B1 Scenarios Research Articles

Irrigation water requirements for seed corn and coffee under potential climate change scenarios

The impact of potential future climate change scenarios on the irrigation water requirements (IRRs) of two major agricultural crops (coffee and seed corn) in Hawai'i was studied using the Irrigation Management System (IManSys) model. In addition to IRRs calculations, IManSys calculates runoff, deep percolation, canopy interception, and effective rainfall based on plant growth parameters, site specific soil hydrological properties, irrigation system efficiency, and long-term daily weather data. Irrigation water requirements of two crops were simulated using historical climate data and different levels of atmospheric CO2 (330, 550, 710 and 970 ppm), temperature (+1.1 and +6.4 °C) and precipitation (±5, ±10 and ±20%) chosen based on the Intergovernmental Panel on Climate Change (IPCC) AR4 projections under reference, B1, A1B1 and A1F1 emission scenarios. IRRs decreased as CO2 emission increased. The average percentage decrease in IRRs for seed corn is higher than that of coffee. However, runoff, rain canopy interception, and deep percolation below the root zone increased as precipitation increased. Canopy interception and drainage increased with increased CO2 emission. Evapotranspiration responded positively to air temperature rise, and as a result, IRRs increased as well. Further studies using crop models will predict crop yield responses to these different irrigation scenarios.

Ecosystem carbon stocks and sequestration potential of federal lands across the conterminous United States.

Federal lands across the conterminous United States (CONUS) account for 23.5% of the CONUS terrestrial area but have received no systematic studies on their ecosystem carbon (C) dynamics and contribution to the national C budgets. The methodology for US Congress-mandated national biological C sequestration potential assessment was used to evaluate ecosystem C dynamics in CONUS federal lands at present and in the future under three Intergovernmental Panel on Climate Change Special Report on Emission Scenarios (IPCC SRES) A1B, A2, and B1. The total ecosystem C stock was estimated as 11,613 Tg C in 2005 and projected to be 13,965 Tg C in 2050, an average increase of 19.4% from the baseline. The projected annual C sequestration rate (in kilograms of carbon per hectare per year) from 2006 to 2050 would be sinks of 620 and 228 for forests and grasslands, respectively, and C sources of 13 for shrublands. The federal lands' contribution to the national ecosystem C budget could decrease from 23.3% in 2005 to 20.8% in 2050. The C sequestration potential in the future depends not only on the footprint of individual ecosystems but also on each federal agency's land use and management. The results presented here update our current knowledge about the baseline ecosystem C stock and sequestration potential of federal lands, which would be useful for federal agencies to decide management practices to achieve the national greenhouse gas (GHG) mitigation goal.

Pastoral suitability driven by future climate change along the Apennines

This work aims at evaluating the impacts of climate change on pastoral resources located along the Apennines chain. To this end, random forest machine learning model was first calibrated for the present period and then applied to future conditions, as projected by HadCM3 general circulation model, in order to simulate possible spatial variation/shift of pastoral areas in two time slices (centred on 2050 and 2080) under A2 and B2 SRES scenarios. Pre-existent spatial database, namely Corine land cover map and WorldClim, were integrated and harmonised in a GIS environment in order to extract climate variables (mean seasonal precipitation, mean maximum temperature of the warmest month and minimum temperature of the coldest month) and response variables (presence/absence of pastures) to be used as model predictors. Random forest model resulted robust and coherent to simulate pastureland suitability under current climatology (classification accuracy error=19%). Accordingly, results indicated that increases in temperatures coupled with decreases in precipitation, as simulated by HadCM3 in the future, would have impacts of great concern on potential pasture distribution. In the specific, an overall decline of pasturelands suitability is predicted by the middle of the century in both A2 (–46%) and B2 (–41%) along the entire chain. However, despite alarming reductions in pastures suitability along the northern (–69% and –71% under A2 and B2 scenarios, respectively) and central Apennines (–90% under both scenarios) by the end of the century, expansions are predicted along the southern areas of the chain (+96% and +105% under A2 and B2 scenarios, respectively). This may be probably due to expansions in pastures dominated by xeric and thermophiles species, which will likely benefit from warmer and drier future conditions predicted in the southern zone of the chain by the HadCM3. Hence, the expected climate, coupled with an increasing abandonment of the traditional grazing practices, will likely threat grassland biodiversity as well as pastoral potential distribution currently dominating the Apennines chain.

Combined analysis of climate, technological and price changes on future arable farming systems in Europe

In this study, we compare the relative importance of climate change to technological, management, price and policy changes on European arable farming systems. This required linking four models: the SIMPLACE crop growth modelling framework to calculate future yields under climate change for arable crops; the CAPRI model to estimate impacts on global agricultural markets, specifically product prices; the bio-economic farm model FSSIM to calculate the future changes in cropping patterns and farm net income at the farm and regional level; and the environmental model INTEGRATOR to calculate nitrogen (N) uptake and losses to air and water. First, the four linked models were applied to analyse the effect of climate change only or a most likely baseline (i.e. B1) scenario for 2050 as well as for two alternative scenarios with, respectively, strong (i.e. A1-b1) and weak economic growth (B2) for five regions/countries across Europe (i.e. Denmark, Flevoland, Midi Pyrenées, Zachodniopomorski and Andalucia). These analyses were repeated but assuming in addition to climate change impacts, also the effects of changes in technology and management on crop yields, the effects of changes in prices and policies in 2050, and the effects of all factors together. The outcomes show that the effects of climate change to 2050 result in higher farm net incomes in the Northern and Northern–Central EU regions, in practically unchanged farm net incomes in the Central and Central–Southern EU regions, and in much lower farm net incomes in Southern EU regions compared to those in the base year. Climate change in combination with improved technology and farm management and/or with price changes towards 2050 results in a higher to much higher farm net incomes. Increases in farm net income for the B1 and A1-b1 scenarios are moderately stronger than those for the B2 scenario, due to the smaller increases in product prices and/or yields for the B2 scenario. Farm labour demand slightly to moderately increases towards 2050 as related to changes in cropping patterns. Changes in N2O emissions and N leaching compared to the base year are mainly caused by changes in total N inputs from the applied fertilizers and animal manure, which in turn are influenced by changes in crop yields and cropping patterns, whereas NH3 emissions are mainly determined by assumed improvements in manure application techniques. N emissions and N leaching strongly increase in Denmark and Zachodniopomorski, slightly decrease to moderately increase in Flevoland and Midi-Pyrenées, and strongly decrease in Andalucia, except for NH3 emissions which zero to moderately decrease in Flevoland and Denmark.

Assessing sustainability of winter wheat production under climate change scenarios in a humid climate — An integrated modelling framework

The proposed study draws a novel framework to assess the sustainability of winter wheat under climate change conditions and irrigation as an adaption measure to reduce yield variability. The methodology combines outputs from a general circulation model (GCM), the Food and Agriculture Organization's (FAO) crop growth model (AquaCrop), a life cycle assessment (LCA) model and economic modelling. Long-term observed climate data (1970–1991) collected in Cambridge (Cambridgeshire, UK) were used to downscale the projected climate data from the GCM for 2050. The structural characteristics of the case study are representative of a typical farm in this UK region. A six-year average wheat price (2007–2012) was considered and the irrigation costs for the economic model were calculated assuming the market prices in 2014. Sensitivity analysis assessed in the longer term included the expected variations due to the increase in world wheat prices and the energy costs.The direct impacts of climate change on winter wheat grown in the East of England, would be a reduction in the rainfed yield (between −5.4% and −32.9%), stronger under the low emission scenario (B1). The projected economic losses from rainfed winter wheat production are expected to range between −43.6% and −100.0%. Irrigation could in the future be an adaptation measure for yield increase (10.5% to 64.3%), lower under B1 and to improve the financial appraisal of irrigation investment which would raise between 41 and 429£ha−1. However, negative externalities are exacerbating pressures on air and water resources; an increase in irrigation water requirements between 25.0% and 39.1% increases global warming potential between 20.4% and 28.3%. Environmental indicators under scenario B1 performed better than the high emission scenario (A1). Finally, under future climate scenarios, the results confirmed that irrigated winter wheat grown on lighter soils using hose reel sprinkler systems fitted with a boom, is more sustainable than that grown on heavier soils using hose reel sprinkler systems fitted with a raingun.

Impacts of sugarcane ethanol production in the Paranaiba basin water resources

This study evaluates the impacts of sugarcane cultivation for ethanol production on water availability in a watershed located in the Center-West of Brazil, using the water footprint (WF) indicator. We assessed i) the green, blue and gray WF of sugarcane produced in Paranaíba basin in baseline (year 2010) and GHG emission scenarios (year 2020) under rainfed and full irrigation conditions; ii) the green, blue and gray WF of sugarcane ethanol produced in Paranaíba basin in 2010, and iii) the impact of the water demand for different sugarcane plantation scenarios on the context of water availability. Differences between full irrigated and rainfed sugarcane growing conditions resulted in different crop evapotranspiration, yields and WFs. For baseline scenario the WF of sugarcane was evaluated around 142 m3 t−1 (full irrigation) and 151 m3 t−1 (rainfed). For GHG emission scenarios was around 137 m3 t−1 (full irrigation) and 139 m3 t−1 (rainfed), in scenario A2, and around 136 m3 t−1 (full irrigation) and 137 m3 t−1 (rainfed), in scenario B2. In this context irrigation has proved to be an important way to increase the sugarcane yield and reduce WFs. However water demands for full irrigated sugarcane destined for ethanol production showed different conditions of quantitative impairment of surface water resources in Paranaíba basin. The potential impacts may result in lack of adequate and equitable access to water, especially when the analysis considered the water availability for grants.

Assessment of the impacts of nonstationarity on watershed runoff using artificial neural networks: a case study in Ardebil, Iran

The purpose of this study is to investigate the impacts of climate change on the runoff of Gharehsoo River Basin in the northwest of Iran. In this research, the outputs of monthly precipitation and temperature data of PRECIS (Providing Regional Climates for Impacts Studies) model, a regional climate model with 50 × 50 km spatial resolution on the basis of B2 scenario, is used for the base (1961–1990) and the future (2071–2100) periods. The output results of PRECIS show that the average temperature of the watershed increased up to 2–5 °C, for the period spanning from 2070 to 2100. In addition, compare to the base period, we are expecting to receive more precipitation in future for the months of January, February, March, September and December. The artificial neural network (ANN) was applied to quantify the future discharge. The results show that in the future, the discharge of Gharehsoo River watershed decreases for all months. Moreover, the peak discharge in the future period happens 1 month earlier, due to increasing in the temperature and earlier start of snow melting season. Finally, 1 and 2 °C increase in temperature lead to 0.05–8.2 % and 0.1–13.4 % decrease of average monthly discharge, respectively.

Climate-induced land health risk in farmland systems: A case study of Qarasou sub-basin in Karkheh River Basin

ABSTRACTThe present study was carried out to investigate the impact of climate change on land suitability for agricultural development in a sub-basin of Karkheh River Basin, Iran. For this, land suitability of the sub-basin was evaluated twice; once regardless of the climate change impact, and again by involving the impact of climate change. Simple Limitation Approach was used to evaluate the suitability of the sub-basin for cultivation of winter wheat. According to the results, around 22.57% (124121.16 ha) of the study area is suitable for cropping while the capability of 39.29% (216086.13 ha) of the sub-basin was evaluated to be poor/moderate for this purpose. In this research, in order to investigate the impact of climate change on farmlands, the changing trend of the four variables of maximum and minimum temperature, precipitation, and radiation were stimulated by the year 2039 using downscaled interpolation of IPCM general circulation model under three emission scenarios of A1B, A2, and B1. The stimulation was done by LARS-WG Software. The overlaying was done once more, but this time using the stimulated values. Comparing the current and stimulated land suitability maps revealed the fact that, in the most pessimistic future under A1B scenario, approximately 15.51% (85288.95 ha) of the study area will lose its capability for farming as a result of an increase of 1.3˚C in temperature, and a decrease of 20.43% mm in total precipitation. The research finding emphasizes the risk of climate change on land health for farming purposes.

Modeling Land-Use and Land-Cover Change and Hydrological Responses under Consistent Climate Change Scenarios in the Heihe River Basin, China

This study investigated land-use and land-cover change (LUCC) and hydrological responses under consistent climate change scenarios (A1B and B1) in the Heihe River Basin (HRB), a typical arid inland river basin in northwest China. LUCC was first projected using the Dynamic Conversion of Land-Use and its Effects (Dyna-CLUE) model. Two cases (Case 1 and Case 2) were then established to quantify the hydrological responses to single climate change and the combined responses to climate change and LUCC with the Soil and Water Assessment Tool (SWAT). The results of LUCC modeling under the A1B and B1 scenarios present distinct regional characteristics and also indicate that the projected future land-use patterns are not appreciably different than the actual map for the year 2000. In Case 1, which only considers the impacts of single climate change, overall, the streamflow at the outlet of the upper HRB is projected to decline, whereas at the outlet of the middle HRB to increase, under both climate change scenarios. Meanwhile, the frequency of occurrence of hydrological extremes is expect to increase under both scenarios. In Case 2, which considers the combined impacts of climate change and LUCC, the changes in streamflow and frequency of hydrological extremes are found to be remarkably consistent with those in Case 1. The results imply that climate change rather than LUCC are primarily responsible for the hydrological variations. The role of LUCC varies with regions in the context of climate change dominated hydrological responses.

Flood analysis and flood projections under climate change in New Brunswick

Floods events are a key component in river engineering including the design and risk assessment of various projects. In this study, a flood frequency analysis was carried out to determine flood characteristics in New Brunswick under present and future climate. For current flood characteristics, an analysis was carried out using 56 hydrometric stations across the province using the Generalized Extreme Value (GEV) distribution and the three-parameter lognormal distribution function. A regional flood frequency analysis was also carried out using regression equations. Results showed that current regional flood equations were very consistent among distribution functions. Results were also consistent with previous studies. To study floods under climate change, seven catchments were selected within the province and these catchments were further analyzed using artificial neural network (ANN) models for two climate scenarios. As such, future climate data were extracted from the third-generation Coupled Climate Model (CGCM3.1) under the greenhouse gas emission scenarios B1 and A2. The climate variables (temperature and precipitation) were downscaled using the delta change approach, and future river discharges were predicted. A frequency analysis was then carried out on these seven stations using the GEV distribution function. Results showed that for the period 2010–2100, average temperatures are projected to increase between 2.9°C (B1) and 5.2°C (A2) in New Brunswick. As for precipitation, the mean annual precipitation showed an increase of 9 to 12% compared to current conditions. Results also showed an increase in flood flows. The increase in low-return floods (e.g. 2-year) was generally higher than the increase of higher return floods (e.g. 100-year). Depending on the scenario and the future time period, the increase in low-return floods was about 30%, and about 15% for higher return floods. A Regional Climate Index (RCI) was used to links floods to their frequency under future climate scenarios.

Analyzing the potential impacts of climate change on rainfed wheat production in Hamedan Province, Iran, via generalized additive models

Climate change is one of the greatest challenges in the 21st century and the agriculture sector is very vulnerable to this phenomenon. Since wheat is the most important cereal crop in Iran, we aim to analyze the potential impact of climatic variables (temperature and precipitation) on rainfed wheat productivity in Hamedan Province, Iran. For this purpose, generalized additive models have been used to model yields of rainfed wheat based on climatic variables during 2004–2012. Then, based on sensitivity of rainfed wheat to temperature and precipitation in this period, we predict the potential effects of climate change on rainfed wheat yield under the IPCC SRES A1FI and B1 climate change scenarios. Results suggest that yields of rainfed wheat would decrease in all Hamedan's counties primarily because of decreasing October to June precipitation and higher temperature. As a result, it is predicted that the yield of rainfed wheat in Hamedan under the A1F1 and B1 scenarios will fall by 41.3% and 20.6%, respectively, in the 2080s. In other words, according to the A1F1 scenario, in the 2080s, Hamedan Province's rainfed wheat production will decline from 1090 kg/ha to 639 kg/ha and under the B1 scenario to 865 kg/ha.

Changes in stratospheric ClO and HCl concentrations under different greenhouse gas emission scenarios

In this study, comparison of model results and satellite observations reveals that the Whole-Atmosphere Community Climate Model (WACCM-3) reasonably well reproduced the distributions and seasonal variations of ClO and HCl concentrations. In three greenhouse gas emission scenarios (A1B, A2, and B1), the ClO, Cl, ClONO2, and HCl concentrations would gradually decrease with time as emissions of ozone depleting substances (ODS) steadily decrease. The rates of the changes in the ClO, Cl, ClONO2, and HCl concentrations are different in the same emission scenario and the rates of change in the same composition concentration are different for different emission scenarios. The ClO, Cl, and ClONO2 concentrations decrease fastest in scenario A2, next fastest in scenario A1B, and slowest in scenario B1. In contrast, the HCl concentration decreases fastest in scenario B1. The ozone concentration recovers quickly, and is highest in scenario A2. The results show that a rapid decrease in the ClO concentration is an important reason for the accelerated recovery of the ozone layer in scenario A2.

Current and future estimates for the fire frequency and the fire rotation period in the main woodland types of peninsular Spain: a case-study approach

Aim of study. Fire regimes are frequently dynamic and change as a function of the interactions between the three main fire drivers: fuels, ignitions and climatic conditions. We characterized the recent period (1974-2005) and performed estimates for the future fire regimeArea of study. We have considered five pine and another four woodland types by means of the analyses of 100 reference areas in peninsular Spain.Material and methods. The estimates of the expected alterations in fire frequency and the fire rotation period were based on models previously developed for the climatic scenarios SRES A2 and B2.Main results. The results point to the large variability in fire frequency and rotation periods between the woodland types as defined, and also among the reference areas delimited for each of them. Fire frequencies will increase for all woodland types while very relevant shortenings of the fire rotation periods are expected. For the 32 yr period analysed, rotation periods longer than 500 yr were obtained in 54% of the reference areas while this percentage would decrease to 31% in the B2 and to 29% in the A2 climatic scenario. In the most affected woodland type, P. pinaster, from a median rotation period of 83 yr it would decrease to 26 yr in the B2 and to 20 yr in the A2 climatic scenario.Research highlights. We conclude that the predicted increases in fire activity will have adverse effects on some of the main Spanish woodland types due to the expected future disruptions in the fire regime. Keywords: Forest fires; fire regime; fire frequency; fire rotation period; climatic change.Abbreviations used: SRES: Special Report on Emissions Scenarios; IPCC: Intergovernmental Panel on Climate Change; RA: Reference Areas.

Study of the Climate Change Impacts on Water Quality in the Upstream Portion of the Cau River Basin, Vietnam

This paper presents simulations of climate change impacts on water quality in the upstream portion of the Cau River Basin in the North of Vietnam. The integrated modeling system GIBSI was used to simulate hydrological processes, pollutant and sediment wash-off in the river basin, and pollutant transport and transformation in the river network. Three projections for climate change based on emission scenarios B1, B2, and A2 of IPCC Special Report on Emission Scenarios (SRES) were considered. By assuming that the input pollution sources and watershed configuration were constant, based on 2008 data, water quality in the river network was simulated up to the terminal year 2050. For each climate change scenario, patterns of precipitation in wet and dry year were considered. The change in annual and monthly trends for dissolved oxygen (DO), biochemical oxygen demand (BOD), and ammonium ions (NH4+) load and concentration for different portions of the watershed have been analyzed. The results of these simulations show that climate change has more impact on changing the seasonal water quality parameters than on altering the average annual load of the pollutants. The percent change and change pattern in water quality parameters are different for wet and dry year, and the changes in wet year are smaller than those in dry year.

Projected impacts of climate change on water availability indicators in a semi-arid region of central Mexico

In many arid and semi-arid regions of the world, the scarcity of water resources, increasing population and the experience of recent droughts are exerting great pressures on water resources. Climate change is anticipated to exacerbate the vulnerability of water resources, which clearly highlights the need for developing sustainable water management policies and appropriate adaptation strategies. In this paper, the likely impact of climate change on water availability indicators in a semiarid region is explored through a case study in a developing country. Queretaro River Basin (QRB) in Central Mexico, is presented as an example of a semi-arid region that is facing growing pressures on the availability of water resources to sustainably meet social, economic and ecological needs. The output of seven downscaled Global Coupled Ocean-Atmosphere General Circulation Models (AOGCMs) for the B1 and A1B greenhouse gas emissions scenarios (GHGES) were used to investigate the likely impacts of climate change on water resources in the QRB. The computed future scenarios of climate change predict that increases in mean annual temperature ranging from 0.8 °C to 4.8 °C and decreases in mean annual precipitation ranging from 17% to 22% could result in a decline of up to 9.16% in the available water for groundwater recharge and runoff by the end of the 21st century. Results also suggest that for the future, both dry and wet events will become more severe and frequent, increasing the vulnerability of water resources and compromising sustainability. Therefore, it is advisable that water management planning considers flexible adaptation strategies in order to allow for adjustment under different scenarios of water availability, if the implementation of unbiased, efficient and economical water resources strategies is to enhance sustainability and resilience to climate change in the long-term.

Modeling the Projected Changes of River Flow in Central Vietnam under Different Climate Change Scenarios

Recent studies by the United Nations Environment Programme (UNEP) and the Intergovernmental Panel on Climate Change (IPCC) indicate that Vietnam is one of the countries most affected by climate change. The variability of climate in this region, characterized by large fluctuations in precipitation and temperature, has caused significant changes in surface water resources. This study aims to project the impact of climate change on the seasonal availability of surface water of the Huong River in Central Vietnam in the twenty-first century through hydrologic simulations driven by climate model projections. To calibrate and validate the hydrologic model, the model was forced by the rain gage-based gridded Asian Precipitation–Highly Resolved Observational Data Integration Towards Evaluation of water resources (APHRODITE) V1003R1 Monsoon Asia precipitation data along with observed temperature, humidity, wind speed, and solar radiation data from local weather stations. The simulated discharge was compared to observations for the period from 1951 until present. Three Global Climate Models (GCMs) ECHAM5-OM, HadCM3 and GFDL-CM2.1 integrated into Long Ashton Research Station-Weather Generator (LARS-WG) stochastic weather generator were run for three IPCC–Special Report on Emissions Scenarios (IPCC-SRES) emissions scenarios A1B, A2, and B1 to simulate future climate conditions. The hydrologic model simulated the Huong River discharge for each IPCC-SRES scenario. Simulation results under the three GCMs generally indicate an increase in summer and fall river discharge during the twenty-first century in A2 and B1 scenarios. For A1B scenario, HadCM3 and GFDL-CM2.1 models project a decrease in river discharge from present to the 2051–2080 period and then increase until the 2071–2100 period while ECHAM5-OM model produces opposite projection that discharge will increase until the 2051–2080 period and then decrease for the rest of the century. Water management impacts, such as irrigation or dam regulation, were not considered in this study. However, the results provide local policy makers with quantitative data to consider possible adjustment of future dam capacities for development of flood control policies.

Changes of Terrestrial Water Storage in River Basins of China Projected by RegCM4

In this study, a historic simulation covering the period from 1951 to 2000 and three projected scenario simulations covering 2001-2050 were conducted em- ploying the regional climate model RegCM4 to detect the changes of terrestrial water storage (TWS) in major river basins of China, using the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES): A1B, A2, and B1. The historic simula- tion revealed that the variations of TWS, which are dominated by precipitation in the basins, rely highly on their climatic features. Compared with the historic simu- lation, the changes of TWS in the scenario simulations showed strong regional differences. However, for all sce- narios, TWS was found to increase most in Northeast China and surrounding mountains around the Tibetan Plateau, and decrease most in eastern regions of China. Unlike the low seasonal variations of TWS in arid areas, the TWS showed strong seasonal variations in eastern monsoon areas, with the maximum changes usually oc- curring in summer, when TWS increases most in a year. Among the three scenario simulations, TWS increased most in Songhua River Basin of B1 scenario, and de- creased most in Pearl River Basin of A2 scenario and Hai River Basin of A1B scenario, accompanied by different annual trends and seasonal variations.

Simulation of climate change in Iran during 2071-2100 using PRECIS regional climate modelling system

Parameters such as future precipitation, temperature, snowfall, and runoff were modeled using PRECIS regionalclimate modeling system in Iran with the horizontal resolutions of 0.44×0.44°C in latitude and longitude under SRESA2 and B2 scenarios. The dataset was based on HadAM3p during the periods of 1961-1990 and 2071-2100. Theoverall precipitation error of the model in the period of 1961-1990 was 5.3%. Minimum errors were found to be overAzari, north-central, and Kordi regions. Maximum and minimum monthly precipitation errors were found inSeptember and May, respectively; but, minimum and maximum seasonal biases were found in spring and winter with-0.1 and -17.2% errors, respectively. Results revealed a decrease in mean annual precipitation toward the end of the21st century by 7.8 mm in B2 scenario and 10.1 mm in A2 Scenario with maximum regional decrease of 100 mm inthe southeast of the Caspian Sea. The decrease in precipitation was higher for A2 scenario, whereas it was minimumfor B1 scenario. Mean annual temperature of Iran during 2071-2100 would be projected to increase by 4.5-5.5°C inA2 scenario and 3-4°C in B2 scenarios compared to 1961-1990. It was shown that mean annual changes in runoffover the country were negligible both in A2 and B2 scenarios. Maximum annual amount of runoff increase was foundover western part of the Caspian Sea, Zagros and Alborz mountain chains by 6.4-15. 8mm. Results also indicated thatannual snowfall would decrease by the maximum amount of 22.9-23.7 cm over Zagros and Alborz mountain chains.

Indian Summer Monsoon Rainfall Processes in Climate Change Scenarios

Abstract Indian summer monsoon rainfall was examined in two different greenhouse gas emission scenarios: the Special Report on Emissions Scenarios (SRES; B1) and a similar greenhouse gas scenario, the new representative concentration pathways (RCPs; RCP4.5). The rainfall change in the climate model projections through remotely induced changes in precipitation processes and through changes in precipitation efficiency processes was discussed. To that end, two model setups were applied: 1) the regional climate model (RCM) Consortium for Small-Scale Modelling in Climate Mode (COSMO-CLM), nested in the global climate model (GCM) ECHAM5/Max Planck Institute ocean model (ECHAM5/MPIOM), applying the greenhouse gas scenario B1; and 2) the RCM nested in a newer version of the GCM, ECHAM6/MPIOM, incorporating the RCP4.5 scenario. Both GCM simulations showed a slight increase in precipitation over central India toward the end of the twenty-first century. This slight increase was the result of two largely compensating changes: increase of remotely induced precipitation and decrease of precipitation efficiency. The RCM with the scenario RCP4.5 followed this trend, but with smaller changes. However, the RCM with B1 showed a decreasing trend in precipitation because of a slightly larger absolute change of the reduced precipitation efficiency compared to the change caused by the remote processes. Changes of these processes in the scenario simulations were larger than the natural variability, as simulated in an unperturbed preindustrial greenhouse gas control (CTL) climate simulation. Results indicated that the projection of the Indian summer monsoon rainfall is still a key challenge for both the GCM and the RCM.

Assessment of the impacts of climate change and brackish irrigation water on rice productivity and evaluation of adaptation measures in Ca Mau province, Vietnam

This study investigates the temporal impacts of climate change on rice yield for summer-autumn (SA) and autumn-winter (AW) cropping pattern along with implication of brackish irrigation water for the SA season. Furthermore, evaluation of different agro-adaptations to overcome negative impacts of climate change was also done for Ca Mau province of Vietnam. Climatic variables were derived from six general circulation models which were further bias corrected at Ca Mau city station for three future time periods (2025s, 2055s, and 2085s). Calibrated AquaCrop 4.0 was used to project the future rice yield under climate change and different salinity levels in irrigation water. Simulation shows a decline in rice yield ranging from 1.60 to 23.69 % and 8.06 to 20.15 % by 2085s relative to baseline climate for A2 and B2 scenarios respectively in the case of the SA cropping season. However, an increase in rice yield ranging from 3.29 to 12.35 % and 6.64 to 17.23 % is observed for the corresponding time period and scenarios. Further simulations for the SA cropping season under climate change and increasing salinity in irrigation water suggest an insignificant increase in yield relative to the yield obtained without irrigation. Moreover, proper management practices, namely forward and early shifts in transplanting dates along with increasing fertilizer application rates, are observed to be beneficial to enhance the rice yield under climate change.