluded that signal-to-noise ratio is high for temperature and low for precipitation. Therefore, the MM5 model is a useful tool in the generation of regional climate change scenarios of high resolution over southern South America, particularly for temperature, and is a starting point to perform studies related to impacts of climate change.

Crop niche modeling projects major shifts in common bean growing areas

Crops experience different climate stresses during development. The magnitude of damage will depend on the phenological stage of the crop and the stress duration. Climate change could intensify some or all of these stresses, thus negatively impacting agriculture. An assessment of staple crop productivity, quality and climatically suitable areas under climate change conditions is necessary to undertake any global initiatives to tackle food security issues. The common bean (Phaseolus vulgaris L.) is a staple crop and the main source of proteins and nutrients in Africa and Latin America. The purpose of this study is to develop a process-oriented niche model to assess the impacts of climate change on the current and future potential distribution of common bean and to use this model to investigate the changes in heat, cold, dry and wet stresses under climate change. We used A2 and A1B emission scenarios and two different global climate models, CSIRO-Mk3.0 and MIROC-H, for the years 2050 and 2100. Our results indicate future climate conditions are more favorable for common bean cultivation in the Northern Hemisphere, but are less favorable in the Southern Hemisphere. Heat and dry stresses are the main factors limiting and reducing common bean distribution under current and future projected conditions. Africa and Latin America are projected to decrease with respect to suitability for common bean cultivation. The model projections indicate that a shift in the common bean productive areas is highly likely with a loss of suitability of the current common bean cultivation areas and an increase in cold regions such as Canada, the Nordic countries and Russia. The results indicate the likelihood of changes in climatic suitability and the distribution of common bean at a global scale under a future climate, which will affect regions where this legume is a staple crop and an important source of household income. Regions in the Northern Hemisphere could take advantage of the increase in suitability by increasing the production and exportation of this grain.

Impact of future climates on the durability of typical residential wall assemblies retrofitted to the PassiveHaus for the Eastern Canada region

Attention to the global warming has influenced many aspects of human activities. Worldwide effort toward energy consumption reduction in building sector is one of the areas affected by climate change. Building regulations demand the building construction industry to be more energy efficient. Studies have been carried out on the thermal performance of energy efficient buildings under future climates, while studies on the durability of energy efficient building envelopes over future climates are limited. This study assesses the impact of future climates on the durability of typical Canadian residential wall assemblies retrofitted to the PassiveHaus over the current, 2020, 2050, and 2080 climatic conditions for Montreal. The durability performance is evaluated in terms of the frost damage risk of bricks and the biodegradation risk of plywood sheathing through simulations using WUFI Pro program. The future weather files are generated based on weather data recorded at the Montreal International Airport weather station using General Circulation Model HadCM3 based on the A2 emission scenario by the Intergovernmental Panel on Climate Change. This study concludes that upgrading wall assemblies to the PassiveHaus recommended level would increase the frost damage risk of bricks, however, this risk would decrease under 2080 climatic conditions. While the decay risk of the plywood sheathing would decrease, the mould growth risk defined by RHT criteria would increase over future climates. Under future climates, mould growth risks of the plywood defined by the mould growth index exist only when rain leakage is introduced and would likely decrease for the double-stud assembly.

Projected changes in atmospheric river events in Arizona as simulated by global and regional climate models

Inland-penetrating atmospheric rivers (ARs) affect the United States Southwest and significantly contribute to cool season precipitation. In this study, we examine the results from an ensemble of dynamically downscaled simulations from the North American Regional Climate Change Assessment Program (NARCCAP) and their driving general circulation models (GCMs) in order to determine statistically significant changes in the intensity of the cool season ARs impacting Arizona and the associated precipitation. Future greenhouse gas emissions follow the A2 emission scenario from the Intergovernmental Panel on Climate Change Fourth Assessment Report simulations. We find that there is a consistent and clear intensification of the AR-related water vapor transport in both the global and regional simulations which reflects the increase in water vapor content due to warmer atmospheric temperatures, according to the Clausius-Clapeyron relationship. However, the response of AR-related precipitation intensity to increased moisture flux and column-integrated water vapor is weak and no significant changes are projected either by the GCMs or the NARCCAP models. This lack of robust precipitation variations can be explained in part by the absence of meaningful changes in both the large-scale water vapor flux convergence and the maximum positive relative vorticity in the GCMs. Additionally, some global models show a robust decrease in relative humidity which may also be responsible for the projected precipitation patterns.

An integrated statistical and data-driven framework for supporting flood risk analysis under climate change

Summary An integrated statistical and data-driven (ISD) framework was proposed for analyzing river flows and flood frequencies in the Duhe River Basin, China, under climate change. The proposed framework involved four major components: (i) a hybrid model based on ASD (Automated regression-based Statistical Downscaling tool) and KNN (K-nearest neighbor) was used for downscaling rainfall and CDEN (Conditional Density Estimate Network) was applied for downscaling minimum temperature and relative humidity from global circulation models (GCMs) to local weather stations; (ii) Bayesian neural network (BNN) was used for simulating monthly river flows based on projected weather information; (iii) KNN was applied for converting monthly flow to daily time series; (iv) Generalized Extreme Value (GEV) distribution was adopted for flood frequency analysis. In this study, the variables from CGCM3 A2 and HadCM3 A2 scenarios were employed as the large-scale predictors. The results indicated that the maximum monthly and annual runoffs would both increase under CGCM3 and HadCM3 A2 emission scenarios at the middle and end of this century. The flood risk in the study area would generally increase with a widening uncertainty range. Compared with traditional approaches, the proposed framework takes the full advantages of a series of statistical and data-driven methods and offers a parsimonious way of projecting flood risks under climatic change conditions.

Climate change impacts on streamflow and sediment yield in the North of Iran

Climate change will accelerate the hydrological cycle, altering rainfall, and the magnitude and timing of runoff. The purpose of this paper is to assess the impacts of climate change on streamflow and sediment yield from the Gorganroud river basin in the North of Iran. To study the effects of climatic variations, the SWAT model was implemented to simulate the hydrological regime and the SUFI-2 algorithm was used for parameter optimization. The climate change scenarios were constructed using the outcomes of three general circulation models for three emission scenarios. The study results for 2040–2069 showed an increase in annual streamflow of 5.8%, 2.8% and 9.5% and an increase in sediment yield of 47.7%, 44.5% and 35.9% for the A1F1, A2 and B1 emission scenarios, respectively. This implies that the impact of climate change on sediment yield is greater than on streamflow. Monthly variations show that the increase in discharge and sediment yield is more pronounced in wet seasons and the decrease is more pronounced in summer (July–September). The results highlighted the strong impact of climate change and reflected the importance of incorporating such analysis into adaptive management.Editor Z.W. Kundzewicz Associate editor Not assigned